459  
Toggle Poster Visibility
Invited Talk
Thu Jul 12th 09:00 -- 10:00 AM @ A1
Intelligence per Kilowatthour
Max Welling
Session
Thu Jul 12th 10:00 -- 10:20 AM @ A1
Best Paper Session 2
Break
Thu Jul 12th 10:30 -- 11:00 AM @ Hall B
Coffee Break
Oral
Thu Jul 12th 11:00 -- 11:20 AM @ K1
Learning Memory Access Patterns
Milad Hashemi · Kevin Swersky · Jamie Smith · Grant Ayers · Heiner Litz · Jichuan Chang · Christos Kozyrakis · Parthasarathy Ranganathan
Oral
Thu Jul 12th 11:00 -- 11:20 AM @ A3
Learning Policy Representations in Multiagent Systems
Aditya Grover · Maruan Al-Shedivat · Jayesh Gupta · Yura Burda · Harrison Edwards
Oral
Thu Jul 12th 11:00 -- 11:20 AM @ A4
Learning unknown ODE models with Gaussian processes
Markus Heinonen · Cagatay Yildiz · Henrik Mannerström · Jukka Intosalmi · Harri Lähdesmäki
Oral
Thu Jul 12th 11:00 -- 11:20 AM @ A5
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time
Asish Ghoshal · Jean Honorio
Oral
Thu Jul 12th 11:00 -- 11:20 AM @ A6
Multicalibration: Calibration for the (Computationally-Identifiable) Masses
Ursula Hebert-Johnson · Michael Kim · Omer Reingold · Guy Rothblum
Oral
Thu Jul 12th 11:00 -- 11:20 AM @ K11
Probabilistic Boolean Tensor Decomposition
Tammo Rukat · Christopher Holmes · Christopher Yau
Oral
Thu Jul 12th 11:00 -- 11:20 AM @ A7
Geometry Score: A Method For Comparing Generative Adversarial Networks
Valentin Khrulkov · Ivan Oseledets
Oral
Thu Jul 12th 11:00 -- 11:20 AM @ A1
Convergent Tree Backup and Retrace with Function Approximation
Ahmed Touati · Pierre-Luc Bacon · Doina Precup · Pascal Vincent
Oral
Thu Jul 12th 11:00 -- 11:20 AM @ A9
Exploring Hidden Dimensions in Accelerating Convolutional Neural Networks
Zhihao Jia · Sina Lin · Charles Qi · Alex Aiken
Oral
Thu Jul 12th 11:00 -- 11:20 AM @ Victoria
Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care
Patrick Schwab · Emanuela Keller · Carl Muroi · David J. Mack · Christian Strässle · Walter Karlen
Oral
Thu Jul 12th 11:20 -- 11:40 AM @ A5
Differentiable Dynamic Programming for Structured Prediction and Attention
Arthur Mensch · Mathieu Blondel
Oral
Thu Jul 12th 11:20 -- 11:30 AM @ A6
Residual Unfairness in Fair Machine Learning from Prejudiced Data
Nathan Kallus · Angela Zhou
Oral
Thu Jul 12th 11:20 -- 11:40 AM @ Victoria
Compressing Neural Networks using the Variational Information Bottelneck
Bin Dai · Chen Zhu · Baining Guo · David Wipf
Oral
Thu Jul 12th 11:20 -- 11:30 AM @ K11
A Primal-Dual Analysis of Global Optimality in Nonconvex Low-Rank Matrix Recovery
Xiao Zhang · Lingxiao Wang · Yaodong Yu · Quanquan Gu
Oral
Thu Jul 12th 11:20 -- 11:30 AM @ A3
Learning to Coordinate with Coordination Graphs in Repeated Single-Stage Multi-Agent Decision Problems
Eugenio Bargiacchi · Timothy Verstraeten · Diederik Roijers · Ann Nowé · Hado van Hasselt
Oral
Thu Jul 12th 11:20 -- 11:40 AM @ A9
Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization
Jiaxiang Wu · Weidong Huang · Junzhou Huang · Tong Zhang
Oral
Thu Jul 12th 11:20 -- 11:30 AM @ A7
Optimizing the Latent Space of Generative Networks
Piotr Bojanowski · Armand Joulin · David Lopez-Paz · Arthur Szlam
Oral
Thu Jul 12th 11:20 -- 11:40 AM @ A4
Constraining the Dynamics of Deep Probabilistic Models
Marco Lorenzi · Maurizio Filippone
Oral
Thu Jul 12th 11:20 -- 11:40 AM @ A1
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation
Bo Dai · Albert Shaw · Lihong Li · Lin Xiao · Niao He · Zhen Liu · Jianshu Chen · Le Song
Oral
Thu Jul 12th 11:20 -- 11:40 AM @ K1
Geodesic Convolutional Shape Optimization
Pierre Baque · Edoardo Remelli · Francois Fleuret · EPFL Pascal Fua
Oral
Thu Jul 12th 11:30 -- 11:40 AM @ A3
Learning to Act in Decentralized Partially Observable MDPs
Jilles Dibangoye · Olivier Buffet
Oral
Thu Jul 12th 11:30 -- 11:40 AM @ A7
Adversarial Learning with Local Coordinate Coding
Jiezhang Cao · Yong Guo · Qingyao Wu · Chunhua Shen · Junzhou Huang · Mingkui Tan
Oral
Thu Jul 12th 11:30 -- 11:40 AM @ A6
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising
Borja de Balle Pigem · Yu-Xiang Wang
Oral
Thu Jul 12th 11:30 -- 11:40 AM @ K11
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion
Cong Ma · Kaizheng Wang · Yuejie Chi · Yuxin Chen
Oral
Thu Jul 12th 11:40 -- 11:50 AM @ A6
Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms
Xueru Zhang · Mohammad Khalili · Mingyan Liu
Oral
Thu Jul 12th 11:40 -- 11:50 AM @ K1
AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning
Ahmed M. Alaa Ibrahim · M van der Schaar
Oral
Thu Jul 12th 11:40 -- 11:50 AM @ A3
Modeling Others using Oneself in Multi-Agent Reinforcement Learning
Roberta Raileanu · Emily Denton · Arthur Szlam · Facebook Rob Fergus
Oral
Thu Jul 12th 11:40 -- 11:50 AM @ A4
Probabilistic Recurrent State-Space Models
Andreas Doerr · Christian Daniel · Martin Schiegg · Duy Nguyen-Tuong · Stefan Schaal · Marc Toussaint · Sebastian Trimpe
Oral
Thu Jul 12th 11:40 -- 11:50 AM @ A7
Learning Representations and Generative Models for 3D Point Clouds
Panagiotis Achlioptas · Olga Diamanti · Ioannis Mitliagkas · Leonidas Guibas
Oral
Thu Jul 12th 11:40 -- 11:50 AM @ A1
Scalable Bilinear Pi Learning Using State and Action Features
Yichen Chen · Lihong Li · Mengdi Wang
Oral
Thu Jul 12th 11:40 -- 11:50 AM @ Victoria
Kernelized Synaptic Weight Matrices
Lorenz Müller · Julien Martel · Giacomo Indiveri
Oral
Thu Jul 12th 11:40 -- 11:50 AM @ A9
DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding
Thomas Moreau · Laurent Oudre · Nicolas Vayatis
Oral
Thu Jul 12th 11:40 -- 11:50 AM @ A5
Structured Output Learning with Abstention: Application to Accurate Opinion Prediction
Alexandre Garcia · Telecom-ParisTech Chloé Clavel · Slim Essid · Florence d'Alche-Buc
Oral
Thu Jul 12th 11:40 -- 11:50 AM @ K11
Learning Binary Latent Variable Models: A Tensor Eigenpair Approach
Ariel Jaffe · Roi Weiss · Boaz Nadler · Shai Carmi · Yuval Kluger
Oral
Thu Jul 12th 11:50 AM -- 12:00 PM @ A3
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
Tabish Rashid · Mikayel Samvelyan · Christian Schroeder · Gregory Farquhar · Jakob Foerster · Shimon Whiteson
Oral
Thu Jul 12th 11:50 AM -- 12:00 PM @ A7
Theoretical Analysis of Image-to-Image Translation with Adversarial Learning
Xudong Pan · Mi Zhang · Daizong Ding
Oral
Thu Jul 12th 11:50 AM -- 12:00 PM @ A5
End-to-End Learning for the Deep Multivariate Probit Model
Di Chen · Yexiang Xue · Carla Gomes
Oral
Thu Jul 12th 11:50 AM -- 12:00 PM @ K11
Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization
Louis Filstroff · Alberto Lumbreras · Cedric Fevotte
Oral
Thu Jul 12th 11:50 AM -- 12:00 PM @ Victoria
Deep Models of Interactions Across Sets
Jason Hartford · Devon Graham · Kevin Leyton-Brown · Siamak Ravanbakhsh
Oral
Thu Jul 12th 11:50 AM -- 12:00 PM @ K1
TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service
Amartya Sanyal · Matt Kusner · Adria Gascon · Varun Kanade
Oral
Thu Jul 12th 11:50 AM -- 12:00 PM @ A1
Stochastic Variance-Reduced Policy Gradient
Matteo Papini · Damiano Binaghi · Giuseppe Canonaco · Matteo Pirotta · Marcello Restelli
Oral
Thu Jul 12th 11:50 AM -- 12:00 PM @ A4
Structured Variationally Auto-encoded Optimization
Xiaoyu Lu · Javier González · Zhenwen Dai · Neil Lawrence
Oral
Thu Jul 12th 11:50 AM -- 12:00 PM @ A6
Adversarial Regression with Multiple Learners
Liang Tong · Sixie Yu · Scott Alfeld · Yevgeniy Vorobeychik
Oral
Thu Jul 12th 11:50 AM -- 12:00 PM @ A9
Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go?
Zhengyuan Zhou · Panayotis Mertikopoulos · Nicholas Bambos · Peter Glynn · Yinyu Ye · Li-Jia Li · Li Fei-Fei
Break
Thu Jul 12th 12:00 -- 01:30 PM @
Lunch - on your own
Oral
Thu Jul 12th 01:30 -- 01:50 PM @ A1
Investigating Human Priors for Playing Video Games
Rachit Dubey · Pulkit Agrawal · Deepak Pathak · Tom Griffiths · Alexei Efros
Oral
Thu Jul 12th 01:30 -- 01:50 PM @ A5
Accelerated Spectral Ranking
Arpit Agarwal · Prathamesh Patil · Shivani Agarwal
Oral
Thu Jul 12th 01:30 -- 01:50 PM @ K1
Learning One Convolutional Layer with Overlapping Patches
Surbhi Goel · Adam Klivans · Raghu Meka
Oral
Thu Jul 12th 01:30 -- 01:50 PM @ A9
Shampoo: Preconditioned Stochastic Tensor Optimization
Vineet Gupta · Tomer Koren · Yoram Singer
Oral
Thu Jul 12th 01:30 -- 01:50 PM @ A3
Fast Information-theoretic Bayesian Optimisation
Binxin Ru · Michael A Osborne · Mark Mcleod · Diego Granziol
Oral
Thu Jul 12th 01:30 -- 01:50 PM @ A7
Composite Functional Gradient Learning of Generative Adversarial Models
Rie Johnson · Tong Zhang
Oral
Thu Jul 12th 01:30 -- 01:50 PM @ K11
Improved large-scale graph learning through ridge spectral sparsification
Daniele Calandriello · Alessandro Lazaric · Ioannis Koutis · Michal Valko
Oral
Thu Jul 12th 01:30 -- 01:50 PM @ A4
Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap
Miles Lopes · Shusen Wang · Michael Mahoney
Oral
Thu Jul 12th 01:30 -- 01:50 PM @ Victoria
Focused Hierarchical RNNs for Conditional Sequence Processing
Rosemary Nan Ke · Konrad Zolna · Alessandro Sordoni · MILA Zhouhan Lin · Adam Trischler · Yoshua Bengio · Joelle Pineau · Laurent Charlin · Christopher Pal
Oral
Thu Jul 12th 01:30 -- 01:50 PM @ A6
Inductive Two-Layer Modeling with Parametric Bregman Transfer
Vignesh Ganapathiraman · Zhan Shi · Xinhua Zhang · Yaoliang Yu
Oral
Thu Jul 12th 01:50 -- 02:00 PM @ A1
Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?
Maithra Raghu · Alexander Irpan · Jacob Andreas · Bobby Kleinberg · Quoc Le · Jon Kleinberg
Oral
Thu Jul 12th 01:50 -- 02:10 PM @ K11
Parallel and Streaming Algorithms for K-Core Decomposition
Hossein Esfandiari · Silvio Lattanzi · Vahab Mirrokni
Oral
Thu Jul 12th 01:50 -- 02:00 PM @ A5
Composite Marginal Likelihood Methods for Random Utility Models
Zhibing Zhao · Lirong Xia
Oral
Thu Jul 12th 01:50 -- 02:10 PM @ Victoria
Learn from Your Neighbor: Learning Multi-modal Mappings from Sparse Annotations
Ashwin Kalyan · Stefan Lee · Anitha Kannan · Dhruv Batra
Oral
Thu Jul 12th 01:50 -- 02:10 PM @ A3
Optimization, fast and slow: optimally switching between local and Bayesian optimization
Mark McLeod · Stephen Roberts · Michael A Osborne
Oral
Thu Jul 12th 01:50 -- 02:00 PM @ A6
Does Distributionally Robust Supervised Learning Give Robust Classifiers?
Weihua Hu · Gang Niu · Issei Sato · Masashi Sugiyama
Oral
Thu Jul 12th 01:50 -- 02:00 PM @ A7
Tempered Adversarial Networks
Mehdi S. M. Sajjadi · Giambattista Parascandolo · Arash Mehrjou · Bernhard Schölkopf
Oral
Thu Jul 12th 01:50 -- 02:00 PM @ A4
Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization
Umut Simsekli · Cagatay Yildiz · Thanh Huy Nguyen · Ali Taylan Cemgil · Gaël RICHARD
Oral
Thu Jul 12th 01:50 -- 02:00 PM @ A9
Characterizing Implicit Bias in Terms of Optimization Geometry
Suriya Gunasekar · Jason Lee · Daniel Soudry · Nati Srebro
Oral
Thu Jul 12th 01:50 -- 02:10 PM @ K1
Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima
Simon Du · Jason Lee · Yuandong Tian · Aarti Singh · Barnabás Póczos
Oral
Thu Jul 12th 02:00 -- 02:10 PM @ A6
Prediction Rule Reshaping
Matt Bonakdarpour · Sabyasachi Chatterjee · Rina Barber · John Lafferty
Oral
Thu Jul 12th 02:00 -- 02:10 PM @ A1
GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms
Cédric Colas · Olivier Sigaud · Pierre-Yves Oudeyer
Oral
Thu Jul 12th 02:00 -- 02:10 PM @ A4
Stochastic Variance-Reduced Hamilton Monte Carlo Methods
Difan Zou · Pan Xu · Quanquan Gu
Oral
Thu Jul 12th 02:00 -- 02:10 PM @ A5
Ranking Distributions based on Noisy Sorting
Adil El Mesaoudi-Paul · Eyke Hüllermeier · Robert Busa-Fekete
Oral
Thu Jul 12th 02:00 -- 02:10 PM @ A9
A Distributed Second-Order Algorithm You Can Trust
Celestine Dünner · Aurelien Lucchi · Matilde Gargiani · An Bian · Thomas Hofmann · Martin Jaggi
Oral
Thu Jul 12th 02:00 -- 02:10 PM @ A7
Improved Training of Generative Adversarial Networks Using Representative Features
Duhyeon Bang · Hyunjung Shim
Oral
Thu Jul 12th 02:10 -- 02:20 PM @ A3
Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design
Wenlong Lyu · Fan Yang · Changhao Yan · Dian Zhou · Xuan Zeng
Oral
Thu Jul 12th 02:10 -- 02:20 PM @ K1
The Multilinear Structure of ReLU Networks
Thomas Laurent · James von Brecht
Oral
Thu Jul 12th 02:10 -- 02:20 PM @ Victoria
Learning long term dependencies via Fourier recurrent units
Jiong Zhang · Yibo Lin · Zhao Song · Inderjit Dhillon
Oral
Thu Jul 12th 02:10 -- 02:20 PM @ A9
A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning
Konstantin Mishchenko · Franck Iutzeler · Jérôme Malick · Massih-Reza Amini
Oral
Thu Jul 12th 02:10 -- 02:20 PM @ A4
A Robust Approach to Sequential Information Theoretic Planning
Sue Zheng · Jason Pacheco · John Fisher
Oral
Thu Jul 12th 02:10 -- 02:20 PM @ A5
SQL-Rank: A Listwise Approach to Collaborative Ranking
LIWEI WU · Cho-Jui Hsieh · University of California James Sharpnack
Oral
Thu Jul 12th 02:10 -- 02:20 PM @ A6
Finding Influential Training Samples for Gradient Boosted Decision Trees
Boris Sharchilev · Yury Ustinovskiy · Pavel Serdyukov · Maarten de Rijke
Oral
Thu Jul 12th 02:10 -- 02:20 PM @ K11
Fast Approximate Spectral Clustering for Dynamic Networks
Lionel Martin · Andreas Loukas · Pierre Vandergheynst
Oral
Thu Jul 12th 02:10 -- 02:20 PM @ A7
A Two-Step Computation of the Exact GAN Wasserstein Distance
Huidong Liu · Xianfeng GU · Samaras Dimitris
Oral
Thu Jul 12th 02:10 -- 02:20 PM @ A1
Time Limits in Reinforcement Learning
Fabio Pardo · Arash Tavakoli · Vitaly Levdik · Petar Kormushev
Oral
Thu Jul 12th 02:20 -- 02:30 PM @ A9
Gradient Coding from Cyclic MDS Codes and Expander Graphs
Netanel Raviv · Rashish Tandon · Alexandros Dimakis · Itzhak Tamo
Oral
Thu Jul 12th 02:20 -- 02:30 PM @ A7
Is Generator Conditioning Causally Related to GAN Performance?
Augustus Odena · Jacob Buckman · Catherine Olsson · Tom B Brown · Christopher Olah · Colin Raffel · Ian Goodfellow
Oral
Thu Jul 12th 02:20 -- 02:30 PM @ K11
Matrix Norms in Data Streams: Faster, Multi-Pass and Row-Order
Vladimir Braverman · Stephen Chestnut · Robert Krauthgamer · Yi Li · David Woodruff · Lin Yang
Oral
Thu Jul 12th 02:20 -- 02:30 PM @ Victoria
Training Neural Machines with Trace-Based Supervision
Matthew Mirman · Dimitar Dimitrov · Pavle Djordjevic · Timon Gehr · Martin Vechev
Oral
Thu Jul 12th 02:20 -- 02:30 PM @ K1
Understanding the Loss Surface of Neural Networks for Binary Classification
SHIYU LIANG · Ruoyu Sun · Yixuan Li · R Srikant
Oral
Thu Jul 12th 02:20 -- 02:30 PM @ A3
Tight Regret Bounds for Bayesian Optimization in One Dimension
Jonathan Scarlett
Oral
Thu Jul 12th 02:20 -- 02:30 PM @ A1
Visualizing and Understanding Atari Agents
Samuel Greydanus · Anurag Koul · Jonathan Dodge · Alan Fern
Oral
Thu Jul 12th 02:20 -- 02:30 PM @ A4
Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms
Yi Wu · Siddharth Srivastava · Nicholas Hay · Simon Du · Stuart Russell
Oral
Thu Jul 12th 02:20 -- 02:30 PM @ A5
Extreme Learning to Rank via Low Rank Assumption
Minhao Cheng · Ian Davidson · Cho-Jui Hsieh
Oral
Thu Jul 12th 02:20 -- 02:30 PM @ A6
Noise2Noise: Learning Image Restoration without Clean Data
Jaakko Lehtinen · Jacob Munkberg · Jon Hasselgren · Samuli Laine · Tero Karras · Miika Aittala · Timo Aila
Oral
Thu Jul 12th 02:30 -- 02:50 PM @ A3
To Understand Deep Learning We Need to Understand Kernel Learning
Mikhail Belkin · Siyuan Ma · Soumik Mandal
Oral
Thu Jul 12th 02:30 -- 02:50 PM @ Victoria
Neural Dynamic Programming for Musical Self Similarity
Christian Walder · Dongwoo Kim
Oral
Thu Jul 12th 02:30 -- 02:50 PM @ A9
Alternating Randomized Block Coordinate Descent
Jelena Diakonikolas · Orecchia Lorenzo
Oral
Thu Jul 12th 02:30 -- 02:50 PM @ K11
Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices
Zengfeng Huang
Oral
Thu Jul 12th 02:30 -- 02:50 PM @ A1
The Mirage of Action-Dependent Baselines in Reinforcement Learning
George Tucker · Surya Bhupatiraju · Shixiang Gu · Richard E Turner · Zoubin Ghahramani · Sergey Levine
Oral
Thu Jul 12th 02:30 -- 02:50 PM @ A7
Black-box Adversarial Attacks with Limited Queries and Information
Andrew Ilyas · Logan Engstrom · Anish Athalye · Jessy Lin
Oral
Thu Jul 12th 02:30 -- 02:50 PM @ A6
Dimensionality-Driven Learning with Noisy Labels
Xingjun Ma · Yisen Wang · Michael E. Houle · Shuo Zhou · Sarah Erfani · Shutao Xia · Sudanthi Wijewickrema · James Bailey
Oral
Thu Jul 12th 02:30 -- 02:50 PM @ A5
Feasible Arm Identification
Julian Katz-Samuels · Clay Scott
Oral
Thu Jul 12th 02:30 -- 02:50 PM @ A4
Robust and Scalable Models of Microbiome Dynamics
Travis Gibson · Georg Gerber
Oral
Thu Jul 12th 02:30 -- 02:50 PM @ K1
Tropical Geometry of Deep Neural Networks
Liwen Zhang · Gregory Naisat · Lek-Heng Lim
Oral
Thu Jul 12th 02:50 -- 03:00 PM @ Victoria
A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music
Adam Roberts · Jesse Engel · Colin Raffel · Curtis Hawthorne · Douglas Eck
Oral
Thu Jul 12th 02:50 -- 03:00 PM @ K11
Loss Decomposition for Fast Learning in Large Output Spaces
En-Hsu Yen · Satyen Kale · Felix Xinnan Yu · Daniel Holtmann-Rice · Sanjiv Kumar · Pradeep Ravikumar
Oral
Thu Jul 12th 02:50 -- 03:00 PM @ A4
Stein Variational Message Passing for Continuous Graphical Models
Dilin Wang · Zhe Zeng · Qiang Liu
Oral
Thu Jul 12th 02:50 -- 03:10 PM @ K1
A Spline Theory of Deep Learning
Randall Balestriero · Richard Baraniuk
Oral
Thu Jul 12th 02:50 -- 03:10 PM @ A3
Kernel Recursive ABC: Point Estimation with Intractable Likelihood
Takafumi Kajihara · Motonobu Kanagawa · Keisuke Yamazaki · Kenji Fukumizu
Oral
Thu Jul 12th 02:50 -- 03:10 PM @ A9
Randomized Block Cubic Newton Method
Nikita Doikov · Peter Richtarik
Oral
Thu Jul 12th 02:50 -- 03:10 PM @ A5
Bandits with Delayed, Aggregated Anonymous Feedback
Ciara Pike-Burke · Shipra Agrawal · Csaba Szepesvari · Steffen Grünewälder
Oral
Thu Jul 12th 02:50 -- 03:10 PM @ A1
Smoothed Action Value Functions for Learning Gaussian Policies
Ofir Nachum · Mohammad Norouzi · George Tucker · Dale Schuurmans
Oral
Thu Jul 12th 02:50 -- 03:10 PM @ A7
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye · Nicholas Carlini · David Wagner
Oral
Thu Jul 12th 02:50 -- 03:00 PM @ A6
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels
Lu Jiang · Zhengyuan Zhou · Thomas Leung · Li-Jia Li · Li Fei-Fei
Oral
Thu Jul 12th 03:00 -- 03:10 PM @ A4
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models
Beilun Wang · Arshdeep Sekhon · Yanjun Qi
Oral
Thu Jul 12th 03:00 -- 03:10 PM @ K11
Ultra Large-Scale Feature Selection using Count-Sketches
Amirali Aghazadeh · Ryan Spring · Daniel LeJeune · Gautam Dasarathy · Anshumali Shrivastava · Richard Baraniuk
Oral
Thu Jul 12th 03:00 -- 03:10 PM @ Victoria
Fast Decoding in Sequence Models Using Discrete Latent Variables
Lukasz M Kaiser · Samy Bengio · Aurko Roy · Ashish Vaswani · Niki Parmar · Jakob Uszkoreit · Noam Shazeer
Oral
Thu Jul 12th 03:00 -- 03:10 PM @ A6
Learning to Reweight Examples for Robust Deep Learning
Mengye Ren · Wenyuan Zeng · Bin Yang · Raquel Urtasun
Oral
Thu Jul 12th 03:10 -- 03:20 PM @ Victoria
PixelSNAIL: An Improved Autoregressive Generative Model
Xi Chen · Nikhil Mishra · Mostafa Rohaninejad · Pieter Abbeel
Oral
Thu Jul 12th 03:10 -- 03:20 PM @ A9
Accelerating Greedy Coordinate Descent Methods
Haihao Lu · Robert Freund · Vahab Mirrokni
Oral
Thu Jul 12th 03:10 -- 03:20 PM @ A5
Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits
Zeyuan Allen-Zhu · Sebastien Bubeck · Yuanzhi Li
Oral
Thu Jul 12th 03:10 -- 03:20 PM @ A4
Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion
Richard Zhang · Salar Fattahi · Somayeh Sojoudi
Oral
Thu Jul 12th 03:10 -- 03:20 PM @ K1
Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions
Quynh Nguyen · Mahesh Mukkamala · Matthias Hein
Oral
Thu Jul 12th 03:10 -- 03:20 PM @ A1
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
Tuomas Haarnoja · Aurick Zhou · Pieter Abbeel · Sergey Levine
Oral
Thu Jul 12th 03:10 -- 03:20 PM @ A6
Curriculum Learning by Transfer Learning: Theory and Experiments with Deep Networks
Daphna Weinshall · Gad A Cohen · Dan Amir
Oral
Thu Jul 12th 03:10 -- 03:20 PM @ K11
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions
Shuaiwen Wang · Wenda Zhou · Haihao Lu · Arian Maleki · Vahab Mirrokni
Oral
Thu Jul 12th 03:10 -- 03:20 PM @ A7
Adversarial Attack on Graph Structured Data
Hanjun Dai · Hui Li · Tian Tian · Xin Huang · Lin Wang · Jun Zhu · Le Song
Oral
Thu Jul 12th 03:10 -- 03:20 PM @ A3
Differentially Private Database Release via Kernel Mean Embeddings
Matej Balog · Ilya Tolstikhin · Bernhard Schölkopf
Oral
Thu Jul 12th 03:20 -- 03:30 PM @ A5
Thompson Sampling for Combinatorial Semi-Bandits
Siwei Wang · Wei Chen
Oral
Thu Jul 12th 03:20 -- 03:30 PM @ A6
Improving Regression Performance with Distributional Losses
Ehsan Imani · Martha White
Oral
Thu Jul 12th 03:20 -- 03:30 PM @ A3
Learning in Reproducing Kernel Kreı̆n Spaces
Dino Oglic · Thomas Gaertner
Oral
Thu Jul 12th 03:20 -- 03:30 PM @ A1
Addressing Function Approximation Error in Actor-Critic Methods
Scott Fujimoto · Herke van Hoof · David Meger
Oral
Thu Jul 12th 03:20 -- 03:30 PM @ A9
On Acceleration with Noise-Corrupted Gradients
Michael Cohen · Jelena Diakonikolas · Orecchia Lorenzo
Oral
Thu Jul 12th 03:20 -- 03:30 PM @ Victoria
Image Transformer
Niki Parmar · Ashish Vaswani · Jakob Uszkoreit · Lukasz M Kaiser · Noam Shazeer · Alexander Ku · Dustin Tran
Oral
Thu Jul 12th 03:20 -- 03:30 PM @ A7
GAIN: Missing Data Imputation using Generative Adversarial Nets
Jinsung Yoon · James Jordon · Mihaela van der Schaar
Oral
Thu Jul 12th 03:20 -- 03:30 PM @ K1
Stronger Generalization Bounds for Deep Nets via a Compression Approach
Sanjeev Arora · Rong Ge · Behnam Neyshabur · Yi Zhang
Oral
Thu Jul 12th 03:20 -- 03:30 PM @ K11
Semi-Supervised Learning on Data Streams via Temporal Label Propagation
Tal Wagner · Sudipto Guha · Shiva Kasiviswanathan · Nina Mishra
Oral
Thu Jul 12th 03:20 -- 03:30 PM @ A4
Bucket Renormalization for Approximate Inference
Sung-Soo Ahn · Michael Chertkov · Adrian Weller · Jinwoo Shin
Break
Thu Jul 12th 03:30 -- 04:00 PM @ Hall B
Coffee Break
Oral
Thu Jul 12th 04:00 -- 04:20 PM @ A3
Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron
RJ Skerry-Ryan · Eric Battenberg · Ying Xiao · Yuxuan Wang · Daisy Stanton · Joel Shor · Ron Weiss · Robert Clark · Rif Saurous
Oral
Thu Jul 12th 04:00 -- 04:20 PM @ Victoria
Using Inherent Structures to design Lean 2-layer RBMs
Abhishek Bansal · Abhinav Anand · Chiranjib Bhattacharyya
Oral
Thu Jul 12th 04:00 -- 04:20 PM @ A4
Variational Bayesian dropout: pitfalls and fixes
Jiri Hron · Alexander Matthews · Zoubin Ghahramani
Oral
Thu Jul 12th 04:00 -- 04:20 PM @ A5
Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity
Lin Chen · Christopher Harshaw · Hamed Hassani · Amin Karbasi
Oral
Thu Jul 12th 04:00 -- 04:20 PM @ K11
Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings
Aryan Mokhtari · Hamed Hassani · Amin Karbasi
Oral
Thu Jul 12th 04:00 -- 04:20 PM @ A1
Configurable Markov Decision Processes
Alberto Maria Metelli · Mirco Mutti · Marcello Restelli
Oral
Thu Jul 12th 04:00 -- 04:20 PM @ A9
Approximate message passing for amplitude based optimization
Junjie Ma · Ji Xu · Arian Maleki
Oral
Thu Jul 12th 04:00 -- 04:20 PM @ A7
The Mechanics of n-Player Differentiable Games
David Balduzzi · Sebastien Racaniere · James Martens · Jakob Foerster · Karl Tuyls · Thore Graepel
Oral
Thu Jul 12th 04:00 -- 04:20 PM @ A6
Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods
Junhong Lin · Volkan Cevher
Oral
Thu Jul 12th 04:00 -- 04:20 PM @ K1
Reviving and Improving Recurrent Back-Propagation
Renjie Liao · Yuwen Xiong · Ethan Fetaya · Lisa Zhang · KiJung Yoon · Zachary S Pitkow · Raquel Urtasun · Richard Zemel
Oral
Thu Jul 12th 04:20 -- 04:40 PM @ A6
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
Dong Yin · Yudong Chen · Kannan Ramchandran · Peter Bartlett
Oral
Thu Jul 12th 04:20 -- 04:30 PM @ A7
K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning
Jihun Hamm · Yung-Kyun Noh
Oral
Thu Jul 12th 04:20 -- 04:30 PM @ Victoria
Deep Asymmetric Multi-task Feature Learning
Hae Beom Lee · Eunho Yang · Sung Ju Hwang
Oral
Thu Jul 12th 04:20 -- 04:30 PM @ A4
Accurate Uncertainties for Deep Learning Using Calibrated Regression
Volodymyr Kuleshov · Nathan Fenner · Stefano Ermon
Oral
Thu Jul 12th 04:20 -- 04:40 PM @ A1
Beyond the One-Step Greedy Approach in Reinforcement Learning
Yonathan Efroni · Gal Dalal · Bruno Scherrer · Shie Mannor
Oral
Thu Jul 12th 04:20 -- 04:30 PM @ K11
Approximation Guarantees for Adaptive Sampling
Eric Balkanski · Yaron Singer
Oral
Thu Jul 12th 04:20 -- 04:40 PM @ A9
Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients
Lukas Balles · Philipp Hennig
Oral
Thu Jul 12th 04:20 -- 04:40 PM @ A5
Practical Contextual Bandits with Regression Oracles
Dylan Foster · Alekh Agarwal · Miroslav Dudik · Haipeng Luo · Robert Schapire
Oral
Thu Jul 12th 04:20 -- 04:30 PM @ K1
Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks
Minmin Chen · Jeffrey Pennington · Samuel Schoenholz
Oral
Thu Jul 12th 04:20 -- 04:40 PM @ A3
Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis
Yuxuan Wang · Daisy Stanton · Yu Zhang · RJ-Skerry Ryan · Eric Battenberg · Joel Shor · Ying Xiao · Ye Jia · Fei Ren · Rif Saurous
Oral
Thu Jul 12th 04:30 -- 04:40 PM @ K11
Greed is Still Good: Maximizing Monotone Submodular+Supermodular (BP) Functions
Wenruo Bai · Jeff Bilmes
Oral
Thu Jul 12th 04:30 -- 04:40 PM @ Victoria
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations
Yiping Lu · Aoxiao Zhong · Quanzheng Li · Bin Dong
Oral
Thu Jul 12th 04:30 -- 04:40 PM @ A4
Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning
Stefan Depeweg · Jose Hernandez-Lobato · Finale Doshi-Velez · Steffen Udluft
Oral
Thu Jul 12th 04:30 -- 04:40 PM @ A7
First Order Generative Adversarial Networks
Calvin Seward · Thomas Unterthiner · Urs M Bergmann · Nikolay Jetchev · Sepp Hochreiter
Oral
Thu Jul 12th 04:30 -- 04:40 PM @ K1
Invariance of Weight Distributions in Rectified MLPs
Susumu Tsuchida · Fred Roosta · Marcus Gallagher
Oral
Thu Jul 12th 04:40 -- 04:50 PM @ A1
Policy and Value Transfer in Lifelong Reinforcement Learning
David Abel · Yuu Jinnai · Sophie Guo · George Konidaris · Michael L. Littman
Oral
Thu Jul 12th 04:40 -- 04:50 PM @ A6
Functional Gradient Boosting based on Residual Network Perception
Atsushi Nitanda · Taiji Suzuki
Oral
Thu Jul 12th 04:40 -- 04:50 PM @ A5
Fast Stochastic AUC Maximization with $O(1/n)$-Convergence Rate
Mingrui Liu · Xiaoxuan Zhang · Zaiyi Chen · Xiaoyu Wang · Tianbao Yang
Oral
Thu Jul 12th 04:40 -- 04:50 PM @ A4
Scalable approximate Bayesian inference for particle tracking data
Ruoxi Sun · Department of Statistics Liam Paninski
Oral
Thu Jul 12th 04:40 -- 04:50 PM @ A3
Fitting New Speakers Based on a Short Untranscribed Sample
Eliya Nachmani · Adam Polyak · Yaniv Taigman · Lior Wolf
Oral
Thu Jul 12th 04:40 -- 04:50 PM @ A9
prDeep: Robust Phase Retrieval with a Flexible Deep Network
Christopher Metzler · Phillip Schniter · Ashok Veeraraghavan · Richard Baraniuk
Oral
Thu Jul 12th 04:40 -- 04:50 PM @ Victoria
Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples
Gail Weiss · Yoav Goldberg · Eran Yahav
Oral
Thu Jul 12th 04:40 -- 04:50 PM @ A7
Towards Fast Computation of Certified Robustness for ReLU Networks
Tsui-Wei (Lily) Weng · Huan Zhang · Hongge Chen · Zhao Song · Cho-Jui Hsieh · Luca Daniel · Duane Boning · Inderjit Dhillon
Oral
Thu Jul 12th 04:40 -- 04:50 PM @ K11
Constrained Interacting Submodular Groupings
Andrew Cotter · Mahdi Milani Fard · Seungil You · Maya Gupta · Jeff Bilmes
Oral
Thu Jul 12th 04:40 -- 04:50 PM @ K1
Learning Dynamics of Linear Denoising Autoencoders
Arnu Pretorius · Steve Kroon · Herman Kamper
Oral
Thu Jul 12th 04:50 -- 05:00 PM @ A4
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Mohammad Emtiyaz Khan · Didrik Nielsen · Voot Tangkaratt · Wu Lin · Yarin Gal · Akash Srivastava
Oral
Thu Jul 12th 04:50 -- 05:00 PM @ A9
Accelerating Natural Gradient with Higher-Order Invariance
Yang Song · Jiaming Song · Stefano Ermon
Oral
Thu Jul 12th 04:50 -- 05:00 PM @ A1
Importance Weighted Transfer of Samples in Reinforcement Learning
Andrea Tirinzoni · Andrea Sessa · Matteo Pirotta · Marcello Restelli
Oral
Thu Jul 12th 04:50 -- 05:00 PM @ A7
LaVAN: Localized and Visible Adversarial Noise
Danny Karmon · Daniel Zoran · Yoav Goldberg
Oral
Thu Jul 12th 04:50 -- 05:00 PM @ Victoria
High Performance Zero-Memory Overhead Direct Convolutions
Jiyuan Zhang · Franz Franchetti · Tze Meng Low
Oral
Thu Jul 12th 04:50 -- 05:00 PM @ A6
Binary Classification with Karmic, Threshold-Quasi-Concave Metrics
Bowei Yan · Sanmi Koyejo · Kai Zhong · Pradeep Ravikumar
Oral
Thu Jul 12th 04:50 -- 05:00 PM @ K11
Fast Maximization of Non-Submodular, Monotonic Functions on the Integer Lattice
Alan Kuhnle · J. Smith · Victoria Crawford · My Thai
Oral
Thu Jul 12th 04:50 -- 05:00 PM @ K1
Understanding Generalization and Optimization Performance of Deep CNNs
Pan Zhou · Jiashi Feng
Oral
Thu Jul 12th 04:50 -- 05:00 PM @ A5
Stochastic Proximal Algorithms for AUC Maximization
Michael Natole Jr · Yiming Ying · Siwei Lyu
Oral
Thu Jul 12th 04:50 -- 05:00 PM @ A3
Towards Binary-Valued Gates for Robust LSTM Training
Zhuohan Li · Di He · Fei Tian · Wei Chen · Tao Qin · Liwei Wang · Tie-Yan Liu
Oral
Thu Jul 12th 05:00 -- 05:20 PM @ K11
Representation Tradeoffs for Hyperbolic Embeddings
Frederic Sala · Chris De Sa · Albert Gu · Christopher Re
Oral
Thu Jul 12th 05:00 -- 05:20 PM @ A7
Synthesizing Programs for Images using Reinforced Adversarial Learning
Iaroslav Ganin · Tejas Kulkarni · Igor Babuschkin · S. M. Ali Eslami · Oriol Vinyals
Oral
Thu Jul 12th 05:00 -- 05:20 PM @ A1
An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning
Dhruv Malik · Malayandi Palaniappan · Jaime Fisac · Dylan Hadfield-Menell · Stuart Russell · EECS Anca Dragan
Oral
Thu Jul 12th 05:00 -- 05:20 PM @ A5
Let’s be Honest: An Optimal No-Regret Framework for Zero-Sum Games
Ehsan Asadi Kangarshahi · Ya-Ping Hsieh · Mehmet Fatih Sahin · Volkan Cevher
Oral
Thu Jul 12th 05:00 -- 05:20 PM @ A3
Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation
Dane Corneil · Wulfram Gerstner · Johanni Brea
Oral
Thu Jul 12th 05:00 -- 05:20 PM @ Victoria
ContextNet: Deep learning for Star Galaxy Classification
Noble Kennamer · University of California David Kirkby · Alexander Ihler · University of California Francisco Javier Sanchez-Lopez
Oral
Thu Jul 12th 05:00 -- 05:20 PM @ A6
SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate
Aaditya Ramdas · Tijana Zrnic · Martin Wainwright · Michael Jordan
Oral
Thu Jul 12th 05:00 -- 05:20 PM @ K1
Composable Planning with Attributes
Amy Zhang · Sainbayar Sukhbaatar · Adam Lerer · Arthur Szlam · Facebook Rob Fergus
Oral
Thu Jul 12th 05:00 -- 05:20 PM @ A4
Neural Autoregressive Flows
Chin-Wei Huang · David Krueger · Alexandre Lacoste · Aaron Courville
Oral
Thu Jul 12th 05:00 -- 05:20 PM @ A9
Stochastic Wasserstein Barycenters
Sebastian Claici · Edward Chien · Justin Solomon
Oral
Thu Jul 12th 05:20 -- 05:40 PM @ K1
Measuring abstract reasoning in neural networks
Adam Santoro · Feilx Hill · David GT Barrett · Ari S Morcos · Timothy Lillicrap
Oral
Thu Jul 12th 05:20 -- 05:30 PM @ A6
Open Category Detection with PAC Guarantees
Si Liu · Risheek Garrepalli · Thomas Dietterich · Alan Fern · Dan Hendrycks
Oral
Thu Jul 12th 05:20 -- 05:40 PM @ K11
Massively Parallel Algorithms and Hardness for Single-Linkage Clustering under $\ell_p$ Distances
Grigory Yaroslavtsev · Adithya Vadapalli
Oral
Thu Jul 12th 05:20 -- 05:30 PM @ A9
Learning Compact Neural Networks with Regularization
Samet Oymak
Oral
Thu Jul 12th 05:20 -- 05:40 PM @ A3
Deep Variational Reinforcement Learning for POMDPs
Maximilian Igl · Luisa Zintgraf · Tuan Anh Le · Frank Wood · Shimon Whiteson
Oral
Thu Jul 12th 05:20 -- 05:30 PM @ A4
Distilling the Posterior in Bayesian Neural Networks
Kuan-Chieh Wang · Paul Vicol · James Lucas · Li Gu · Roger Grosse · Richard Zemel
Oral
Thu Jul 12th 05:20 -- 05:30 PM @ A5
Weakly Consistent Optimal Pricing Algorithms in Repeated Posted-Price Auctions with Strategic Buyer
Alexey Drutsa
Oral
Thu Jul 12th 05:20 -- 05:30 PM @ A7
MAGAN: Aligning Biological Manifolds
Matt Amodio · Smita Krishnaswamy
Oral
Thu Jul 12th 05:20 -- 05:30 PM @ A1
Fast Bellman Updates for Robust MDPs
Chin Pang Ho · Marek Petrik · Wolfram Wiesemann
Oral
Thu Jul 12th 05:20 -- 05:30 PM @ Victoria
Autoregressive Convolutional Neural Networks for Asynchronous Time Series
Mikolaj Binkowski · Gautier Marti · Philippe Donnat
Oral
Thu Jul 12th 05:30 -- 05:40 PM @ A7
Max-Mahalanobis Linear Discriminant Analysis Networks
Tianyu Pang · Chao Du · Jun Zhu
Oral
Thu Jul 12th 05:30 -- 05:40 PM @ A9
Riemannian Stochastic Recursive Gradient Algorithm with Retraction and Vector Transport and Its Convergence Analysis
Hiroyuki Kasai · Hiroyuki Sato · Bamdev Mishra
Oral
Thu Jul 12th 05:30 -- 05:40 PM @ A6
Unbiased Objective Estimation in Predictive Optimization
Shinji Ito · Akihiro Yabe · Ryohei Fujimaki
Oral
Thu Jul 12th 05:30 -- 05:40 PM @ A1
Decoupling Gradient-Like Learning Rules from Representations
Philip Thomas · Christoph Dann · Emma Brunskill
Oral
Thu Jul 12th 05:30 -- 05:40 PM @ A5
Self-Bounded Prediction Suffix Tree via Approximate String Matching
Dongwoo Kim · Christian Walder
Oral
Thu Jul 12th 05:30 -- 05:40 PM @ Victoria
Hierarchical Multi-Label Classification Networks
Jonatas Wehrmann · Ricardo Cerri · Rodrigo Barros
Oral
Thu Jul 12th 05:30 -- 05:40 PM @ A4
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks
Mattias Teye · Hossein Azizpour · Kevin Smith
Oral
Thu Jul 12th 05:40 -- 05:50 PM @ A3
Recurrent Predictive State Policy Networks
Ahmed Hefny · Zita Marinho · Wen Sun · Siddhartha Srinivasa · Geoff Gordon
Oral
Thu Jul 12th 05:40 -- 05:50 PM @ A5
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection
Jeremias Knoblauch · Theodoros Damoulas
Oral
Thu Jul 12th 05:40 -- 05:50 PM @ A6
Goodness-of-fit Testing for Discrete Distributions via Stein Discrepancy
Jiasen Yang · Qiang Liu · Vinayak A Rao · Jennifer Neville
Oral
Thu Jul 12th 05:40 -- 05:50 PM @ A9
Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering
Ahmed Douik · Babak Hassibi
Oral
Thu Jul 12th 05:40 -- 05:50 PM @ K1
GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks
Zhao Chen · Vijay Badrinarayanan · Chen-Yu Lee · Andrew Rabinovich
Oral
Thu Jul 12th 05:40 -- 05:50 PM @ A1
PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos
Paavo Parmas · Carl E Rasmussen · Jan Peters · Kenji Doya
Oral
Thu Jul 12th 05:40 -- 05:50 PM @ A4
Noisy Natural Gradient as Variational Inference
Guodong Zhang · Shengyang Sun · David Duvenaud · Roger Grosse
Oral
Thu Jul 12th 05:40 -- 05:50 PM @ Victoria
Nonparametric variable importance using an augmented neural network with multi-task learning
Jean Feng · Brian Williamson · Noah Simon · Marco Carone
Oral
Thu Jul 12th 05:40 -- 05:50 PM @ K11
Local Density Estimation in High Dimensions
Xian Wu · Moses Charikar · Vishnu Natchu
Oral
Thu Jul 12th 05:40 -- 05:50 PM @ A7
Adversarial Time-to-Event Modeling
Paidamoyo Chapfuwa · Chenyang Tao · Chunyuan Li · Courtney Page · Benjamin Goldstein · Lawrence Carin · Ricardo Henao
Oral
Thu Jul 12th 05:50 -- 06:00 PM @ Victoria
Knowledge Transfer with Jacobian Matching
Suraj Srinivas · Francois Fleuret
Oral
Thu Jul 12th 05:50 -- 06:00 PM @ A9
Graphical Nonconvex Optimization via an Adaptive Convex Relaxation
Qiang Sun · Kean Ming Tan · Han Liu · Tong Zhang
Oral
Thu Jul 12th 05:50 -- 06:00 PM @ A7
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training
Xi Wu · Wooyeong Jang · Jiefeng Chen · Lingjiao Chen · Somesh Jha
Oral
Thu Jul 12th 05:50 -- 06:00 PM @ A1
Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning
Thomas Dietterich · George Trimponias · Zhitang Chen
Oral
Thu Jul 12th 05:50 -- 06:00 PM @ K11
Improving Sign Random Projections With Additional Information
Keegan Kang · Wei Pin Wong
Oral
Thu Jul 12th 05:50 -- 06:00 PM @ A3
Regret Minimization for Partially Observable Deep Reinforcement Learning
Peter Jin · EECS Kurt Keutzer · Sergey Levine
Oral
Thu Jul 12th 05:50 -- 06:00 PM @ A4
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors
Soumya Ghosh · Jiayu Yao · Finale Doshi-Velez
Oral
Thu Jul 12th 05:50 -- 06:00 PM @ A6
Towards Black-box Iterative Machine Teaching
Weiyang Liu · Bo Dai · Xingguo Li · Zhen Liu · James Rehg · Le Song
Oral
Thu Jul 12th 05:50 -- 06:00 PM @ K1
Explicit Inductive Bias for Transfer Learning with Convolutional Networks
Xuhong LI · Yves Grandvalet · Franck Davoine
Oral
Thu Jul 12th 05:50 -- 06:00 PM @ A5
Learning Localized Spatio-Temporal Models From Streaming Data
Muhammad Osama · Dave Zachariah · Thomas Schön
Break
Thu Jul 12th 06:15 -- 07:15 PM @ Hall B
Light Evening Snack
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #1
Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion
Richard Zhang · Salar Fattahi · Somayeh Sojoudi
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #2
Robust and Scalable Models of Microbiome Dynamics
Travis Gibson · Georg Gerber
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #3
Explicit Inductive Bias for Transfer Learning with Convolutional Networks
Xuhong LI · Yves Grandvalet · Franck Davoine
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #4
GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks
Zhao Chen · Vijay Badrinarayanan · Chen-Yu Lee · Andrew Rabinovich
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #5
Optimizing the Latent Space of Generative Networks
Piotr Bojanowski · Armand Joulin · David Lopez-Paz · Arthur Szlam
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #6
Theoretical Analysis of Image-to-Image Translation with Adversarial Learning
Xudong Pan · Mi Zhang · Daizong Ding
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #7
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
Tuomas Haarnoja · Aurick Zhou · Pieter Abbeel · Sergey Levine
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #8
PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos
Paavo Parmas · Carl E Rasmussen · Jan Peters · Kenji Doya
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #9
Probabilistic Recurrent State-Space Models
Andreas Doerr · Christian Daniel · Martin Schiegg · Duy Nguyen-Tuong · Stefan Schaal · Marc Toussaint · Sebastian Trimpe
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #10
Structured Variationally Auto-encoded Optimization
Xiaoyu Lu · Javier González · Zhenwen Dai · Neil Lawrence
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #11
A Robust Approach to Sequential Information Theoretic Planning
Sue Zheng · Jason Pacheco · John Fisher
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #12
Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap
Miles Lopes · Shusen Wang · Michael Mahoney
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #13
Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go?
Zhengyuan Zhou · Panayotis Mertikopoulos · Nicholas Bambos · Peter Glynn · Yinyu Ye · Li-Jia Li · Li Fei-Fei
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #14
Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization
Jiaxiang Wu · Weidong Huang · Junzhou Huang · Tong Zhang
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #15
Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering
Ahmed Douik · Babak Hassibi
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #16
Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients
Lukas Balles · Philipp Hennig
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #17
Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning
Thomas Dietterich · George Trimponias · Zhitang Chen
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #18
Differentially Private Database Release via Kernel Mean Embeddings
Matej Balog · Ilya Tolstikhin · Bernhard Schölkopf
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #19
Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples
Gail Weiss · Yoav Goldberg · Eran Yahav
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #20
Neural Dynamic Programming for Musical Self Similarity
Christian Walder · Dongwoo Kim
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #21
Learning long term dependencies via Fourier recurrent units
Jiong Zhang · Yibo Lin · Zhao Song · Inderjit Dhillon
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #22
Autoregressive Convolutional Neural Networks for Asynchronous Time Series
Mikolaj Binkowski · Gautier Marti · Philippe Donnat
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #23
Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation
Dane Corneil · Wulfram Gerstner · Johanni Brea
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #24
Regret Minimization for Partially Observable Deep Reinforcement Learning
Peter Jin · EECS Kurt Keutzer · Sergey Levine
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #25
Goodness-of-fit Testing for Discrete Distributions via Stein Discrepancy
Jiasen Yang · Qiang Liu · Vinayak A Rao · Jennifer Neville
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #26
Unbiased Objective Estimation in Predictive Optimization
Shinji Ito · Akihiro Yabe · Ryohei Fujimaki
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #27
Ultra Large-Scale Feature Selection using Count-Sketches
Amirali Aghazadeh · Ryan Spring · Daniel LeJeune · Gautam Dasarathy · Anshumali Shrivastava · Richard Baraniuk
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #28
Matrix Norms in Data Streams: Faster, Multi-Pass and Row-Order
Vladimir Braverman · Stephen Chestnut · Robert Krauthgamer · Yi Li · David Woodruff · Lin Yang
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #29
Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?
Maithra Raghu · Alexander Irpan · Jacob Andreas · Bobby Kleinberg · Quoc Le · Jon Kleinberg
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #30
The Mirage of Action-Dependent Baselines in Reinforcement Learning
George Tucker · Surya Bhupatiraju · Shixiang Gu · Richard E Turner · Zoubin Ghahramani · Sergey Levine
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #31
Composite Marginal Likelihood Methods for Random Utility Models
Zhibing Zhao · Lirong Xia
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #32
Ranking Distributions based on Noisy Sorting
Adil El Mesaoudi-Paul · Eyke Hüllermeier · Robert Busa-Fekete
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #33
DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding
Thomas Moreau · Laurent Oudre · Nicolas Vayatis
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #34
Exploring Hidden Dimensions in Accelerating Convolutional Neural Networks
Zhihao Jia · Sina Lin · Charles Qi · Alex Aiken
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #35
Deep Models of Interactions Across Sets
Jason Hartford · Devon Graham · Kevin Leyton-Brown · Siamak Ravanbakhsh
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #36
ContextNet: Deep learning for Star Galaxy Classification
Noble Kennamer · University of California David Kirkby · Alexander Ihler · University of California Francisco Javier Sanchez-Lopez
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #37
First Order Generative Adversarial Networks
Calvin Seward · Thomas Unterthiner · Urs M Bergmann · Nikolay Jetchev · Sepp Hochreiter
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #38
Max-Mahalanobis Linear Discriminant Analysis Networks
Tianyu Pang · Chao Du · Jun Zhu
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #39
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time
Asish Ghoshal · Jean Honorio
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #40
Structured Output Learning with Abstention: Application to Accurate Opinion Prediction
Alexandre Garcia · Telecom-ParisTech Chloé Clavel · Slim Essid · Florence d'Alche-Buc
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #41
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation
Bo Dai · Albert Shaw · Lihong Li · Lin Xiao · Niao He · Zhen Liu · Jianshu Chen · Le Song
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #42
Smoothed Action Value Functions for Learning Gaussian Policies
Ofir Nachum · Mohammad Norouzi · George Tucker · Dale Schuurmans
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #43
Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron
RJ Skerry-Ryan · Eric Battenberg · Ying Xiao · Yuxuan Wang · Daisy Stanton · Joel Shor · Ron Weiss · Robert Clark · Rif Saurous
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #44
Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis
Yuxuan Wang · Daisy Stanton · Yu Zhang · RJ-Skerry Ryan · Eric Battenberg · Joel Shor · Ying Xiao · Ye Jia · Fei Ren · Rif Saurous
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #45
AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning
Ahmed M. Alaa Ibrahim · M van der Schaar
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #46
TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service
Amartya Sanyal · Matt Kusner · Adria Gascon · Varun Kanade
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #47
End-to-End Learning for the Deep Multivariate Probit Model
Di Chen · Yexiang Xue · Carla Gomes
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #48
Differentiable Dynamic Programming for Structured Prediction and Attention
Arthur Mensch · Mathieu Blondel
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #49
Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods
Junhong Lin · Volkan Cevher
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #50
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
Dong Yin · Yudong Chen · Kannan Ramchandran · Peter Bartlett
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #51
SQL-Rank: A Listwise Approach to Collaborative Ranking
LIWEI WU · Cho-Jui Hsieh · University of California James Sharpnack
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #52
Extreme Learning to Rank via Low Rank Assumption
Minhao Cheng · Ian Davidson · Cho-Jui Hsieh
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #53
Adversarial Attack on Graph Structured Data
Hanjun Dai · Hui Li · Tian Tian · Xin Huang · Lin Wang · Jun Zhu · Le Song
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #54
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training
Xi Wu · Wooyeong Jang · Jiefeng Chen · Lingjiao Chen · Somesh Jha
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #55
Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization
Louis Filstroff · Alberto Lumbreras · Cedric Fevotte
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #56
Learning Binary Latent Variable Models: A Tensor Eigenpair Approach
Ariel Jaffe · Roi Weiss · Boaz Nadler · Shai Carmi · Yuval Kluger
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #57
Thompson Sampling for Combinatorial Semi-Bandits
Siwei Wang · Wei Chen
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #58
Let’s be Honest: An Optimal No-Regret Framework for Zero-Sum Games
Ehsan Asadi Kangarshahi · Ya-Ping Hsieh · Mehmet Fatih Sahin · Volkan Cevher
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #59
Deep Asymmetric Multi-task Feature Learning
Hae Beom Lee · Eunho Yang · Sung Ju Hwang
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #60
Learn from Your Neighbor: Learning Multi-modal Mappings from Sparse Annotations
Ashwin Kalyan · Stefan Lee · Anitha Kannan · Dhruv Batra
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #61
Stein Variational Message Passing for Continuous Graphical Models
Dilin Wang · Zhe Zeng · Qiang Liu
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #62
Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms
Yi Wu · Siddharth Srivastava · Nicholas Hay · Simon Du · Stuart Russell
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #63
Towards Binary-Valued Gates for Robust LSTM Training
Zhuohan Li · Di He · Fei Tian · Wei Chen · Tao Qin · Liwei Wang · Tie-Yan Liu
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #64
Fitting New Speakers Based on a Short Untranscribed Sample
Eliya Nachmani · Adam Polyak · Yaniv Taigman · Lior Wolf
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #65
Stochastic Variance-Reduced Policy Gradient
Matteo Papini · Damiano Binaghi · Giuseppe Canonaco · Matteo Pirotta · Marcello Restelli
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #66
Convergent Tree Backup and Retrace with Function Approximation
Ahmed Touati · Pierre-Luc Bacon · Doina Precup · Pascal Vincent
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #67
Alternating Randomized Block Coordinate Descent
Jelena Diakonikolas · Orecchia Lorenzo
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #68
Shampoo: Preconditioned Stochastic Tensor Optimization
Vineet Gupta · Tomer Koren · Yoram Singer
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #69
Stochastic Wasserstein Barycenters
Sebastian Claici · Edward Chien · Justin Solomon
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #70
Accelerating Natural Gradient with Higher-Order Invariance
Yang Song · Jiaming Song · Stefano Ermon
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #71
Learning unknown ODE models with Gaussian processes
Markus Heinonen · Cagatay Yildiz · Henrik Mannerström · Jukka Intosalmi · Harri Lähdesmäki
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #72
Constraining the Dynamics of Deep Probabilistic Models
Marco Lorenzi · Maurizio Filippone
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #73
Fast Decoding in Sequence Models Using Discrete Latent Variables
Lukasz M Kaiser · Samy Bengio · Aurko Roy · Ashish Vaswani · Niki Parmar · Jakob Uszkoreit · Noam Shazeer
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #74
High Performance Zero-Memory Overhead Direct Convolutions
Jiyuan Zhang · Franz Franchetti · Tze Meng Low
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #75
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions
Shuaiwen Wang · Wenda Zhou · Haihao Lu · Arian Maleki · Vahab Mirrokni
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #76
Improved large-scale graph learning through ridge spectral sparsification
Daniele Calandriello · Alessandro Lazaric · Ioannis Koutis · Michal Valko
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #77
Distilling the Posterior in Bayesian Neural Networks
Kuan-Chieh Wang · Paul Vicol · James Lucas · Li Gu · Roger Grosse · Richard Zemel
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #78
Scalable approximate Bayesian inference for particle tracking data
Ruoxi Sun · Department of Statistics Liam Paninski
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #79
Weakly Consistent Optimal Pricing Algorithms in Repeated Posted-Price Auctions with Strategic Buyer
Alexey Drutsa
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #80
Practical Contextual Bandits with Regression Oracles
Dylan Foster · Alekh Agarwal · Miroslav Dudik · Haipeng Luo · Robert Schapire
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #81
Stochastic Variance-Reduced Hamilton Monte Carlo Methods
Difan Zou · Pan Xu · Quanquan Gu
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #82
Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization
Umut Simsekli · Cagatay Yildiz · Thanh Huy Nguyen · Ali Taylan Cemgil · Gaël RICHARD
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #83
GAIN: Missing Data Imputation using Generative Adversarial Nets
Jinsung Yoon · James Jordon · Mihaela van der Schaar
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #84
Synthesizing Programs for Images using Reinforced Adversarial Learning
Iaroslav Ganin · Tejas Kulkarni · Igor Babuschkin · S. M. Ali Eslami · Oriol Vinyals
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #85
Geometry Score: A Method For Comparing Generative Adversarial Networks
Valentin Khrulkov · Ivan Oseledets
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #86
Addressing Function Approximation Error in Actor-Critic Methods
Scott Fujimoto · Herke van Hoof · David Meger
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #87
Fast Bellman Updates for Robust MDPs
Chin Pang Ho · Marek Petrik · Wolfram Wiesemann
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #88
Configurable Markov Decision Processes
Alberto Maria Metelli · Mirco Mutti · Marcello Restelli
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #89
Prediction Rule Reshaping
Matt Bonakdarpour · Sabyasachi Chatterjee · Rina Barber · John Lafferty
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #90
Dimensionality-Driven Learning with Noisy Labels
Xingjun Ma · Yisen Wang · Michael E. Houle · Shuo Zhou · Sarah Erfani · Shutao Xia · Sudanthi Wijewickrema · James Bailey
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #91
Learning Memory Access Patterns
Milad Hashemi · Kevin Swersky · Jamie Smith · Grant Ayers · Heiner Litz · Jichuan Chang · Christos Kozyrakis · Parthasarathy Ranganathan
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #92
Geodesic Convolutional Shape Optimization
Pierre Baque · Edoardo Remelli · Francois Fleuret · EPFL Pascal Fua
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #93
Visualizing and Understanding Atari Agents
Samuel Greydanus · Anurag Koul · Jonathan Dodge · Alan Fern
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #94
An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning
Dhruv Malik · Malayandi Palaniappan · Jaime Fisac · Dylan Hadfield-Menell · Stuart Russell · EECS Anca Dragan
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #95
Is Generator Conditioning Causally Related to GAN Performance?
Augustus Odena · Jacob Buckman · Catherine Olsson · Tom B Brown · Christopher Olah · Colin Raffel · Ian Goodfellow
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #96
K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning
Jihun Hamm · Yung-Kyun Noh
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #97
Inductive Two-Layer Modeling with Parametric Bregman Transfer
Vignesh Ganapathiraman · Zhan Shi · Xinhua Zhang · Yaoliang Yu
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #98
Does Distributionally Robust Supervised Learning Give Robust Classifiers?
Weihua Hu · Gang Niu · Issei Sato · Masashi Sugiyama
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #99
Understanding Generalization and Optimization Performance of Deep CNNs
Pan Zhou · Jiashi Feng
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #100
The Multilinear Structure of ReLU Networks
Thomas Laurent · James von Brecht
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #101
Parallel and Streaming Algorithms for K-Core Decomposition
Hossein Esfandiari · Silvio Lattanzi · Vahab Mirrokni
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #102
Fast Approximate Spectral Clustering for Dynamic Networks
Lionel Martin · Andreas Loukas · Pierre Vandergheynst
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #103
Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima
Simon Du · Jason Lee · Yuandong Tian · Aarti Singh · Barnabás Póczos
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #104
Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions
Quynh Nguyen · Mahesh Mukkamala · Matthias Hein
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #105
Greed is Still Good: Maximizing Monotone Submodular+Supermodular (BP) Functions
Wenruo Bai · Jeff Bilmes
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #106
Black-box Adversarial Attacks with Limited Queries and Information
Andrew Ilyas · Logan Engstrom · Anish Athalye · Jessy Lin
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #107
Using Inherent Structures to design Lean 2-layer RBMs
Abhishek Bansal · Abhinav Anand · Chiranjib Bhattacharyya
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #108
Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care
Patrick Schwab · Emanuela Keller · Carl Muroi · David J. Mack · Christian Strässle · Walter Karlen
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #109
Composable Planning with Attributes
Amy Zhang · Sainbayar Sukhbaatar · Adam Lerer · Arthur Szlam · Facebook Rob Fergus
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #110
Measuring abstract reasoning in neural networks
Adam Santoro · Feilx Hill · David GT Barrett · Ari S Morcos · Timothy Lillicrap
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #111
Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity
Lin Chen · Christopher Harshaw · Hamed Hassani · Amin Karbasi
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #112
Self-Bounded Prediction Suffix Tree via Approximate String Matching
Dongwoo Kim · Christian Walder
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #113
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels
Lu Jiang · Zhengyuan Zhou · Thomas Leung · Li-Jia Li · Li Fei-Fei
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #114
Curriculum Learning by Transfer Learning: Theory and Experiments with Deep Networks
Daphna Weinshall · Gad A Cohen · Dan Amir
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #115
Composite Functional Gradient Learning of Generative Adversarial Models
Rie Johnson · Tong Zhang
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #116
LaVAN: Localized and Visible Adversarial Noise
Danny Karmon · Daniel Zoran · Yoav Goldberg
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #117
Approximation Guarantees for Adaptive Sampling
Eric Balkanski · Yaron Singer
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #118
Constrained Interacting Submodular Groupings
Andrew Cotter · Mahdi Milani Fard · Seungil You · Maya Gupta · Jeff Bilmes
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #119
Residual Unfairness in Fair Machine Learning from Prejudiced Data
Nathan Kallus · Angela Zhou
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #120
Adversarial Regression with Multiple Learners
Liang Tong · Sixie Yu · Scott Alfeld · Yevgeniy Vorobeychik
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #121
Representation Tradeoffs for Hyperbolic Embeddings
Frederic Sala · Chris De Sa · Albert Gu · Christopher Re
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #122
Improving Sign Random Projections With Additional Information
Keegan Kang · Wei Pin Wong
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #123
Bandits with Delayed, Aggregated Anonymous Feedback
Ciara Pike-Burke · Shipra Agrawal · Csaba Szepesvari · Steffen Grünewälder
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #124
Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits
Zeyuan Allen-Zhu · Sebastien Bubeck · Yuanzhi Li
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #125
Learning Policy Representations in Multiagent Systems
Aditya Grover · Maruan Al-Shedivat · Jayesh Gupta · Yura Burda · Harrison Edwards
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #126
Learning to Coordinate with Coordination Graphs in Repeated Single-Stage Multi-Agent Decision Problems
Eugenio Bargiacchi · Timothy Verstraeten · Diederik Roijers · Ann Nowé · Hado van Hasselt
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #127
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations
Yiping Lu · Aoxiao Zhong · Quanzheng Li · Bin Dong
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #128
Compressing Neural Networks using the Variational Information Bottelneck
Bin Dai · Chen Zhu · Baining Guo · David Wipf
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #129
Scalable Bilinear Pi Learning Using State and Action Features
Yichen Chen · Lihong Li · Mengdi Wang
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #130
Time Limits in Reinforcement Learning
Fabio Pardo · Arash Tavakoli · Vitaly Levdik · Petar Kormushev
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #131
Semi-Supervised Learning on Data Streams via Temporal Label Propagation
Tal Wagner · Sudipto Guha · Shiva Kasiviswanathan · Nina Mishra
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #132
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion
Cong Ma · Kaizheng Wang · Yuejie Chi · Yuxin Chen
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #133
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models
Beilun Wang · Arshdeep Sekhon · Yanjun Qi
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #134
Bucket Renormalization for Approximate Inference
Sung-Soo Ahn · Michael Chertkov · Adrian Weller · Jinwoo Shin
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #135
Kernel Recursive ABC: Point Estimation with Intractable Likelihood
Takafumi Kajihara · Motonobu Kanagawa · Keisuke Yamazaki · Kenji Fukumizu
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #136
Modeling Others using Oneself in Multi-Agent Reinforcement Learning
Roberta Raileanu · Emily Denton · Arthur Szlam · Facebook Rob Fergus
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #137
Tropical Geometry of Deep Neural Networks
Liwen Zhang · Gregory Naisat · Lek-Heng Lim
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #138
Learning Dynamics of Linear Denoising Autoencoders
Arnu Pretorius · Steve Kroon · Herman Kamper
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #139
Nonparametric variable importance using an augmented neural network with multi-task learning
Jean Feng · Brian Williamson · Noah Simon · Marco Carone
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #140
Training Neural Machines with Trace-Based Supervision
Matthew Mirman · Dimitar Dimitrov · Pavle Djordjevic · Timon Gehr · Martin Vechev
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #141
Open Category Detection with PAC Guarantees
Si Liu · Risheek Garrepalli · Thomas Dietterich · Alan Fern · Dan Hendrycks
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #142
SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate
Aaditya Ramdas · Tijana Zrnic · Martin Wainwright · Michael Jordan
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #143
Learning Localized Spatio-Temporal Models From Streaming Data
Muhammad Osama · Dave Zachariah · Thomas Schön
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #144
Feasible Arm Identification
Julian Katz-Samuels · Clay Scott
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #145
Fast Maximization of Non-Submodular, Monotonic Functions on the Integer Lattice
Alan Kuhnle · J. Smith · Victoria Crawford · My Thai
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #146
Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings
Aryan Mokhtari · Hamed Hassani · Amin Karbasi
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #147
Towards Fast Computation of Certified Robustness for ReLU Networks
Tsui-Wei (Lily) Weng · Huan Zhang · Hongge Chen · Zhao Song · Cho-Jui Hsieh · Luca Daniel · Duane Boning · Inderjit Dhillon
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #148
A Two-Step Computation of the Exact GAN Wasserstein Distance
Huidong Liu · Xianfeng GU · Samaras Dimitris
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #149
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection
Jeremias Knoblauch · Theodoros Damoulas
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #150
Fast Stochastic AUC Maximization with $O(1/n)$-Convergence Rate
Mingrui Liu · Xiaoxuan Zhang · Zaiyi Chen · Xiaoyu Wang · Tianbao Yang
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #151
Accurate Uncertainties for Deep Learning Using Calibrated Regression
Volodymyr Kuleshov · Nathan Fenner · Stefano Ermon
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #152
Neural Autoregressive Flows
Chin-Wei Huang · David Krueger · Alexandre Lacoste · Aaron Courville
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #153
Probabilistic Boolean Tensor Decomposition
Tammo Rukat · Christopher Holmes · Christopher Yau
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #154
A Primal-Dual Analysis of Global Optimality in Nonconvex Low-Rank Matrix Recovery
Xiao Zhang · Lingxiao Wang · Yaodong Yu · Quanquan Gu
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #155
A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning
Konstantin Mishchenko · Franck Iutzeler · Jérôme Malick · Massih-Reza Amini
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #156
Randomized Block Cubic Newton Method
Nikita Doikov · Peter Richtarik
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #157
Massively Parallel Algorithms and Hardness for Single-Linkage Clustering under $\ell_p$ Distances
Grigory Yaroslavtsev · Adithya Vadapalli
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #158
Local Density Estimation in High Dimensions
Xian Wu · Moses Charikar · Vishnu Natchu
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #159
To Understand Deep Learning We Need to Understand Kernel Learning
Mikhail Belkin · Siyuan Ma · Soumik Mandal
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #160
Learning in Reproducing Kernel Kreı̆n Spaces
Dino Oglic · Thomas Gaertner
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #161
Functional Gradient Boosting based on Residual Network Perception
Atsushi Nitanda · Taiji Suzuki
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #162
Binary Classification with Karmic, Threshold-Quasi-Concave Metrics
Bowei Yan · Sanmi Koyejo · Kai Zhong · Pradeep Ravikumar
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #163
Characterizing Implicit Bias in Terms of Optimization Geometry
Suriya Gunasekar · Jason Lee · Daniel Soudry · Nati Srebro
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #164
prDeep: Robust Phase Retrieval with a Flexible Deep Network
Christopher Metzler · Phillip Schniter · Ashok Veeraraghavan · Richard Baraniuk
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #165
Adversarial Time-to-Event Modeling
Paidamoyo Chapfuwa · Chenyang Tao · Chunyuan Li · Courtney Page · Benjamin Goldstein · Lawrence Carin · Ricardo Henao
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #166
MAGAN: Aligning Biological Manifolds
Matt Amodio · Smita Krishnaswamy
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #167
Multicalibration: Calibration for the (Computationally-Identifiable) Masses
Ursula Hebert-Johnson · Michael Kim · Omer Reingold · Guy Rothblum
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #168
Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms
Xueru Zhang · Mohammad Khalili · Mingyan Liu
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #169
PixelSNAIL: An Improved Autoregressive Generative Model
Xi Chen · Nikhil Mishra · Mostafa Rohaninejad · Pieter Abbeel
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #170
Focused Hierarchical RNNs for Conditional Sequence Processing
Rosemary Nan Ke · Konrad Zolna · Alessandro Sordoni · MILA Zhouhan Lin · Adam Trischler · Yoshua Bengio · Joelle Pineau · Laurent Charlin · Christopher Pal
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #171
Noise2Noise: Learning Image Restoration without Clean Data
Jaakko Lehtinen · Jacob Munkberg · Jon Hasselgren · Samuli Laine · Tero Karras · Miika Aittala · Timo Aila
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #172
Learning to Reweight Examples for Robust Deep Learning
Mengye Ren · Wenyuan Zeng · Bin Yang · Raquel Urtasun
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #173
Policy and Value Transfer in Lifelong Reinforcement Learning
David Abel · Yuu Jinnai · Sophie Guo · George Konidaris · Michael L. Littman
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #174
GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms
Cédric Colas · Olivier Sigaud · Pierre-Yves Oudeyer
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #175
A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music
Adam Roberts · Jesse Engel · Colin Raffel · Curtis Hawthorne · Douglas Eck
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #176
Understanding the Loss Surface of Neural Networks for Binary Classification
SHIYU LIANG · Ruoyu Sun · Yixuan Li · R Srikant
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #177
Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks
Minmin Chen · Jeffrey Pennington · Samuel Schoenholz
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #178
Reviving and Improving Recurrent Back-Propagation
Renjie Liao · Yuwen Xiong · Ethan Fetaya · Lisa Zhang · KiJung Yoon · Zachary S Pitkow · Raquel Urtasun · Richard Zemel
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #179
Riemannian Stochastic Recursive Gradient Algorithm with Retraction and Vector Transport and Its Convergence Analysis
Hiroyuki Kasai · Hiroyuki Sato · Bamdev Mishra
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #180
Learning Compact Neural Networks with Regularization
Samet Oymak
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #181
Investigating Human Priors for Playing Video Games
Rachit Dubey · Pulkit Agrawal · Deepak Pathak · Tom Griffiths · Alexei Efros
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #182
Decoupling Gradient-Like Learning Rules from Representations
Philip Thomas · Christoph Dann · Emma Brunskill
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #183
Invariance of Weight Distributions in Rectified MLPs
Susumu Tsuchida · Fred Roosta · Marcus Gallagher
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #184
Stronger Generalization Bounds for Deep Nets via a Compression Approach
Sanjeev Arora · Rong Ge · Behnam Neyshabur · Yi Zhang
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #185
Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices
Zengfeng Huang
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #186
Loss Decomposition for Fast Learning in Large Output Spaces
En-Hsu Yen · Satyen Kale · Felix Xinnan Yu · Daniel Holtmann-Rice · Sanjiv Kumar · Pradeep Ravikumar
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #187
Stochastic Proximal Algorithms for AUC Maximization
Michael Natole Jr · Yiming Ying · Siwei Lyu
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #188
Accelerated Spectral Ranking
Arpit Agarwal · Prathamesh Patil · Shivani Agarwal
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #189
Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning
Stefan Depeweg · Jose Hernandez-Lobato · Finale Doshi-Velez · Steffen Udluft
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #190
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Mohammad Emtiyaz Khan · Didrik Nielsen · Voot Tangkaratt · Wu Lin · Yarin Gal · Akash Srivastava
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #191
Learning One Convolutional Layer with Overlapping Patches
Surbhi Goel · Adam Klivans · Raghu Meka
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #192
A Spline Theory of Deep Learning
Randall Balestriero · Richard Baraniuk
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #193
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors
Soumya Ghosh · Jiayu Yao · Finale Doshi-Velez
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #194
Variational Bayesian dropout: pitfalls and fixes
Jiri Hron · Alexander Matthews · Zoubin Ghahramani
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #195
Adversarial Learning with Local Coordinate Coding
Jiezhang Cao · Yong Guo · Qingyao Wu · Chunhua Shen · Junzhou Huang · Mingkui Tan
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #196
Learning Representations and Generative Models for 3D Point Clouds
Panagiotis Achlioptas · Olga Diamanti · Ioannis Mitliagkas · Leonidas Guibas
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #197
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks
Mattias Teye · Hossein Azizpour · Kevin Smith
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #198
Noisy Natural Gradient as Variational Inference
Guodong Zhang · Shengyang Sun · David Duvenaud · Roger Grosse
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #199
Deep Variational Reinforcement Learning for POMDPs
Maximilian Igl · Luisa Zintgraf · Tuan Anh Le · Frank Wood · Shimon Whiteson
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #200
Recurrent Predictive State Policy Networks
Ahmed Hefny · Zita Marinho · Wen Sun · Siddhartha Srinivasa · Geoff Gordon
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #201
The Mechanics of n-Player Differentiable Games
David Balduzzi · Sebastien Racaniere · James Martens · Jakob Foerster · Karl Tuyls · Thore Graepel
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #202
Improved Training of Generative Adversarial Networks Using Representative Features
Duhyeon Bang · Hyunjung Shim
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #203
Hierarchical Multi-Label Classification Networks
Jonatas Wehrmann · Ricardo Cerri · Rodrigo Barros
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #204
Knowledge Transfer with Jacobian Matching
Suraj Srinivas · Francois Fleuret
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #205
Towards Black-box Iterative Machine Teaching
Weiyang Liu · Bo Dai · Xingguo Li · Zhen Liu · James Rehg · Le Song
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #206
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising
Borja de Balle Pigem · Yu-Xiang Wang
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #207
Importance Weighted Transfer of Samples in Reinforcement Learning
Andrea Tirinzoni · Andrea Sessa · Matteo Pirotta · Marcello Restelli
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #208
Beyond the One-Step Greedy Approach in Reinforcement Learning
Yonathan Efroni · Gal Dalal · Bruno Scherrer · Shie Mannor
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #209
Optimization, fast and slow: optimally switching between local and Bayesian optimization
Mark McLeod · Stephen Roberts · Michael A Osborne
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #210
Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design
Wenlong Lyu · Fan Yang · Changhao Yan · Dian Zhou · Xuan Zeng
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #211
Graphical Nonconvex Optimization via an Adaptive Convex Relaxation
Qiang Sun · Kean Ming Tan · Han Liu · Tong Zhang
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #212
Approximate message passing for amplitude based optimization
Junjie Ma · Ji Xu · Arian Maleki
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #214
Tempered Adversarial Networks
Mehdi S. M. Sajjadi · Giambattista Parascandolo · Arash Mehrjou · Bernhard Schölkopf
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #213
Delayed Impact of Fair Machine Learning
Lydia T. Liu · Sarah Dean · Esther Rolf · Max Simchowitz · University of California Moritz Hardt
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #215
Fast Information-theoretic Bayesian Optimisation
Binxin Ru · Michael A Osborne · Mark Mcleod · Diego Granziol
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #216
Tight Regret Bounds for Bayesian Optimization in One Dimension
Jonathan Scarlett
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #217
Image Transformer
Niki Parmar · Ashish Vaswani · Jakob Uszkoreit · Lukasz M Kaiser · Noam Shazeer · Alexander Ku · Dustin Tran
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #218
Kernelized Synaptic Weight Matrices
Lorenz Müller · Julien Martel · Giacomo Indiveri
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #219
A Distributed Second-Order Algorithm You Can Trust
Celestine Dünner · Aurelien Lucchi · Matilde Gargiani · An Bian · Thomas Hofmann · Martin Jaggi
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #220
On Acceleration with Noise-Corrupted Gradients
Michael Cohen · Jelena Diakonikolas · Orecchia Lorenzo
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #221
Gradient Coding from Cyclic MDS Codes and Expander Graphs
Netanel Raviv · Rashish Tandon · Alexandros Dimakis · Itzhak Tamo
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #222
Accelerating Greedy Coordinate Descent Methods
Haihao Lu · Robert Freund · Vahab Mirrokni
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #223
Finding Influential Training Samples for Gradient Boosted Decision Trees
Boris Sharchilev · Yury Ustinovskiy · Pavel Serdyukov · Maarten de Rijke
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #224
Improving Regression Performance with Distributional Losses
Ehsan Imani · Martha White
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #225
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
Tabish Rashid · Mikayel Samvelyan · Christian Schroeder · Gregory Farquhar · Jakob Foerster · Shimon Whiteson
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #226
Learning to Act in Decentralized Partially Observable MDPs
Jilles Dibangoye · Olivier Buffet
Poster
Thu Jul 12th 06:15 -- 09:00 PM @ Hall B #227
Local Convergence Properties of SAGA/Prox-SVRG and Acceleration
Clarice Poon · Jingwei Liang · Carola-Bibiane Schönlieb