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Session
Fri Jul 13 12:00 AM -- 12:20 AM (PDT) @ A1
Test of Time Award
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ A1
RLlib: Abstractions for Distributed Reinforcement Learning
In Reinforcement Learning 14
Eric Liang · Richard Liaw · Robert Nishihara · Philipp Moritz · Roy Fox · Ken Goldberg · Joseph E Gonzalez · Michael Jordan · Ion Stoica
[ PDF] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ A3
Learning Registered Point Processes from Idiosyncratic Observations
In Time-Series Analysis 1
Hongteng Xu · Lawrence Carin · Hongyuan Zha
[ PDF] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ K1
Solving Partial Assignment Problems using Random Clique Complexes
In Computer Vision 2
Charu Sharma · Deepak Nathani · Manu Kaul
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ Victoria
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
In Other Models and Methods 2
Been Kim · Martin Wattenberg · Justin Gilmer · Carrie Cai · James Wexler · Fernanda Viégas · Rory sayres
[ PDF] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ A9
Convergence guarantees for a class of non-convex and non-smooth optimization problems
In Optimization (Non-convex) 5
Koulik Khamaru · Martin Wainwright
[ PDF] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ A6
A Reductions Approach to Fair Classification
In Society Impacts of Machine Learning 2
Alekh Agarwal · Alina Beygelzimer · Miroslav Dudik · John Langford · Hanna Wallach
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ A5
Dynamic Regret of Strongly Adaptive Methods
In Online Learning 4
Lijun Zhang · Tianbao Yang · rong jin · Zhi-Hua Zhou
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ A7
Mixed batches and symmetric discriminators for GAN training
In Deep Learning (Adversarial) 6
Thomas LUCAS · Corentin Tallec · Yann Ollivier · Jakob Verbeek
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ K11
Out-of-sample extension of graph adjacency spectral embedding
In Dimensionality Reduction 3
Keith Levin · Fred Roosta · Michael Mahoney · Carey Priebe
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:30 AM -- 12:50 AM (PDT) @ A4
Learning in Integer Latent Variable Models with Nested Automatic Differentiation
In Graphical Models 2
Daniel Sheldon · Kevin Winner · Debora Sujono
[ PDF] 
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (PDT) @ A4
Sound Abstraction and Decomposition of Probabilistic Programs
In Graphical Models 2
Steven Holtzen · Guy Van den Broeck · Todd Millstein
[ PDF] 
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (PDT) @ K11
Bayesian Model Selection for Change Point Detection and Clustering
In Dimensionality Reduction 3
othmane mazhar · Cristian R. Rojas · Inst. of Technology Carlo Fischione · Mohammad Reza Hesamzadeh
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:50 AM -- 01:10 AM (PDT) @ A1
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
In Reinforcement Learning 14
Lasse Espeholt · Hubert Soyer · Remi Munos · Karen Simonyan · Vlad Mnih · Tom Ward · Yotam Doron · Vlad Firoiu · Tim Harley · Iain Dunning · Shane Legg · Koray Kavukcuoglu
[ PDF] 
Oral
Fri Jul 13 12:50 AM -- 01:10 AM (PDT) @ A9
A Progressive Batching L-BFGS Method for Machine Learning
In Optimization (Non-convex) 5
Vijaya Raghavendra Bollapragada · Jorge Nocedal · Dheevatsa Mudigere · Hao-Jun M Shi · Peter Tang
[ PDF] 
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (PDT) @ Victoria
Learning equations for extrapolation and control
In Other Models and Methods 2
Subham S Sahoo · Christoph H. Lampert · Georg Martius
[ PDF] 
Oral
Fri Jul 13 12:50 AM -- 01:10 AM (PDT) @ A3
Deep Bayesian Nonparametric Tracking
In Time-Series Analysis 1
Aonan Zhang · John Paisley
[ PDF] 
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (PDT) @ K1
Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction
In Computer Vision 2
Siyuan Qi · Baoxiong Jia · Song-Chun Zhu
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (PDT) @ A7
Mutual Information Neural Estimation
In Deep Learning (Adversarial) 6
Mohamed Belghazi · Aristide Baratin · Sai Rajeswar · Sherjil Ozair · Yoshua Bengio · R Devon Hjelm · Aaron Courville
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (PDT) @ A5
Online Learning with Abstention
In Online Learning 4
Corinna Cortes · Giulia DeSalvo · Claudio Gentile · Mehryar Mohri · Scott Yang
[ PDF]  [ Video] 
Oral
Fri Jul 13 12:50 AM -- 01:10 AM (PDT) @ A6
Probably Approximately Metric-Fair Learning
In Society Impacts of Machine Learning 2
Gal Yona · Guy Rothblum
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:00 AM -- 01:10 AM (PDT) @ A4
Parallel Bayesian Network Structure Learning
In Graphical Models 2
Tian Gao · Dennis Wei
[ PDF] 
Oral
Fri Jul 13 01:00 AM -- 01:10 AM (PDT) @ A5
Multi-Fidelity Black-Box Optimization with Hierarchical Partitions
In Online Learning 4
Rajat Sen · kirthevasan kandasamy · Sanjay Shakkottai
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:00 AM -- 01:10 AM (PDT) @ K1
Video Prediction with Appearance and Motion Conditions
In Computer Vision 2
Yunseok Jang · Gunhee Kim · Yale Song
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:00 AM -- 01:10 AM (PDT) @ A7
Adversarially Regularized Autoencoders
In Deep Learning (Adversarial) 6
Jake Zhao · Yoon Kim · Kelly Zhang · Alexander Rush · Yann LeCun
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:00 AM -- 01:10 AM (PDT) @ K11
An Iterative, Sketching-based Framework for Ridge Regression
In Dimensionality Reduction 3
Agniva Chowdhury · Jiasen Yang · Petros Drineas
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:00 AM -- 01:10 AM (PDT) @ Victoria
PDE-Net: Learning PDEs from Data
In Other Models and Methods 2
Zichao Long · Yiping Lu · Xianzhong Ma · Bin Dong
[ PDF] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ K1
Neural Program Synthesis from Diverse Demonstration Videos
In Computer Vision 2
Shao-Hua Sun · Hyeonwoo Noh · Sriram Somasundaram · Joseph Lim
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ A9
Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solution for Nonconvex Distributed Optimization Over Networks
In Optimization (Non-convex) 5
Mingyi Hong · Meisam Razaviyayn · Jason Lee
[ PDF] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ Victoria
Transformation Autoregressive Networks
In Other Models and Methods 2
Junier Oliva · Kumar Avinava Dubey · Manzil Zaheer · Barnabás Póczos · Ruslan Salakhutdinov · Eric Xing · Jeff Schneider
[ PDF] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ A3
Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling
In Time-Series Analysis 1
Kejun Huang · Xiao Fu · Nicholas Sidiropoulos
[ PDF] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ A4
The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference
In Graphical Models 2
Hao Lu · Yuan Cao · Junwei Lu · Han Liu · Zhaoran Wang
[ PDF] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ A1
Mix & Match - Agent Curricula for Reinforcement Learning
In Reinforcement Learning 14
Wojciech Czarnecki · Siddhant Jayakumar · Max Jaderberg · Leonard Hasenclever · Yee Teh · Nicolas Heess · Simon Osindero · Razvan Pascanu
[ PDF] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ K11
Provable Variable Selection for Streaming Features
In Dimensionality Reduction 3
Jing Wang · Jie Shen · Ping Li
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ A5
Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits
In Online Learning 4
Huasen Wu · Xueying Guo · Xin Liu
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ A7
JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets
In Deep Learning (Adversarial) 6
Yunchen Pu · Shuyang Dai · Zhe Gan · Weiyao Wang · Guoyin Wang · Yizhe Zhang · Ricardo Henao · Lawrence Carin
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:10 AM -- 01:20 AM (PDT) @ A6
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
In Society Impacts of Machine Learning 2
Michael Kearns · Seth Neel · Aaron Roth · Steven Wu
[ PDF] 
Oral
Fri Jul 13 01:20 AM -- 01:30 AM (PDT) @ A6
Blind Justice: Fairness with Encrypted Sensitive Attributes
In Society Impacts of Machine Learning 2
Niki Kilbertus · Adria Gascon · Matt Kusner · Michael Veale · Krishna Gummadi · Adrian Weller
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:20 AM -- 01:30 AM (PDT) @ A7
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data
In Deep Learning (Adversarial) 6
Amjad Almahairi · Sai Rajeswar · Alessandro Sordoni · Philip Bachman · Aaron Courville
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:20 AM -- 01:30 AM (PDT) @ A1
Learning to Explore via Meta-Policy Gradient
In Reinforcement Learning 14
Tianbing Xu · Qiang Liu · Liang Zhao · Jian Peng
[ PDF] 
Oral
Fri Jul 13 01:20 AM -- 01:30 AM (PDT) @ Victoria
Weightless: Lossy weight encoding for deep neural network compression
In Other Models and Methods 2
Brandon Reagen · Udit Gupta · Bob Adolf · Michael Mitzenmacher · Alexander Rush · Gu-Yeon Wei · David Brooks
[ PDF] 
Oral
Fri Jul 13 01:20 AM -- 01:30 AM (PDT) @ A5
Firing Bandits: Optimizing Crowdfunding
In Online Learning 4
Lalit Jain · Kevin Jamieson
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:20 AM -- 01:30 AM (PDT) @ A4
Temporal Poisson Square Root Graphical Models
In Graphical Models 2
Sinong Geng · Zhaobin Kuang · Peggy Peissig · University of Wisconsin David Page
[ PDF] 
Oral
Fri Jul 13 01:20 AM -- 01:30 AM (PDT) @ K11
Learning Low-Dimensional Temporal Representations
In Dimensionality Reduction 3
Bing Su · Ying Wu
[ PDF]  [ Video] 
Oral
Fri Jul 13 01:20 AM -- 01:30 AM (PDT) @ A9
Estimation of Markov Chain via Rank-constrained Likelihood
In Optimization (Non-convex) 5
XUDONG LI · Mengdi Wang · Anru Zhang
[ PDF] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ K1
Spurious Local Minima are Common in Two-Layer ReLU Neural Networks
In Deep Learning (Theory) 6
Itay Safran · Ohad Shamir
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ A5
Online Linear Quadratic Control
In Online Learning 5
Alon Cohen · Avinatan Hasidim · Tomer Koren · Nevena Lazic · Yishay Mansour · Kunal Talwar
[ PDF] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ A3
Learning Adversarially Fair and Transferable Representations
In Transfer and Multi-Task Learning 3
David Madras · Elliot Creager · Toniann Pitassi · Richard Zemel
[ PDF] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ A6
Theoretical Analysis of Sparse Subspace Clustering with Missing Entries
In Unsupervised Learning 2
Manolis Tsakiris · Rene Vidal
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ A7
Junction Tree Variational Autoencoder for Molecular Graph Generation
In Generative Models 3
Wengong Jin · Regina Barzilay · Tommi Jaakkola
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ K11
Competitive Caching with Machine Learned Advice
In Optimization (Combinatorial) 4
Thodoris Lykouris · Sergei Vassilvitskii
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ A4
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)
In Gaussian Processes 3
Trefor Evans · Prasanth B Nair
[ PDF] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ A1
Hierarchical Imitation and Reinforcement Learning
In Reinforcement Learning 15
Hoang Le · Nan Jiang · Alekh Agarwal · Miroslav Dudik · Yisong Yue · Hal Daumé III
[ PDF] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ Victoria
Efficient Neural Audio Synthesis
In Deep Learning (Neural Network Architectures) 11
Nal Kalchbrenner · Erich Elsen · Karen Simonyan · Seb Noury · Norman Casagrande · Edward Lockhart · Florian Stimberg · Aäron van den Oord · Sander Dieleman · Koray Kavukcuoglu
[ PDF] 
Oral
Fri Jul 13 02:00 AM -- 02:20 AM (PDT) @ A9
A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming
In Optimization (Convex) 5
Alp Yurtsever · Olivier Fercoq · Francesco Locatello · Volkan Cevher
[ PDF] 
Oral
Fri Jul 13 02:20 AM -- 02:40 AM (PDT) @ A4
State Space Gaussian Processes with Non-Gaussian Likelihood
In Gaussian Processes 3
Hannes Nickisch · Arno Solin · Alexander Grigorevskiy
[ PDF] 
Oral
Fri Jul 13 02:20 AM -- 02:30 AM (PDT) @ K11
Distributed Clustering via LSH Based Data Partitioning
In Optimization (Combinatorial) 4
Aditya Bhaskara · Pruthuvi Maheshakya Wijewardena
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:20 AM -- 02:30 AM (PDT) @ A3
Learning Semantic Representations for Unsupervised Domain Adaptation
In Transfer and Multi-Task Learning 3
Shaoan Xie · Zibin Zheng · Liang Chen · Chuan Chen
[ PDF] 
Oral
Fri Jul 13 02:20 AM -- 02:40 AM (PDT) @ K1
Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks
In Deep Learning (Theory) 6
Peter Bartlett · Dave Helmbold · Phil Long
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:20 AM -- 02:40 AM (PDT) @ Victoria
Understanding and Simplifying One-Shot Architecture Search
In Deep Learning (Neural Network Architectures) 11
Gabriel Bender · Pieter-Jan Kindermans · Barret Zoph · Vijay Vasudevan · Quoc Le
[ PDF] 
Oral
Fri Jul 13 02:20 AM -- 02:40 AM (PDT) @ A9
Frank-Wolfe with Subsampling Oracle
In Optimization (Convex) 5
Thomas Kerdreux · Fabian Pedregosa · Alexandre d'Aspremont
[ PDF] 
Oral
Fri Jul 13 02:20 AM -- 02:40 AM (PDT) @ A1
Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning
In Reinforcement Learning 15
Rodrigo A Toro Icarte · Toryn Q Klassen · Richard Valenzano · Sheila McIlraith
[ PDF] 
Oral
Fri Jul 13 02:20 AM -- 02:40 AM (PDT) @ A7
Semi-Amortized Variational Autoencoders
In Generative Models 3
Yoon Kim · Sam Wiseman · Andrew Miller · David Sontag · Alexander Rush
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:20 AM -- 02:40 AM (PDT) @ A5
Semiparametric Contextual Bandits
In Online Learning 5
Akshay Krishnamurthy · Steven Wu · Vasilis Syrgkanis
[ PDF] 
Oral
Fri Jul 13 02:20 AM -- 02:30 AM (PDT) @ A6
Improved nearest neighbor search using auxiliary information and priority functions
In Unsupervised Learning 2
Omid Keivani · Kaushik Sinha
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:30 AM -- 02:40 AM (PDT) @ A6
QuantTree: Histograms for Change Detection in Multivariate Data Streams
In Unsupervised Learning 2
Giacomo Boracchi · Diego Carrera · Cristiano Cervellera · Danilo Macciò
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:30 AM -- 02:40 AM (PDT) @ K11
Learning to Branch
In Optimization (Combinatorial) 4
Nina Balcan · Travis Dick · Tuomas Sandholm · Ellen Vitercik
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:30 AM -- 02:40 AM (PDT) @ A3
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
In Transfer and Multi-Task Learning 3
Judy Hoffman · Eric Tzeng · Taesung Park · Jun-Yan Zhu · Philip Isola · Kate Saenko · Alexei Efros · Trevor Darrell
[ PDF] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ A5
Minimax Concave Penalized Multi-Armed Bandit Model with High-Dimensional Covariates
In Online Learning 5
xue wang · Mingcheng Wei · Tao Yao
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ A4
Constant-Time Predictive Distributions for Gaussian Processes
In Gaussian Processes 3
Geoff Pleiss · Jacob Gardner · Kilian Weinberger · Andrew Wilson
[ PDF] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ K1
On the Power of Over-parametrization in Neural Networks with Quadratic Activation
In Deep Learning (Theory) 6
Simon Du · Jason Lee
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ A1
State Abstractions for Lifelong Reinforcement Learning
In Reinforcement Learning 15
David Abel · Dilip S. Arumugam · Lucas Lehnert · Michael L. Littman
[ PDF] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ A6
Topological mixture estimation
In Unsupervised Learning 2
Steve Huntsman
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ A9
On Matching Pursuit and Coordinate Descent
In Optimization (Convex) 5
Francesco Locatello · Anant Raj · Sai Praneeth Reddy Karimireddy · Gunnar Ratsch · Bernhard Schölkopf · Sebastian Stich · Martin Jaggi
[ PDF] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ A3
Rectify Heterogeneous Models with Semantic Mapping
In Transfer and Multi-Task Learning 3
Han-Jia Ye · De-Chuan Zhan · Yuan Jiang · Zhi-Hua Zhou
[ PDF]  [ PDF] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ K11
Compiling Combinatorial Prediction Games
In Optimization (Combinatorial) 4
Frederic Koriche
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ Victoria
Path-Level Network Transformation for Efficient Architecture Search
In Deep Learning (Neural Network Architectures) 11
Han Cai · Jiacheng Yang · Weinan Zhang · Song Han · Yong Yu
[ PDF] 
Oral
Fri Jul 13 02:40 AM -- 02:50 AM (PDT) @ A7
Iterative Amortized Inference
In Generative Models 3
Joe Marino · Yisong Yue · Stephan Mandt
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ A3
Detecting and Correcting for Label Shift with Black Box Predictors
In Transfer and Multi-Task Learning 3
Zachary Lipton · Yu-Xiang Wang · Alexander Smola
[ PDF] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ A9
Adaptive Three Operator Splitting
In Optimization (Convex) 5
Fabian Pedregosa · Gauthier Gidel
[ PDF] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ K1
Optimization Landscape and Expressivity of Deep CNNs
In Deep Learning (Theory) 6
Quynh Nguyen · Matthias Hein
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ A7
DVAE++: Discrete Variational Autoencoders with Overlapping Transformations
In Generative Models 3
Arash Vahdat · William Macready · Zhengbing Bian · Amir Khoshaman · Evgeny Andriyash
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ A6
Revealing Common Statistical Behaviors in Heterogeneous Populations
In Unsupervised Learning 2
Andrey Zhitnikov · Rotem Mulayoff · Tomer Michaeli
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ Victoria
Learning Longer-term Dependencies in RNNs with Auxiliary Losses
In Deep Learning (Neural Network Architectures) 11
Trieu H Trinh · Andrew Dai · Thang Luong · Quoc Le
[ PDF] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ A4
Large-Scale Cox Process Inference using Variational Fourier Features
In Gaussian Processes 3
ST John · James Hensman
[ PDF] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ K11
Approximation Algorithms for Cascading Prediction Models
In Optimization (Combinatorial) 4
Matthew Streeter
[ PDF]  [ Video] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ A1
Policy Optimization with Demonstrations
In Reinforcement Learning 15
Bingyi Kang · Zequn Jie · Jiashi Feng
[ PDF] 
Oral
Fri Jul 13 02:50 AM -- 03:00 AM (PDT) @ A5
Racing Thompson: an Efficient Algorithm for Thompson Sampling with Non-conjugate Priors
In Online Learning 5
Yichi Zhou · Jun Zhu · Jingwei Zhuo
[ PDF] 
Invited Talk
Fri Jul 13 04:30 AM -- 05:30 AM (PDT) @ A1
Language to Action: towards Interactive Task Learning with Physical Agents
Joyce Chai
Workshop
Fri Jul 13 05:00 AM -- 09:00 AM (PDT) @ K22
Learning and Reasoning: Principles & Applications to Everyday Spatial and Temporal Knowledge (day 1)
Invited Talk
Fri Jul 13 05:30 AM -- 06:30 AM (PDT) @ A1
Building Machines that Learn and Think Like People
Josh Tenenbaum
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ A4
Stein Variational Gradient Descent Without Gradient
In Monte Carlo Methods 2
Jun Han · Qiang Liu
[ PDF] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ Victoria
Progress & Compress: A scalable framework for continual learning
In Deep Learning (Neural Network Architectures) 12
Jonathan Schwarz · Wojciech Czarnecki · Jelena Luketina · Agnieszka Grabska-Barwinska · Yee Teh · Razvan Pascanu · Raia Hadsell
[ PDF] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ A3
The Hidden Vulnerability of Distributed Learning in Byzantium
In Parallel and Distributed Learning 3
El Mahdi El Mhamdi · Rachid Guerraoui · Sébastien Rouault
[ PDF] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ A9
SADAGRAD: Strongly Adaptive Stochastic Gradient Methods
In Optimization (Convex) 6
Zaiyi Chen · Yi Xu · Enhong Chen · Tianbao Yang
[ PDF] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ A7
Parallel WaveNet: Fast High-Fidelity Speech Synthesis
In Generative Models 4
Aäron van den Oord · Yazhe Li · Igor Babuschkin · Karen Simonyan · Oriol Vinyals · Koray Kavukcuoglu · George van den Driessche · Edward Lockhart · Luis C Cobo · Florian Stimberg · Norman Casagrande · Dominik Grewe · Seb Noury · Sander Dieleman · Erich Elsen · Nal Kalchbrenner · Heiga Zen · Alex Graves · Helen King · Tom Walters · Dan Belov · Demis Hassabis
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ A6
Candidates vs. Noises Estimation for Large Multi-Class Classification Problem
In Supervised Learning 3
Lei Han · Yiheng Huang · Tong Zhang
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ K11
On the Spectrum of Random Features Maps of High Dimensional Data
In Spectral Methods 1
Zhenyu Liao · Romain Couillet
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ A5
Causal Bandits with Propagating Inference
In Causal Inference 1
Akihiro Yabe · Daisuke Hatano · Hanna Sumita · Shinji Ito · Naonori Kakimura · Takuro Fukunaga · Ken-ichi Kawarabayashi
[ PDF] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ K1
Efficient end-to-end learning for quantizable representations
In Deep Learning (Theory) 7
Yeonwoo Jeong · Hyun Oh Song
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:00 AM -- 07:20 AM (PDT) @ A1
Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator
In Reinforcement Learning 16
Maryam Fazel · Rong Ge · Sham Kakade · Mehran Mesbahi
[ PDF] 
Oral
Fri Jul 13 07:20 AM -- 07:40 AM (PDT) @ A4
Minibatch Gibbs Sampling on Large Graphical Models
In Monte Carlo Methods 2
Christopher De Sa · Vincent Chen · Wong
[ PDF]  [ PDF] 
Oral
Fri Jul 13 07:20 AM -- 07:40 AM (PDT) @ A7
Autoregressive Quantile Networks for Generative Modeling
In Generative Models 4
Georg Ostrovski · Will Dabney · Remi Munos
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:20 AM -- 07:40 AM (PDT) @ A5
Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions
In Causal Inference 1
Karren Yang · Abigail Katoff · Caroline Uhler
[ PDF] 
Oral
Fri Jul 13 07:20 AM -- 07:30 AM (PDT) @ A9
Level-Set Methods for Finite-Sum Constrained Convex Optimization
In Optimization (Convex) 6
Qihang Lin · Runchao Ma · Tianbao Yang
[ PDF] 
Oral
Fri Jul 13 07:20 AM -- 07:40 AM (PDT) @ A3
Asynchronous Byzantine Machine Learning (the case of SGD)
In Parallel and Distributed Learning 3
Georgios Damaskinos · El Mahdi El Mhamdi · Rachid Guerraoui · Rhicheek Patra · Mahsa Taziki
[ PDF] 
Oral
Fri Jul 13 07:20 AM -- 07:30 AM (PDT) @ K1
High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach
In Deep Learning (Theory) 7
Tim Pearce · Alexandra Brintrup · Mohamed Zaki · Andy Neely
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:20 AM -- 07:40 AM (PDT) @ Victoria
Overcoming Catastrophic Forgetting with Hard Attention to the Task
In Deep Learning (Neural Network Architectures) 12
Joan Serrà · Didac Suris · Marius Miron · Alexandros Karatzoglou
[ PDF] 
Oral
Fri Jul 13 07:20 AM -- 07:30 AM (PDT) @ K11
SMAC: Simultaneous Mapping and Clustering Using Spectral Decompositions
In Spectral Methods 1
chandrajit bajaj · Tingran Gao · Zihang He · Qixing Huang · Zhenxiao Liang
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:20 AM -- 07:30 AM (PDT) @ A1
Policy Optimization as Wasserstein Gradient Flows
In Reinforcement Learning 16
RUIYI (ROY) ZHANG · Changyou Chen · Chunyuan Li · Lawrence Carin
[ PDF] 
Oral
Fri Jul 13 07:20 AM -- 07:30 AM (PDT) @ A6
CRAFTML, an Efficient Clustering-based Random Forest for Extreme Multi-label Learning
In Supervised Learning 3
Wissam Siblini · Frank Meyer · Pascale Kuntz
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:30 AM -- 07:40 AM (PDT) @ K1
A Boo(n) for Evaluating Architecture Performance
In Deep Learning (Theory) 7
Ondrej Bajgar · Rudolf Kadlec · Jan Kleindienst
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:30 AM -- 07:40 AM (PDT) @ A6
Attention-based Deep Multiple Instance Learning
In Supervised Learning 3
Maximilian Ilse · Jakub Tomczak · Max Welling
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:30 AM -- 07:40 AM (PDT) @ K11
Spectrally Approximating Large Graphs with Smaller Graphs
In Spectral Methods 1
Andreas Loukas · Pierre Vandergheynst
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:30 AM -- 07:40 AM (PDT) @ A1
Clipped Action Policy Gradient
In Reinforcement Learning 16
Yasuhiro Fujita · Shin-ichi Maeda
[ PDF] 
Oral
Fri Jul 13 07:30 AM -- 07:40 AM (PDT) @ A9
Local Convergence Properties of SAGA/Prox-SVRG and Acceleration
In Optimization (Convex) 6
Clarice Poon · Jingwei Liang · Carola-Bibiane Schönlieb
[ PDF] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ A3
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients
In Parallel and Distributed Learning 3
Lingjiao Chen · Hongyi Wang · Zachary Charles · Dimitris Papailiopoulos
[ PDF] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ A9
Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions
In Optimization (Convex) 6
Pan Xu · Tianhao Wang · Quanquan Gu
[ PDF] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ A1
Fourier Policy Gradients
In Reinforcement Learning 16
Matthew Fellows · Kamil Ciosek · Shimon Whiteson
[ PDF] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ A5
Budgeted Experiment Design for Causal Structure Learning
In Causal Inference 1
AmirEmad Ghassami · Saber Salehkaleybar · Negar Kiyavash · Elias Bareinboim
[ PDF] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ K1
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors
In Deep Learning (Theory) 7
Gintare Karolina Dziugaite · Daniel Roy
[ PDF] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ K11
Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering
In Spectral Methods 1
Pan Li · Olgica Milenkovic
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ A4
On Nesting Monte Carlo Estimators
In Monte Carlo Methods 2
Tom Rainforth · Rob Cornish · Hongseok Yang · andrew warrington · Frank Wood
[ PDF] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ Victoria
Rapid Adaptation with Conditionally Shifted Neurons
In Deep Learning (Neural Network Architectures) 12
Tsendsuren Munkhdalai · Xingdi Yuan · Soroush Mehri · Adam Trischler
[ PDF] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ A6
Learning and Memorization
In Supervised Learning 3
Sat Chatterjee
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:40 AM -- 07:50 AM (PDT) @ A7
Stochastic Video Generation with a Learned Prior
In Generative Models 4
Emily Denton · Rob Fergus
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ K11
Rates of Convergence of Spectral Methods for Graphon Estimation
In Spectral Methods 1
Jiaming Xu
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ Victoria
Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace
In Deep Learning (Neural Network Architectures) 12
Yoonho Lee · Seungjin Choi
[ PDF] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ A9
Fast Gradient-Based Methods with Exponential Rate: A Hybrid Control Framework
In Optimization (Convex) 6
Arman Sharifi Kolarijani · Peyman Mohajerin Esfahani · Tamas Keviczky
[ PDF] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ A6
Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings
In Supervised Learning 3
Aviral Kumar · Sunita Sarawagi · Ujjwal Jain
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ A5
The Hierarchical Adaptive Forgetting Variational Filter
In Causal Inference 1
Vincent Moens
[ PDF] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ A7
Disentangled Sequential Autoencoder
In Generative Models 4
Yingzhen Li · Stephan Mandt
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ A3
Communication-Computation Efficient Gradient Coding
In Parallel and Distributed Learning 3
Min Ye · Emmanuel Abbe
[ PDF] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ A4
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo
In Monte Carlo Methods 2
Niladri Chatterji · Nicolas Flammarion · Yian Ma · Peter Bartlett · Michael Jordan
[ PDF] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ K1
On the Limitations of First-Order Approximation in GAN Dynamics
In Deep Learning (Theory) 7
Jerry Li · Aleksander Madry · John Peebles · Ludwig Schmidt
[ PDF]  [ Video] 
Oral
Fri Jul 13 07:50 AM -- 08:00 AM (PDT) @ A1
Self-Imitation Learning
In Reinforcement Learning 16
Junhyuk Oh · Yijie Guo · Satinder Singh · Honglak Lee
[ PDF] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ Victoria
WSNet: Compact and Efficient Networks Through Weight Sampling
In Deep Learning (Neural Network Architectures) 13
Xiaojie Jin · Yingzhen Yang · Ning Xu · Jianchao Yang · Nebojsa Jojic · Jiashi Feng · Shuicheng Yan
[ PDF] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ A1
Mean Field Multi-Agent Reinforcement Learning
In Reinforcement Learning 17
Yaodong Yang · Rui Luo · Minne Li · Ming Zhou · Weinan Zhang · Jun Wang
[ PDF] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ K11
Convolutional Imputation of Matrix Networks
In Matrix Factorization 2
Qingyun Sun · Mengyuan Yan · David Donoho · stephen boyd
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ A7
Modeling Sparse Deviations for Compressed Sensing using Generative Models
In Generative Models 5
Manik Dhar · Aditya Grover · Stefano Ermon
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ A6
A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization
In Statistical Learning Theory 5
Robin Vogel · Aurélien Bellet · Stéphan Clémençon
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ A5
Orthogonal Machine Learning: Power and Limitations
In Causal Inference 2
Ilias Zadik · Lester Mackey · Vasilis Syrgkanis
[ PDF]  [ PDF] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ K1
On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups
In Deep Learning (Theory) 8
Risi Kondor · Shubhendu Trivedi
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ A9
Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis
In Optimization (Convex) 7
Pengtao Xie · Wei Wu · Yichen Zhu · Eric Xing
[ PDF] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ A3
Analyzing Uncertainty in Neural Machine Translation
In Natural Language and Speech Processing 2
Myle Ott · Michael Auli · David Grangier · Marc'Aurelio Ranzato
[ PDF] 
Oral
Fri Jul 13 08:00 AM -- 08:20 AM (PDT) @ A4
Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent
In Approximate Inference 3
Trevor Campbell · Tamara Broderick
[ PDF] 
Oral
Fri Jul 13 08:20 AM -- 08:30 AM (PDT) @ K11
Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow
In Matrix Factorization 2
Xiao Zhang · Simon Du · Quanquan Gu
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:20 AM -- 08:30 AM (PDT) @ A3
Generalization without Systematicity: On the Compositional Skills of Sequence-to-Sequence Recurrent Networks
In Natural Language and Speech Processing 2
Brenden Lake · Marco Baroni
[ PDF] 
Oral
Fri Jul 13 08:20 AM -- 08:30 AM (PDT) @ A9
Celer: a Fast Solver for the Lasso with Dual Extrapolation
In Optimization (Convex) 7
Mathurin MASSIAS · Joseph Salmon · Alexandre Gramfort
[ PDF] 
Oral
Fri Jul 13 08:20 AM -- 08:30 AM (PDT) @ K1
Bounding and Counting Linear Regions of Deep Neural Networks
In Deep Learning (Theory) 8
Thiago Serra · Christian Tjandraatmadja · Srikumar Ramalingam
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:20 AM -- 08:30 AM (PDT) @ A4
CRVI: Convex Relaxation for Variational Inference
In Approximate Inference 3
Ghazal Fazelnia · John Paisley
[ PDF] 
Oral
Fri Jul 13 08:20 AM -- 08:40 AM (PDT) @ Victoria
StrassenNets: Deep Learning with a Multiplication Budget
In Deep Learning (Neural Network Architectures) 13
Michael Tschannen · Aran Khanna · Animashree Anandkumar
[ PDF] 
Oral
Fri Jul 13 08:20 AM -- 08:40 AM (PDT) @ A1
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control
In Reinforcement Learning 17
Yangchen Pan · Amir-massoud Farahmand · Martha White · Saleh Nabi · Piyush Grover · Daniel Nikovski
[ PDF] 
Oral
Fri Jul 13 08:20 AM -- 08:40 AM (PDT) @ A5
Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models
In Causal Inference 2
Raj Agrawal · Caroline Uhler · Tamara Broderick
[ PDF] 
Oral
Fri Jul 13 08:20 AM -- 08:30 AM (PDT) @ A6
Classification from Pairwise Similarity and Unlabeled Data
In Statistical Learning Theory 5
Han Bao · Gang Niu · Masashi Sugiyama
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:20 AM -- 08:30 AM (PDT) @ A7
oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis
In Generative Models 5
Samuel Ainsworth · Nicholas J Foti · Adrian KC Lee · Emily Fox
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:30 AM -- 08:40 AM (PDT) @ K1
DCFNet: Deep Neural Network with Decomposed Convolutional Filters
In Deep Learning (Theory) 8
Qiang Qiu · Xiuyuan Cheng · robert Calderbank · Guillermo Sapiro
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:30 AM -- 08:40 AM (PDT) @ A6
Comparison-Based Random Forests
In Statistical Learning Theory 5
Siavash Haghiri · Damien Garreau · Ulrike von Luxburg
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:30 AM -- 08:40 AM (PDT) @ K11
On the Implicit Bias of Dropout
In Matrix Factorization 2
Poorya Mianjy · Raman Arora · Rene Vidal
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:30 AM -- 08:40 AM (PDT) @ A9
Cut-Pursuit Algorithm for Regularizing Nonsmooth Functionals with Graph Total Variation
In Optimization (Convex) 7
Hugo Raguet · loic landrieu
[ PDF] 
Oral
Fri Jul 13 08:30 AM -- 08:40 AM (PDT) @ A3
Adaptive Sampled Softmax with Kernel Based Sampling
In Natural Language and Speech Processing 2
Guy Blanc · Steffen Rendle
[ PDF] 
Oral
Fri Jul 13 08:30 AM -- 08:40 AM (PDT) @ A7
Noisin: Unbiased Regularization for Recurrent Neural Networks
In Generative Models 5
Adji Bousso Dieng · Rajesh Ranganath · Jaan Altosaar · David Blei
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:30 AM -- 08:40 AM (PDT) @ A4
Stein Points
In Approximate Inference 3
Wilson Ye Chen · Lester Mackey · Jackson Gorham · Francois-Xavier Briol · Chris J Oates
[ PDF] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ Victoria
Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions
In Deep Learning (Neural Network Architectures) 13
Junru Wu · Yue Wang · Zhenyu Wu · Zhangyang Wang · Ashok Veeraraghavan · Yingyan Lin
[ PDF] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ A9
Efficient First-Order Algorithms for Adaptive Signal Denoising
In Optimization (Convex) 7
Dmitrii Ostrovskii · Zaid Harchaoui
[ PDF] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ A5
Accurate Inference for Adaptive Linear Models
In Causal Inference 2
Yash Deshpande · Lester Mackey · Vasilis Syrgkanis · Matt Taddy
[ PDF] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ K1
A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations
In Deep Learning (Theory) 8
Weili Nie · Yang Zhang · Ankit Patel
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ A7
Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series
In Generative Models 5
Zhengping Che · Sanjay Purushotham · Max Guangyu Li · Bo Jiang · Yan Liu
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ A6
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples
In Statistical Learning Theory 5
Yizhen Wang · Somesh Jha · Kamalika Chaudhuri
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ A1
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents
In Reinforcement Learning 17
Kaiqing Zhang · Zhuoran Yang · Han Liu · Tong Zhang · Tamer Basar
[ PDF] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ A3
Hierarchical Text Generation and Planning for Strategic Dialogue
In Natural Language and Speech Processing 2
Denis Yarats · Mike Lewis
[ PDF] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ A4
Message Passing Stein Variational Gradient Descent
In Approximate Inference 3
Jingwei Zhuo · Chang Liu · Jiaxin Shi · Jun Zhu · Ning Chen · Bo Zhang
[ PDF] 
Oral
Fri Jul 13 08:40 AM -- 08:50 AM (PDT) @ K11
A Unified Framework for Structured Low-rank Matrix Learning
In Matrix Factorization 2
Pratik Kumar Jawanpuria · Bamdev Mishra
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:50 AM -- 09:00 AM (PDT) @ A5
Detecting non-causal artifacts in multivariate linear regression models
In Causal Inference 2
Dominik Janzing · Bernhard Schölkopf
[ PDF] 
Oral
Fri Jul 13 08:50 AM -- 09:00 AM (PDT) @ A9
An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method
In Optimization (Convex) 7
Li Shen · Peng Sun · Yitong Wang · Wei Liu · Tong Zhang
[ PDF] 
Oral
Fri Jul 13 08:50 AM -- 09:00 AM (PDT) @ A1
The Uncertainty Bellman Equation and Exploration
In Reinforcement Learning 17
Brendan O'Donoghue · Ian Osband · Remi Munos · Vlad Mnih
[ PDF] 
Oral
Fri Jul 13 08:50 AM -- 09:00 AM (PDT) @ Victoria
Born Again Neural Networks
In Deep Learning (Neural Network Architectures) 13
Tommaso Furlanello · Zachary Lipton · Michael Tschannen · Laurent Itti · Anima Anandkumar
[ PDF] 
Oral
Fri Jul 13 08:50 AM -- 09:00 AM (PDT) @ A7
Inter and Intra Topic Structure Learning with Word Embeddings
In Generative Models 5
He Zhao · Lan Du · Wray Buntine · Mingyuan Zhou
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:50 AM -- 09:00 AM (PDT) @ K11
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers
In Matrix Factorization 2
Yao Ma · Alex Olshevsky · Csaba Szepesvari · Venkatesh Saligrama
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:50 AM -- 09:00 AM (PDT) @ A6
Active Learning with Logged Data
In Statistical Learning Theory 5
Songbai Yan · Kamalika Chaudhuri · Tara Javidi
[ PDF]  [ Video] 
Oral
Fri Jul 13 08:50 AM -- 09:00 AM (PDT) @ A4
Pathwise Derivatives Beyond the Reparameterization Trick
In Approximate Inference 3
Martin Jankowiak · Fritz Obermeyer
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #1
Stein Points
In Posters Fri
Wilson Ye Chen · Lester Mackey · Jackson Gorham · Francois-Xavier Briol · Chris J Oates
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #2
Large-Scale Cox Process Inference using Variational Fourier Features
In Posters Fri
ST John · James Hensman
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #3
SADAGRAD: Strongly Adaptive Stochastic Gradient Methods
In Posters Fri
Zaiyi Chen · Yi Xu · Enhong Chen · Tianbao Yang
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #4
Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solution for Nonconvex Distributed Optimization Over Networks
In Posters Fri
Mingyi Hong · Meisam Razaviyayn · Jason Lee
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #5
A Progressive Batching L-BFGS Method for Machine Learning
In Posters Fri
Vijaya Raghavendra Bollapragada · Jorge Nocedal · Dheevatsa Mudigere · Hao-Jun M Shi · Peter Tang
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #6
WSNet: Compact and Efficient Networks Through Weight Sampling
In Posters Fri
Xiaojie Jin · Yingzhen Yang · Ning Xu · Jianchao Yang · Nebojsa Jojic · Jiashi Feng · Shuicheng Yan
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #7
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors
In Posters Fri
Gintare Karolina Dziugaite · Daniel Roy
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #8
High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach
In Posters Fri
Tim Pearce · Alexandra Brintrup · Mohamed Zaki · Andy Neely
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #9
Competitive Caching with Machine Learned Advice
In Posters Fri
Thodoris Lykouris · Sergei Vassilvitskii
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #10
Approximation Algorithms for Cascading Prediction Models
In Posters Fri
Matthew Streeter
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #11
Orthogonal Machine Learning: Power and Limitations
In Posters Fri
Ilias Zadik · Lester Mackey · Vasilis Syrgkanis
[ PDF]  [ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #12
Causal Bandits with Propagating Inference
In Posters Fri
Akihiro Yabe · Daisuke Hatano · Hanna Sumita · Shinji Ito · Naonori Kakimura · Takuro Fukunaga · Ken-ichi Kawarabayashi
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #13
Mix & Match - Agent Curricula for Reinforcement Learning
In Posters Fri
Wojciech Czarnecki · Siddhant Jayakumar · Max Jaderberg · Leonard Hasenclever · Yee Teh · Nicolas Heess · Simon Osindero · Razvan Pascanu
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #14
The Uncertainty Bellman Equation and Exploration
In Posters Fri
Brendan O'Donoghue · Ian Osband · Remi Munos · Vlad Mnih
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #15
Hierarchical Imitation and Reinforcement Learning
In Posters Fri
Hoang Le · Nan Jiang · Alekh Agarwal · Miroslav Dudik · Yisong Yue · Hal Daumé III
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #16
Policy Optimization with Demonstrations
In Posters Fri
Bingyi Kang · Zequn Jie · Jiashi Feng
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #17
Fast Gradient-Based Methods with Exponential Rate: A Hybrid Control Framework
In Posters Fri
Arman Sharifi Kolarijani · Peyman Mohajerin Esfahani · Tamas Keviczky
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #18
Level-Set Methods for Finite-Sum Constrained Convex Optimization
In Posters Fri
Qihang Lin · Runchao Ma · Tianbao Yang
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #19
A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations
In Posters Fri
Weili Nie · Yang Zhang · Ankit Patel
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #20
A Boo(n) for Evaluating Architecture Performance
In Posters Fri
Ondrej Bajgar · Rudolf Kadlec · Jan Kleindienst
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #21
RLlib: Abstractions for Distributed Reinforcement Learning
In Posters Fri
Eric Liang · Richard Liaw · Robert Nishihara · Philipp Moritz · Roy Fox · Ken Goldberg · Joseph E Gonzalez · Michael Jordan · Ion Stoica
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #22
Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator
In Posters Fri
Maryam Fazel · Rong Ge · Sham Kakade · Mehran Mesbahi
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #23
The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference
In Posters Fri
Hao Lu · Yuan Cao · Junwei Lu · Han Liu · Zhaoran Wang
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #24
Sound Abstraction and Decomposition of Probabilistic Programs
In Posters Fri
Steven Holtzen · Guy Van den Broeck · Todd Millstein
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #25
Parallel WaveNet: Fast High-Fidelity Speech Synthesis
In Posters Fri
Aäron van den Oord · Yazhe Li · Igor Babuschkin · Karen Simonyan · Oriol Vinyals · Koray Kavukcuoglu · George van den Driessche · Edward Lockhart · Luis C Cobo · Florian Stimberg · Norman Casagrande · Dominik Grewe · Seb Noury · Sander Dieleman · Erich Elsen · Nal Kalchbrenner · Heiga Zen · Alex Graves · Helen King · Tom Walters · Dan Belov · Demis Hassabis
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #26
Modeling Sparse Deviations for Compressed Sensing using Generative Models
In Posters Fri
Manik Dhar · Aditya Grover · Stefano Ermon
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #27
Revealing Common Statistical Behaviors in Heterogeneous Populations
In Posters Fri
Andrey Zhitnikov · Rotem Mulayoff · Tomer Michaeli
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #28
Improved nearest neighbor search using auxiliary information and priority functions
In Posters Fri
Omid Keivani · Kaushik Sinha
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #29
Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings
In Posters Fri
Aviral Kumar · Sunita Sarawagi · Ujjwal Jain
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #30
QuantTree: Histograms for Change Detection in Multivariate Data Streams
In Posters Fri
Giacomo Boracchi · Diego Carrera · Cristiano Cervellera · Danilo Macciò
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #31
An Iterative, Sketching-based Framework for Ridge Regression
In Posters Fri
Agniva Chowdhury · Jiasen Yang · Petros Drineas
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #32
Learning Low-Dimensional Temporal Representations
In Posters Fri
Bing Su · Ying Wu
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #33
Rapid Adaptation with Conditionally Shifted Neurons
In Posters Fri
Tsendsuren Munkhdalai · Xingdi Yuan · Soroush Mehri · Adam Trischler
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #34
PDE-Net: Learning PDEs from Data
In Posters Fri
Zichao Long · Yiping Lu · Xianzhong Ma · Bin Dong
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #35
Theoretical Analysis of Sparse Subspace Clustering with Missing Entries
In Posters Fri
Manolis Tsakiris · Rene Vidal
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #36
Topological mixture estimation
In Posters Fri
Steve Huntsman
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #37
On Matching Pursuit and Coordinate Descent
In Posters Fri
Francesco Locatello · Anant Raj · Sai Praneeth Reddy Karimireddy · Gunnar Ratsch · Bernhard Schölkopf · Sebastian Stich · Martin Jaggi
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #38
Frank-Wolfe with Subsampling Oracle
In Posters Fri
Thomas Kerdreux · Fabian Pedregosa · Alexandre d'Aspremont
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #39
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control
In Posters Fri
Yangchen Pan · Amir-massoud Farahmand · Martha White · Saleh Nabi · Piyush Grover · Daniel Nikovski
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #40
Fourier Policy Gradients
In Posters Fri
Matthew Fellows · Kamil Ciosek · Shimon Whiteson
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #41
Adaptive Three Operator Splitting
In Posters Fri
Fabian Pedregosa · Gauthier Gidel
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #42
A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming
In Posters Fri
Alp Yurtsever · Olivier Fercoq · Francesco Locatello · Volkan Cevher
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #43
Learning Semantic Representations for Unsupervised Domain Adaptation
In Posters Fri
Shaoan Xie · Zibin Zheng · Liang Chen · Chuan Chen
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #44
Learning Adversarially Fair and Transferable Representations
In Posters Fri
David Madras · Elliot Creager · Toniann Pitassi · Richard Zemel
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #45
Spurious Local Minima are Common in Two-Layer ReLU Neural Networks
In Posters Fri
Itay Safran · Ohad Shamir
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #46
Efficient end-to-end learning for quantizable representations
In Posters Fri
Yeonwoo Jeong · Hyun Oh Song
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #47
Solving Partial Assignment Problems using Random Clique Complexes
In Posters Fri
Charu Sharma · Deepak Nathani · Manu Kaul
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #48
Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction
In Posters Fri
Siyuan Qi · Baoxiong Jia · Song-Chun Zhu
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #49
Convergence guarantees for a class of non-convex and non-smooth optimization problems
In Posters Fri
Koulik Khamaru · Martin Wainwright
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #50
Estimation of Markov Chain via Rank-constrained Likelihood
In Posters Fri
XUDONG LI · Mengdi Wang · Anru Zhang
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #51
Efficient First-Order Algorithms for Adaptive Signal Denoising
In Posters Fri
Dmitrii Ostrovskii · Zaid Harchaoui
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #52
Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions
In Posters Fri
Pan Xu · Tianhao Wang · Quanquan Gu
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #53
Noisin: Unbiased Regularization for Recurrent Neural Networks
In Posters Fri
Adji Bousso Dieng · Rajesh Ranganath · Jaan Altosaar · David Blei
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #54
Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series
In Posters Fri
Zhengping Che · Sanjay Purushotham · Max Guangyu Li · Bo Jiang · Yan Liu
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #55
Disentangled Sequential Autoencoder
In Posters Fri
Yingzhen Li · Stephan Mandt
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #56
Stochastic Video Generation with a Learned Prior
In Posters Fri
Emily Denton · Rob Fergus
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #57
Mutual Information Neural Estimation
In Posters Fri
Mohamed Belghazi · Aristide Baratin · Sai Rajeswar · Sherjil Ozair · Yoshua Bengio · R Devon Hjelm · Aaron Courville
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #58
Adversarially Regularized Autoencoders
In Posters Fri
Jake Zhao · Yoon Kim · Kelly Zhang · Alexander Rush · Yann LeCun
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #59
Policy Optimization as Wasserstein Gradient Flows
In Posters Fri
RUIYI (ROY) ZHANG · Changyou Chen · Chunyuan Li · Lawrence Carin
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #60
Self-Imitation Learning
In Posters Fri
Junhyuk Oh · Yijie Guo · Satinder Singh · Honglak Lee
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #61
Spectrally Approximating Large Graphs with Smaller Graphs
In Posters Fri
Andreas Loukas · Pierre Vandergheynst
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #62
On the Spectrum of Random Features Maps of High Dimensional Data
In Posters Fri
Zhenyu Liao · Romain Couillet
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #63
Learning Registered Point Processes from Idiosyncratic Observations
In Posters Fri
Hongteng Xu · Lawrence Carin · Hongyuan Zha
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #64
Deep Bayesian Nonparametric Tracking
In Posters Fri
Aonan Zhang · John Paisley
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #65
Learning and Memorization
In Posters Fri
Sat Chatterjee
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #66
Attention-based Deep Multiple Instance Learning
In Posters Fri
Maximilian Ilse · Jakub Tomczak · Max Welling
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #67
Classification from Pairwise Similarity and Unlabeled Data
In Posters Fri
Han Bao · Gang Niu · Masashi Sugiyama
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #68
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples
In Posters Fri
Yizhen Wang · Somesh Jha · Kamalika Chaudhuri
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #69
On the Implicit Bias of Dropout
In Posters Fri
Poorya Mianjy · Raman Arora · Rene Vidal
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #70
Convolutional Imputation of Matrix Networks
In Posters Fri
Qingyun Sun · Mengyuan Yan · David Donoho · stephen boyd
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #71
Detecting and Correcting for Label Shift with Black Box Predictors
In Posters Fri
Zachary Lipton · Yu-Xiang Wang · Alexander Smola
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #72
Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis
In Posters Fri
Pengtao Xie · Wei Wu · Yichen Zhu · Eric Xing
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #73
Comparison-Based Random Forests
In Posters Fri
Siavash Haghiri · Damien Garreau · Ulrike von Luxburg
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #74
A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization
In Posters Fri
Robin Vogel · Aurélien Bellet · Stéphan Clémençon
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #75
Provable Variable Selection for Streaming Features
In Posters Fri
Jing Wang · Jie Shen · Ping Li
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #76
Out-of-sample extension of graph adjacency spectral embedding
In Posters Fri
Keith Levin · Fred Roosta · Michael Mahoney · Carey Priebe
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #77
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers
In Posters Fri
Yao Ma · Alex Olshevsky · Csaba Szepesvari · Venkatesh Saligrama
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #78
Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow
In Posters Fri
Xiao Zhang · Simon Du · Quanquan Gu
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #79
DCFNet: Deep Neural Network with Decomposed Convolutional Filters
In Posters Fri
Qiang Qiu · Xiuyuan Cheng · robert Calderbank · Guillermo Sapiro
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #80
Optimization Landscape and Expressivity of Deep CNNs
In Posters Fri
Quynh Nguyen · Matthias Hein
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #81
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)
In Posters Fri
Trefor Evans · Prasanth B Nair
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #82
Learning in Integer Latent Variable Models with Nested Automatic Differentiation
In Posters Fri
Daniel Sheldon · Kevin Winner · Debora Sujono
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #83
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
In Posters Fri
Judy Hoffman · Eric Tzeng · Taesung Park · Jun-Yan Zhu · Philip Isola · Kate Saenko · Alexei Efros · Trevor Darrell
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #84
Rectify Heterogeneous Models with Semantic Mapping
In Posters Fri
Han-Jia Ye · De-Chuan Zhan · Yuan Jiang · Zhi-Hua Zhou
[ PDF]  [ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #85
DVAE++: Discrete Variational Autoencoders with Overlapping Transformations
In Posters Fri
Arash Vahdat · William Macready · Zhengbing Bian · Amir Khoshaman · Evgeny Andriyash
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #86
Iterative Amortized Inference
In Posters Fri
Joe Marino · Yisong Yue · Stephan Mandt
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #87
Blind Justice: Fairness with Encrypted Sensitive Attributes
In Posters Fri
Niki Kilbertus · Adria Gascon · Matt Kusner · Michael Veale · Krishna Gummadi · Adrian Weller
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #88
Active Learning with Logged Data
In Posters Fri
Songbai Yan · Kamalika Chaudhuri · Tara Javidi
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #89
A Reductions Approach to Fair Classification
In Posters Fri
Alekh Agarwal · Alina Beygelzimer · Miroslav Dudik · John Langford · Hanna Wallach
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #90
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
In Posters Fri
Michael Kearns · Seth Neel · Aaron Roth · Steven Wu
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #91
Bayesian Model Selection for Change Point Detection and Clustering
In Posters Fri
othmane mazhar · Cristian R. Rojas · Inst. of Technology Carlo Fischione · Mohammad Reza Hesamzadeh
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #92
A Unified Framework for Structured Low-rank Matrix Learning
In Posters Fri
Pratik Kumar Jawanpuria · Bamdev Mishra
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #93
Firing Bandits: Optimizing Crowdfunding
In Posters Fri
Lalit Jain · Kevin Jamieson
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #94
Multi-Fidelity Black-Box Optimization with Hierarchical Partitions
In Posters Fri
Rajat Sen · kirthevasan kandasamy · Sanjay Shakkottai
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #95
Compiling Combinatorial Prediction Games
In Posters Fri
Frederic Koriche
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #96
Rates of Convergence of Spectral Methods for Graphon Estimation
In Posters Fri
Jiaming Xu
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #97
Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions
In Posters Fri
Karren Yang · Abigail Katoff · Caroline Uhler
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #98
Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models
In Posters Fri
Raj Agrawal · Caroline Uhler · Tamara Broderick
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #99
StrassenNets: Deep Learning with a Multiplication Budget
In Posters Fri
Michael Tschannen · Aran Khanna · Animashree Anandkumar
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #100
Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace
In Posters Fri
Yoonho Lee · Seungjin Choi
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #101
Candidates vs. Noises Estimation for Large Multi-Class Classification Problem
In Posters Fri
Lei Han · Yiheng Huang · Tong Zhang
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #102
CRAFTML, an Efficient Clustering-based Random Forest for Extreme Multi-label Learning
In Posters Fri
Wissam Siblini · Frank Meyer · Pascale Kuntz
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #103
Overcoming Catastrophic Forgetting with Hard Attention to the Task
In Posters Fri
Joan Serrà · Didac Suris · Marius Miron · Alexandros Karatzoglou
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #104
Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions
In Posters Fri
Junru Wu · Yue Wang · Zhenyu Wu · Zhangyang Wang · Ashok Veeraraghavan · Yingyan Lin
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #105
Efficient Neural Audio Synthesis
In Posters Fri
Nal Kalchbrenner · Erich Elsen · Karen Simonyan · Seb Noury · Norman Casagrande · Edward Lockhart · Florian Stimberg · Aäron van den Oord · Sander Dieleman · Koray Kavukcuoglu
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #106
Born Again Neural Networks
In Posters Fri
Tommaso Furlanello · Zachary Lipton · Michael Tschannen · Laurent Itti · Anima Anandkumar
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #107
Adaptive Sampled Softmax with Kernel Based Sampling
In Posters Fri
Guy Blanc · Steffen Rendle
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #109
JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets
In Posters Fri
Yunchen Pu · Shuyang Dai · Zhe Gan · Weiyao Wang · Guoyin Wang · Yizhe Zhang · Ricardo Henao · Lawrence Carin
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #110
Autoregressive Quantile Networks for Generative Modeling
In Posters Fri
Georg Ostrovski · Will Dabney · Remi Munos
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #111
On the Power of Over-parametrization in Neural Networks with Quadratic Activation
In Posters Fri
Simon Du · Jason Lee
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #112
On the Limitations of First-Order Approximation in GAN Dynamics
In Posters Fri
Jerry Li · Aleksander Madry · John Peebles · Ludwig Schmidt
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #113
Learning to Explore via Meta-Policy Gradient
In Posters Fri
Tianbing Xu · Qiang Liu · Liang Zhao · Jian Peng
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #114
Mean Field Multi-Agent Reinforcement Learning
In Posters Fri
Yaodong Yang · Rui Luo · Minne Li · Ming Zhou · Weinan Zhang · Jun Wang
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #115
Online Linear Quadratic Control
In Posters Fri
Alon Cohen · Avinatan Hasidim · Tomer Koren · Nevena Lazic · Yishay Mansour · Kunal Talwar
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #116
Online Learning with Abstention
In Posters Fri
Corinna Cortes · Giulia DeSalvo · Claudio Gentile · Mehryar Mohri · Scott Yang
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #117
Celer: a Fast Solver for the Lasso with Dual Extrapolation
In Posters Fri
Mathurin MASSIAS · Joseph Salmon · Alexandre Gramfort
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #118
Cut-Pursuit Algorithm for Regularizing Nonsmooth Functionals with Graph Total Variation
In Posters Fri
Hugo Raguet · loic landrieu
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #119
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data
In Posters Fri
Amjad Almahairi · Sai Rajeswar · Alessandro Sordoni · Philip Bachman · Aaron Courville
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #120
Mixed batches and symmetric discriminators for GAN training
In Posters Fri
Thomas LUCAS · Corentin Tallec · Yann Ollivier · Jakob Verbeek
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #121
An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method
In Posters Fri
Li Shen · Peng Sun · Yitong Wang · Wei Liu · Tong Zhang
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #124
Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling
In Posters Fri
Kejun Huang · Xiao Fu · Nicholas Sidiropoulos
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #125
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients
In Posters Fri
Lingjiao Chen · Hongyi Wang · Zachary Charles · Dimitris Papailiopoulos
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #126
Communication-Computation Efficient Gradient Coding
In Posters Fri
Min Ye · Emmanuel Abbe
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #127
Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering
In Posters Fri
Pan Li · Olgica Milenkovic
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #128
SMAC: Simultaneous Mapping and Clustering Using Spectral Decompositions
In Posters Fri
chandrajit bajaj · Tingran Gao · Zihang He · Qixing Huang · Zhenxiao Liang
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #129
On Nesting Monte Carlo Estimators
In Posters Fri
Tom Rainforth · Rob Cornish · Hongseok Yang · andrew warrington · Frank Wood
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #130
Stein Variational Gradient Descent Without Gradient
In Posters Fri
Jun Han · Qiang Liu
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #131
Detecting non-causal artifacts in multivariate linear regression models
In Posters Fri
Dominik Janzing · Bernhard Schölkopf
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #132
The Hierarchical Adaptive Forgetting Variational Filter
In Posters Fri
Vincent Moens
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #133
Junction Tree Variational Autoencoder for Molecular Graph Generation
In Posters Fri
Wengong Jin · Regina Barzilay · Tommi Jaakkola
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #134
Semi-Amortized Variational Autoencoders
In Posters Fri
Yoon Kim · Sam Wiseman · Andrew Miller · David Sontag · Alexander Rush
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #135
Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits
In Posters Fri
Huasen Wu · Xueying Guo · Xin Liu
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #136
Semiparametric Contextual Bandits
In Posters Fri
Akshay Krishnamurthy · Steven Wu · Vasilis Syrgkanis
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #137
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
In Posters Fri
Been Kim · Martin Wattenberg · Justin Gilmer · Carrie Cai · James Wexler · Fernanda Viégas · Rory sayres
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #138
Weightless: Lossy weight encoding for deep neural network compression
In Posters Fri
Brandon Reagen · Udit Gupta · Bob Adolf · Michael Mitzenmacher · Alexander Rush · Gu-Yeon Wei · David Brooks
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #139
Parallel Bayesian Network Structure Learning
In Posters Fri
Tian Gao · Dennis Wei
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #140
Temporal Poisson Square Root Graphical Models
In Posters Fri
Sinong Geng · Zhaobin Kuang · Peggy Peissig · University of Wisconsin David Page
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #141
Minimax Concave Penalized Multi-Armed Bandit Model with High-Dimensional Covariates
In Posters Fri
xue wang · Mingcheng Wei · Tao Yao
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #142
Dynamic Regret of Strongly Adaptive Methods
In Posters Fri
Lijun Zhang · Tianbao Yang · rong jin · Zhi-Hua Zhou
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #143
Distributed Clustering via LSH Based Data Partitioning
In Posters Fri
Aditya Bhaskara · Pruthuvi Maheshakya Wijewardena
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #144
Learning to Branch
In Posters Fri
Nina Balcan · Travis Dick · Tuomas Sandholm · Ellen Vitercik
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #145
Minibatch Gibbs Sampling on Large Graphical Models
In Posters Fri
Christopher De Sa · Vincent Chen · Wong
[ PDF]  [ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #146
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo
In Posters Fri
Niladri Chatterji · Nicolas Flammarion · Yian Ma · Peter Bartlett · Michael Jordan
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #147
Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning
In Posters Fri
Rodrigo A Toro Icarte · Toryn Q Klassen · Richard Valenzano · Sheila McIlraith
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #148
Generalization without Systematicity: On the Compositional Skills of Sequence-to-Sequence Recurrent Networks
In Posters Fri
Brenden Lake · Marco Baroni
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #149
Pathwise Derivatives Beyond the Reparameterization Trick
In Posters Fri
Martin Jankowiak · Fritz Obermeyer
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #150
Message Passing Stein Variational Gradient Descent
In Posters Fri
Jingwei Zhuo · Chang Liu · Jiaxin Shi · Jun Zhu · Ning Chen · Bo Zhang
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #151
State Space Gaussian Processes with Non-Gaussian Likelihood
In Posters Fri
Hannes Nickisch · Arno Solin · Alexander Grigorevskiy
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #152
Constant-Time Predictive Distributions for Gaussian Processes
In Posters Fri
Geoff Pleiss · Jacob Gardner · Kilian Weinberger · Andrew Wilson
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #153
Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks
In Posters Fri
Peter Bartlett · Dave Helmbold · Phil Long
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #154
On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups
In Posters Fri
Risi Kondor · Shubhendu Trivedi
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #155
Racing Thompson: an Efficient Algorithm for Thompson Sampling with Non-conjugate Priors
In Posters Fri
Yichi Zhou · Jun Zhu · Jingwei Zhuo
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #156
Probably Approximately Metric-Fair Learning
In Posters Fri
Gal Yona · Guy Rothblum
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #157
Neural Program Synthesis from Diverse Demonstration Videos
In Posters Fri
Shao-Hua Sun · Hyeonwoo Noh · Sriram Somasundaram · Joseph Lim
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #158
Video Prediction with Appearance and Motion Conditions
In Posters Fri
Yunseok Jang · Gunhee Kim · Yale Song
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #159
CRVI: Convex Relaxation for Variational Inference
In Posters Fri
Ghazal Fazelnia · John Paisley
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #160
Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent
In Posters Fri
Trevor Campbell · Tamara Broderick
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #161
Transformation Autoregressive Networks
In Posters Fri
Junier Oliva · Kumar Avinava Dubey · Manzil Zaheer · Barnabás Póczos · Ruslan Salakhutdinov · Eric Xing · Jeff Schneider
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #162
Learning equations for extrapolation and control
In Posters Fri
Subham S Sahoo · Christoph H. Lampert · Georg Martius
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #163
Analyzing Uncertainty in Neural Machine Translation
In Posters Fri
Myle Ott · Michael Auli · David Grangier · Marc'Aurelio Ranzato
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #164
Hierarchical Text Generation and Planning for Strategic Dialogue
In Posters Fri
Denis Yarats · Mike Lewis
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #165
Budgeted Experiment Design for Causal Structure Learning
In Posters Fri
AmirEmad Ghassami · Saber Salehkaleybar · Negar Kiyavash · Elias Bareinboim
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #166
Accurate Inference for Adaptive Linear Models
In Posters Fri
Yash Deshpande · Lester Mackey · Vasilis Syrgkanis · Matt Taddy
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #167
Path-Level Network Transformation for Efficient Architecture Search
In Posters Fri
Han Cai · Jiacheng Yang · Weinan Zhang · Song Han · Yong Yu
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #168
Progress & Compress: A scalable framework for continual learning
In Posters Fri
Jonathan Schwarz · Wojciech Czarnecki · Jelena Luketina · Agnieszka Grabska-Barwinska · Yee Teh · Razvan Pascanu · Raia Hadsell
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #169
Learning Longer-term Dependencies in RNNs with Auxiliary Losses
In Posters Fri
Trieu H Trinh · Andrew Dai · Thang Luong · Quoc Le
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #170
Understanding and Simplifying One-Shot Architecture Search
In Posters Fri
Gabriel Bender · Pieter-Jan Kindermans · Barret Zoph · Vijay Vasudevan · Quoc Le
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #171
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents
In Posters Fri
Kaiqing Zhang · Zhuoran Yang · Han Liu · Tong Zhang · Tamer Basar
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #172
State Abstractions for Lifelong Reinforcement Learning
In Posters Fri
David Abel · Dilip S. Arumugam · Lucas Lehnert · Michael L. Littman
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #173
Bounding and Counting Linear Regions of Deep Neural Networks
In Posters Fri
Thiago Serra · Christian Tjandraatmadja · Srikumar Ramalingam
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #175
Clipped Action Policy Gradient
In Posters Fri
Yasuhiro Fujita · Shin-ichi Maeda
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #176
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
In Posters Fri
Lasse Espeholt · Hubert Soyer · Remi Munos · Karen Simonyan · Vlad Mnih · Tom Ward · Yotam Doron · Vlad Firoiu · Tim Harley · Iain Dunning · Shane Legg · Koray Kavukcuoglu
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #177
Inter and Intra Topic Structure Learning with Word Embeddings
In Posters Fri
He Zhao · Lan Du · Wray Buntine · Mingyuan Zhou
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #178
oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis
In Posters Fri
Samuel Ainsworth · Nicholas J Foti · Adrian KC Lee · Emily Fox
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #179
The Hidden Vulnerability of Distributed Learning in Byzantium
In Posters Fri
El Mahdi El Mhamdi · Rachid Guerraoui · Sébastien Rouault
[ PDF] 
Poster
Fri Jul 13 09:15 AM -- 12:00 PM (PDT) @ Hall B #180
Asynchronous Byzantine Machine Learning (the case of SGD)
In Posters Fri
Georgios Damaskinos · El Mahdi El Mhamdi · Rachid Guerraoui · Rhicheek Patra · Mahsa Taziki
[ PDF] 
Break
Fri Jul 13 10:30 AM -- 11:00 AM (PDT) @ Hall B
Coffee Break
Break
Fri Jul 13 12:00 PM -- 01:30 PM (PDT)
Lunch - on your own
Break
Fri Jul 13 03:30 PM -- 04:00 PM (PDT) @ Hall B
Coffee Break
Break
Fri Jul 13 06:15 PM -- 07:15 PM (PDT) @ Hall B
Light Evening Snack
Break
Fri Jul 13 06:15 PM -- 07:00 PM (PDT) @ K1
Business Meeting
Workshop
Fri Jul 13 11:30 PM -- 03:30 AM (PDT) @ B3
Cognitive Vision: Integrated Vision and AI for Embodied Perception and Interaction
Workshop
Fri Jul 13 11:30 PM -- 03:30 AM (PDT) @ B2
Joint Workshop on AI in Health (day 2)
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ K22
Learning and Reasoning: Principles & Applications to Everyday Spatial and Temporal Knowledge (day 2)
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ A3
Fairness, Interpretability, and Explainability Federation of Workshops (day 2-3) (day 1)
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ B10
10th International Workshop on Agents in Traffic and Transportation (ATT 2018)
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ K23
19th International Workshop on Multi-Agent-Based Simulation (MABS 2018)
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ B4
Adaptive and Learning Agents 2018 (day 1)
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ T1
AI and Computational Psychology: Theories, Algorithms and Applications (CompPsy)
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ K24
AI-MHRI (AI for Multimodal Human-Robot Interaction) (day 1)
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ K14
ALAW - Agents Living in Augmented Worlds
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ K1
AutoML 2018
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ B5
Bridging the Gap between Human and Automated Reasoning
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ T4
Data Science meets Optimization
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ C3
Eighth International Workshop on Statistical Relational AI
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ C2
Enabling Reproducibility in Machine Learning MLTrain@RML
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ K12
Engineering Multi-Agent Systems (day 1)
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ T3
First international workshop on socio-cognitive systems
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ K15
Game-Theoretic Mechanisms for Data and Information
Workshop
Fri Jul 13 11:30 PM -- 03:30 AM (PDT) @ A7
Goal Specifications for Reinforcement Learning
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ B9
International Workshop on Automated Negotiation (ACAN)
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ K13
International Workshop on Optimization in Multi-Agent Systems (OptMAS)
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ C8
Joint ICML and IJCAI Workshop on Computational Biology 2018
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ A4
Lifelong Learning: A Reinforcement Learning Approach
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ A6
Modern Trends in Nonconvex Optimization for Machine Learning
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ C7
The 2018 Joint Workshop on Machine Learning for Music
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ K2
The AAMAS-IJCAI Workshop on Agents and Incentives in Artificial Intelligence (day 1)
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ A5
Theoretical Foundations and Applications of Deep Generative Models (day 1)
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ Victoria
Theory of Deep Learning
Workshop
Fri Jul 13 11:30 PM -- 09:00 AM (PDT) @ K16
TRUST Workshop