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Workshop
Fri Jul 13th 08:30 AM -- 06:00 PM @ K23
31st International Workshop on Qualitative Reasoning (QR 2018)
Workshop
Fri Jul 13th 08:30 AM -- 06:00 PM @ K24
6th Goal Reasoning Workshop
Workshop
Fri Jul 13th 08:30 AM -- 06:00 PM @ T4
Computer Games Workshop
Workshop
Fri Jul 13th 08:30 AM -- 06:00 PM @ K12
FCA4AI 2018
Workshop
Fri Jul 13th 08:30 AM -- 06:00 PM @ B2
Joint Workshop on AI in Health (day 1)
Workshop
Fri Jul 13th 08:30 AM -- 06:00 PM @ B9
Linguistic and Cognitive Approaches To Dialog Agents (LaCATODA 2018)
Workshop
Fri Jul 13th 08:30 AM -- 12:30 PM @ K22
Tenth International Workshop Modelling and Reasoning in Context (MRC)
Workshop
Fri Jul 13th 08:30 AM -- 06:00 PM @ B3
The 3rd International workshop on biomedical informatics with optimization and machine learning (BOOM)
Workshop
Fri Jul 13th 08:30 AM -- 06:00 PM @ B5
The 3rd International Workshop on Knowledge Discovery in Healthcare Data
Workshop
Fri Jul 13th 08:30 AM -- 06:00 PM @ T3
Towards learning with limited labels: Equivariance, Invariance, and Beyond
Workshop
Fri Jul 13th 08:30 AM -- 06:00 PM @ K2
Fairness, Interpretability, and Explainability Federation of Workshops (day 1)
Workshop
Fri Jul 13th 08:30 AM -- 06:00 PM @ K16
Autonomy in Teams -- Joint Workshop on Sharing Autonomy in Human-Robot Interaction
Session
Fri Jul 13th 09:00 -- 09:20 AM @ A1
Test of Time Award
Oral
Fri Jul 13th 09:30 -- 09:50 AM @ K11
Out-of-sample extension of graph adjacency spectral embedding
Keith Levin · Fred Roosta · Michael Mahoney · Carey Priebe
Oral
Fri Jul 13th 09:30 -- 09:50 AM @ A5
Dynamic Regret of Strongly Adaptive Methods
Lijun Zhang · Tianbao Yang · rong jin · Zhi-Hua Zhou
Oral
Fri Jul 13th 09:30 -- 09:50 AM @ A4
Learning in Integer Latent Variable Models with Nested Automatic Differentiation
Daniel Sheldon · Kevin Winner · Debora Sujono
Oral
Fri Jul 13th 09:30 -- 09:50 AM @ A7
Mixed batches and symmetric discriminators for GAN training
Thomas LUCAS · Corentin Tallec · Yann Ollivier · Jakob Verbeek
Oral
Fri Jul 13th 09:30 -- 09:50 AM @ A9
Convergence guarantees for a class of non-convex and non-smooth optimization problems
Koulik Khamaru · Martin Wainwright
Oral
Fri Jul 13th 09:30 -- 09:50 AM @ K1
Solving Partial Assignment Problems using Random Clique Complexes
Charu Sharma · Deepak Nathani · Manu Kaul
Oral
Fri Jul 13th 09:30 -- 09:50 AM @ Victoria
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
Been Kim · Martin Wattenberg · Justin Gilmer · Carrie Cai · James Wexler · Fernanda B Viégas · Rory sayres
Oral
Fri Jul 13th 09:30 -- 09:50 AM @ A1
RLlib: Abstractions for Distributed Reinforcement Learning
Eric Liang · Richard Liaw · Robert Nishihara · Philipp Moritz · Roy Fox · Ken Goldberg · Joseph Gonzalez · Michael Jordan · Ion Stoica
Oral
Fri Jul 13th 09:30 -- 09:50 AM @ A3
Learning Registered Point Processes from Idiosyncratic Observations
Hongteng Xu · Lawrence Carin · Hongyuan Zha
Oral
Fri Jul 13th 09:30 -- 09:50 AM @ A6
A Reductions Approach to Fair Classification
Alekh Agarwal · Alina Beygelzimer · Miroslav Dudik · John Langford · Hanna Wallach
Oral
Fri Jul 13th 09:50 -- 10:00 AM @ K1
Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction
Siyuan Qi · Baoxiong Jia · Song-Chun Zhu
Oral
Fri Jul 13th 09:50 -- 10:10 AM @ A9
A Progressive Batching L-BFGS Method for Machine Learning
Vijaya Raghavendra Bollapragada · Jorge Nocedal · Dheevatsa Mudigere · Hao-Jun M Shi · Peter Tang
Oral
Fri Jul 13th 09:50 -- 10:10 AM @ A3
Deep Bayesian Nonparametric Tracking
Aonan Zhang · John Paisley
Oral
Fri Jul 13th 09:50 -- 10:10 AM @ A1
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
Lasse Espeholt · Hubert Soyer · Remi Munos · Karen Simonyan · Vlad Mnih · Tom Ward · Yotam Doron · Vlad Firoiu · Tim Harley · Iain Dunning · Shane Legg · koray kavukcuoglu
Oral
Fri Jul 13th 09:50 -- 10:00 AM @ A7
Mutual Information Neural Estimation
Mohamed Belghazi · Aristide Baratin · Sai Rajeswar · Sherjil Ozair · Yoshua Bengio · R Devon Hjelm · Aaron Courville
Oral
Fri Jul 13th 09:50 -- 10:00 AM @ A5
Online Learning with Abstention
Corinna Cortes · Giulia DeSalvo · Claudio Gentile · Mehryar Mohri · Scott Yang
Oral
Fri Jul 13th 09:50 -- 10:00 AM @ Victoria
Learning equations for extrapolation and control
Subham S Sahoo · Christoph Lampert · Georg Martius
Oral
Fri Jul 13th 09:50 -- 10:00 AM @ A4
Sound Abstraction and Decomposition of Probabilistic Programs
Steven Holtzen · Guy Van den Broeck · Todd Millstein
Oral
Fri Jul 13th 09:50 -- 10:10 AM @ A6
Probably Approximately Metric-Fair Learning
Gal Yona · Guy Rothblum
Oral
Fri Jul 13th 09:50 -- 10:00 AM @ K11
Bayesian Model Selection for Change Point Detection and Clustering
othmane mazhar · Cristian R. Rojas · Inst. of Technology Carlo Fischione · Mohammad Reza Hesamzadeh
Oral
Fri Jul 13th 10:00 -- 10:10 AM @ K11
An Iterative, Sketching-based Framework for Ridge Regression
Agniva Chowdhury · Jiasen Yang · Petros Drineas
Oral
Fri Jul 13th 10:00 -- 10:10 AM @ A7
Adversarially Regularized Autoencoders
Jake Zhao · Yoon Kim · Kelly Zhang · Alexander Rush · Yann LeCun
Oral
Fri Jul 13th 10:00 -- 10:10 AM @ K1
Video Prediction with Appearance and Motion Conditions
Yunseok Jang · Gunhee Kim · Yale Song
Oral
Fri Jul 13th 10:00 -- 10:10 AM @ Victoria
PDE-Net: Learning PDEs from Data
Zichao Long · Yiping Lu · Xianzhong Ma · Bin Dong
Oral
Fri Jul 13th 10:00 -- 10:10 AM @ A4
Parallel Bayesian Network Structure Learning
Tian Gao · Dennis Wei
Oral
Fri Jul 13th 10:00 -- 10:10 AM @ A5
Multi-Fidelity Black-Box Optimization with Hierarchical Partitions
Rajat Sen · kirthevasan kandasamy · Sanjay Shakkottai
Oral
Fri Jul 13th 10:10 -- 10:20 AM @ A3
Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling
Kejun Huang · Xiao Fu · Nicholas Sidiropoulos
Oral
Fri Jul 13th 10:10 -- 10:20 AM @ K1
Neural Program Synthesis from Diverse Demonstration Videos
Shao-Hua Sun · Hyeonwoo Noh · Sriram Somasundaram · Joseph Lim
Oral
Fri Jul 13th 10:10 -- 10:20 AM @ A9
Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solution for Nonconvex Distributed Optimization Over Networks
Mingyi Hong · Meisam Razaviyayn · Jason Lee
Oral
Fri Jul 13th 10:10 -- 10:20 AM @ A4
The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference
Hao Lu · Yuan Cao · Junwei Lu · Han Liu · Zhaoran Wang
Oral
Fri Jul 13th 10:10 -- 10:20 AM @ A7
JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets
Yunchen Pu · Shuyang Dai · Zhe Gan · Weiyao Wang · Guoyin Wang · Yizhe Zhang · Ricardo Henao · Lawrence Carin
Oral
Fri Jul 13th 10:10 -- 10:20 AM @ A5
Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits
Huasen Wu · Xueying Guo · Xin Liu
Oral
Fri Jul 13th 10:10 -- 10:20 AM @ A6
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
Michael Kearns · Seth V Neel · Aaron Roth · Zhiwei Wu
Oral
Fri Jul 13th 10:10 -- 10:20 AM @ K11
Provable Variable Selection for Streaming Features
Jing Wang · Jie Shen · Ping Li
Oral
Fri Jul 13th 10:10 -- 10:20 AM @ A1
Mix & Match - Agent Curricula for Reinforcement Learning
Wojciech Czarnecki · Siddhant Jayakumar · Max Jaderberg · Leonard Hasenclever · Yee Teh · Nicolas Heess · Simon Osindero · Razvan Pascanu
Oral
Fri Jul 13th 10:10 -- 10:20 AM @ Victoria
Transformation Autoregressive Networks
Junier Oliva · Kumar Avinava Dubey · Manzil Zaheer · Barnabás Póczos · Ruslan Salakhutdinov · Eric Xing · Jeff Schneider
Oral
Fri Jul 13th 10:20 -- 10:30 AM @ A4
Temporal Poisson Square Root Graphical Models
Sinong Geng · Zhaobin Kuang · Peggy Peissig · University of Wisconsin David Page
Oral
Fri Jul 13th 10:20 -- 10:30 AM @ A7
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data
Amjad Almahairi · Sai Rajeswar · Alessandro Sordoni · Philip Bachman · Aaron Courville
Oral
Fri Jul 13th 10:20 -- 10:30 AM @ A9
Estimation of Markov Chain via Rank-constrained Likelihood
XUDONG LI · Mengdi Wang · Anru Zhang
Oral
Fri Jul 13th 10:20 -- 10:30 AM @ A6
Blind Justice: Fairness with Encrypted Sensitive Attributes
Niki Kilbertus · Adria Gascon · Matt Kusner · Michael Veale · Krishna Gummadi · Adrian Weller
Oral
Fri Jul 13th 10:20 -- 10:30 AM @ A1
Learning to Explore via Meta-Policy Gradient
Tianbing Xu · Qiang Liu · Liang Zhao · Jian Peng
Oral
Fri Jul 13th 10:20 -- 10:30 AM @ K11
Learning Low-Dimensional Temporal Representations
Bing Su · Ying Wu
Oral
Fri Jul 13th 10:20 -- 10:30 AM @ A5
Firing Bandits: Optimizing Crowdfunding
Lalit Jain · Kevin Jamieson
Oral
Fri Jul 13th 10:20 -- 10:30 AM @ Victoria
Weightless: Lossy weight encoding for deep neural network compression
Brandon Reagen · Udit Gupta · Bob Adolf · Michael Mitzenmacher · Alexander Rush · Gu-Yeon Wei · David Brooks
Break
Fri Jul 13th 10:30 -- 11:00 AM @ Hall B
Coffee Break
Oral
Fri Jul 13th 11:00 -- 11:20 AM @ K1
Spurious Local Minima are Common in Two-Layer ReLU Neural Networks
Itay Safran · Ohad Shamir
Oral
Fri Jul 13th 11:00 -- 11:20 AM @ Victoria
Efficient Neural Audio Synthesis
Nal Kalchbrenner · Erich Elsen · Karen Simonyan · Seb Noury · Norman Casagrande · Edward Lockhart · Florian Stimberg · Aäron van den Oord · Sander Dieleman · koray kavukcuoglu
Oral
Fri Jul 13th 11:00 -- 11:20 AM @ A9
A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming
Alp Yurtsever · Olivier Fercoq · Francesco Locatello · Volkan Cevher
Oral
Fri Jul 13th 11:00 -- 11:20 AM @ A6
Theoretical Analysis of Sparse Subspace Clustering with Missing Entries
Manolis Tsakiris · Rene Vidal
Oral
Fri Jul 13th 11:00 -- 11:20 AM @ A5
Online Linear Quadratic Control
Alon Cohen · Avinatan Hasidim · Tomer Koren · Nevena Lazic · Yishay Mansour · Kunal Talwar
Oral
Fri Jul 13th 11:00 -- 11:20 AM @ A4
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)
Trefor Evans · Prasanth B Nair
Oral
Fri Jul 13th 11:00 -- 11:20 AM @ K11
Competitive Caching with Machine Learned Advice
Thodoris Lykouris · Sergei Vassilvitskii
Oral
Fri Jul 13th 11:00 -- 11:20 AM @ A7
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin · Regina Barzilay · Tommi Jaakkola
Oral
Fri Jul 13th 11:00 -- 11:20 AM @ A1
Hierarchical Imitation and Reinforcement Learning
Hoang M Le · Nan Jiang · Alekh Agarwal · Miroslav Dudik · Yisong Yue · Hal Daume
Oral
Fri Jul 13th 11:00 -- 11:20 AM @ A3
Learning Adversarially Fair and Transferable Representations
David Madras · Elliot Creager · Toniann Pitassi · Richard Zemel
Oral
Fri Jul 13th 11:20 -- 11:40 AM @ A9
Frank-Wolfe with Subsampling Oracle
Thomas Kerdreux · Fabian Pedregosa · Alexandre d'Aspremont
Oral
Fri Jul 13th 11:20 -- 11:40 AM @ A5
Semiparametric Contextual Bandits
Akshay Krishnamurthy · Zhiwei Wu · Vasilis Syrgkanis
Oral
Fri Jul 13th 11:20 -- 11:30 AM @ A6
Improved nearest neighbor search using auxiliary information and priority functions
Omid Keivani · Kaushik Sinha
Oral
Fri Jul 13th 11:20 -- 11:30 AM @ A3
Learning Semantic Representations for Unsupervised Domain Adaptation
Shaoan Xie · Zibin Zheng · Liang Chen · Chuan Chen
Oral
Fri Jul 13th 11:20 -- 11:30 AM @ K11
Distributed Clustering via LSH Based Data Partitioning
Aditya Bhaskara · Pruthuvi Wijewardena
Oral
Fri Jul 13th 11:20 -- 11:40 AM @ Victoria
Understanding and Simplifying One-Shot Architecture Search
Gabriel Bender · Pieter-Jan Kindermans · Barret Zoph · Vijay Vasudevan · Quoc Le
Oral
Fri Jul 13th 11:20 -- 11:40 AM @ A4
State Space Gaussian Processes with Non-Gaussian Likelihood
Hannes Nickisch · Arno Solin · Alexander Grigorevskiy
Oral
Fri Jul 13th 11:20 -- 11:40 AM @ K1
Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks
Peter Bartlett · Dave Helmbold · Phil Long
Oral
Fri Jul 13th 11:20 -- 11:40 AM @ A1
Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning
Rodrigo A Toro Icarte · Toryn Q Klassen · Richard Valenzano · Sheila McIlraith
Oral
Fri Jul 13th 11:20 -- 11:40 AM @ A7
Semi-Amortized Variational Autoencoders
Yoon Kim · Sam Wiseman · Andrew Miller · David Sontag · Alexander Rush
Oral
Fri Jul 13th 11:30 -- 11:40 AM @ K11
Learning to Branch
Nina Balcan · Travis Dick · Tuomas Sandholm · Ellen Vitercik
Oral
Fri Jul 13th 11:30 -- 11:40 AM @ A3
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
Judy Hoffman · Eric Tzeng · Taesung Park · Jun-Yan Zhu · Philip Isola · Kate Saenko · Alexei Efros · Trevor Darrell
Oral
Fri Jul 13th 11:30 -- 11:40 AM @ A6
QuantTree: Histograms for Change Detection in Multivariate Data Streams
Giacomo Boracchi · Diego Carrera · Cristiano Cervellera · Danilo Macciò
Oral
Fri Jul 13th 11:40 -- 11:50 AM @ K11
Compiling Combinatorial Prediction Games
Frederic Koriche
Oral
Fri Jul 13th 11:40 -- 11:50 AM @ K1
On the Power of Over-parametrization in Neural Networks with Quadratic Activation
Simon Du · Jason Lee
Oral
Fri Jul 13th 11:40 -- 11:50 AM @ A1
State Abstractions for Lifelong Reinforcement Learning
David Abel · Dilip S. Arumugam · Lucas Lehnert · Michael L. Littman
Oral
Fri Jul 13th 11:40 -- 11:50 AM @ A7
Iterative Amortized Inference
Joseph Marino · Yisong Yue · Stephan Mandt
Oral
Fri Jul 13th 11:40 -- 11:50 AM @ A9
On Matching Pursuit and Coordinate Descent
Francesco Locatello · Anant Raj · Sai Praneeth Reddy Karimireddy · Gunnar Raetsch · Bernhard Schölkopf · Sebastian Stich · Martin Jaggi
Oral
Fri Jul 13th 11:40 -- 11:50 AM @ Victoria
Path-Level Network Transformation for Efficient Architecture Search
Han Cai · Jiacheng Yang · Weinan Zhang · Song Han · Yong Yu
Oral
Fri Jul 13th 11:40 -- 11:50 AM @ A4
Constant-Time Predictive Distributions for Gaussian Processes
Geoff Pleiss · Jacob Gardner · Kilian Weinberger · Andrew Wilson
Oral
Fri Jul 13th 11:40 -- 11:50 AM @ A6
Topological mixture estimation
Steve Huntsman
Oral
Fri Jul 13th 11:40 -- 11:50 AM @ A5
Minimax Concave Penalized Multi-Armed Bandit Model with High-Dimensional Covariates
xue wang · Mingcheng Wei · Tao Yao
Oral
Fri Jul 13th 11:40 -- 11:50 AM @ A3
Rectify Heterogeneous Models with Semantic Mapping
Han-Jia Ye · De-Chuan Zhan · Yuan Jiang · Zhi-Hua Zhou
Oral
Fri Jul 13th 11:50 AM -- 12:00 PM @ A6
Revealing Common Statistical Behaviors in Heterogeneous Populations
Andrey Zhitnikov · Rotem Mulayoff · Tomer Michaeli
Oral
Fri Jul 13th 11:50 AM -- 12:00 PM @ A7
DVAE++: Discrete Variational Autoencoders with Overlapping Transformations
Arash Vahdat · William Macready · Zhengbing Bian · Amir Khoshaman · Evgeny Andriyash
Oral
Fri Jul 13th 11:50 AM -- 12:00 PM @ K1
Optimization Landscape and Expressivity of Deep CNNs
Quynh Nguyen · Matthias Hein
Oral
Fri Jul 13th 11:50 AM -- 12:00 PM @ A3
Detecting and Correcting for Label Shift with Black Box Predictors
Zachary Lipton · Yu-Xiang Wang · Alexander Smola
Oral
Fri Jul 13th 11:50 AM -- 12:00 PM @ Victoria
Learning Longer-term Dependencies in RNNs with Auxiliary Losses
Trieu H Trinh · Andrew Dai · Thang Luong · Quoc Le
Oral
Fri Jul 13th 11:50 AM -- 12:00 PM @ A5
Racing Thompson: an Efficient Algorithm for Thompson Sampling with Non-conjugate Priors
Yichi Zhou · Jun Zhu · Jingwei Zhuo
Oral
Fri Jul 13th 11:50 AM -- 12:00 PM @ A1
Policy Optimization with Demonstrations
Bingyi Kang · Zequn Jie · Jiashi Feng
Oral
Fri Jul 13th 11:50 AM -- 12:00 PM @ A4
Large-Scale Cox Process Inference using Variational Fourier Features
ST John · James Hensman
Oral
Fri Jul 13th 11:50 AM -- 12:00 PM @ A9
Adaptive Three Operator Splitting
Fabian Pedregosa · Gauthier Gidel
Oral
Fri Jul 13th 11:50 AM -- 12:00 PM @ K11
Approximation Algorithms for Cascading Prediction Models
Matthew Streeter
Break
Fri Jul 13th 12:00 -- 01:30 PM @
Lunch - on your own
Invited Talk
Fri Jul 13th 01:30 -- 02:30 PM @ A1
Language to Action: towards Interactive Task Learning with Physical Agents
Joyce Chai
Workshop
Fri Jul 13th 02:00 -- 06:00 PM @ K22
Learning and Reasoning: Principles & Applications to Everyday Spatial and Temporal Knowledge (day 1)
Invited Talk
Fri Jul 13th 02:30 -- 03:30 PM @ A1
Building Machines that Learn and Think Like People
Josh Tenenbaum
Break
Fri Jul 13th 03:30 -- 04:00 PM @ Hall B
Coffee Break
Oral
Fri Jul 13th 04:00 -- 04:20 PM @ A6
Candidates vs. Noises Estimation for Large Multi-Class Classification Problem
Lei Han · Yiheng Huang · Tong Zhang
Oral
Fri Jul 13th 04:00 -- 04:20 PM @ A7
Parallel WaveNet: Fast High-Fidelity Speech Synthesis
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
Oral
Fri Jul 13th 04:00 -- 04:20 PM @ K11
On the Spectrum of Random Features Maps of High Dimensional Data
Zhenyu Liao · Romain Couillet
Oral
Fri Jul 13th 04:00 -- 04:20 PM @ A1
Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator
Maryam Fazel · Rong Ge · Sham Kakade · Mehran Mesbahi
Oral
Fri Jul 13th 04:00 -- 04:20 PM @ A9
SADAGRAD: Strongly Adaptive Stochastic Gradient Methods
Zaiyi Chen · Yi Xu · Enhong Chen · Tianbao Yang
Oral
Fri Jul 13th 04:00 -- 04:20 PM @ Victoria
Progress & Compress: A scalable framework for continual learning
Jonathan Schwarz · Wojciech Czarnecki · Jelena Luketina · Agnieszka Grabska-Barwinska · Yee Teh · Razvan Pascanu · Raia Hadsell
Oral
Fri Jul 13th 04:00 -- 04:20 PM @ K1
Efficient end-to-end learning for quantizable representations
Yeonwoo Jeong · Hyun Oh Song
Oral
Fri Jul 13th 04:00 -- 04:20 PM @ A3
The Hidden Vulnerability of Distributed Learning in Byzantium
El Mahdi El Mhamdi · Rachid Guerraoui · Sébastien Rouault
Oral
Fri Jul 13th 04:00 -- 04:20 PM @ A4
Stein Variational Gradient Descent Without Gradient
Jun Han · Qiang Liu
Oral
Fri Jul 13th 04:00 -- 04:20 PM @ A5
Causal Bandits with Propagating Inference
Akihiro Yabe · Daisuke Hatano · Hanna Sumita · Shinji Ito · Naonori Kakimura · Takuro Fukunaga · Ken-ichi Kawarabayashi
Oral
Fri Jul 13th 04:20 -- 04:30 PM @ A6
CRAFTML, an Efficient Clustering-based Random Forest for Extreme Multi-label Learning
Wissam Siblini · Frank Meyer · Pascale Kuntz
Oral
Fri Jul 13th 04:20 -- 04:40 PM @ A4
Minibatch Gibbs Sampling on Large Graphical Models
Chris De Sa · Vincent Chen · Wong
Oral
Fri Jul 13th 04:20 -- 04:30 PM @ A9
Level-Set Methods for Finite-Sum Constrained Convex Optimization
Qihang Lin · Runchao Ma · Tianbao Yang
Oral
Fri Jul 13th 04:20 -- 04:40 PM @ A5
Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions
Karren Yang · Abigail Katoff · Caroline Uhler
Oral
Fri Jul 13th 04:20 -- 04:30 PM @ K11
SMAC: Simultaneous Mapping and Clustering Using Spectral Decompositions
chandrajit bajaj · Tingran Gao · Zihang He · Qixing Huang · Zhenxiao Liang
Oral
Fri Jul 13th 04:20 -- 04:40 PM @ A3
Asynchronous Byzantine Machine Learning (the case of SGD)
Georgios Damaskinos · El Mahdi El Mhamdi · Rachid Guerraoui · Rhicheek Patra · Mahsa Taziki
Oral
Fri Jul 13th 04:20 -- 04:30 PM @ A1
Policy Optimization as Wasserstein Gradient Flows
RUIYI ZHANG · Changyou Chen · Chunyuan Li · Lawrence Carin
Oral
Fri Jul 13th 04:20 -- 04:30 PM @ K1
High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach
Tim Pearce · Alexandra Brintrup · Mohamed Zaki · Andy Neely
Oral
Fri Jul 13th 04:20 -- 04:40 PM @ A7
Autoregressive Quantile Networks for Generative Modeling
Georg Ostrovski · Will Dabney · Remi Munos
Oral
Fri Jul 13th 04:20 -- 04:40 PM @ Victoria
Overcoming Catastrophic Forgetting with Hard Attention to the Task
Joan Serrà · Didac Suris · Marius Miron · Alexandros Karatzoglou
Oral
Fri Jul 13th 04:30 -- 04:40 PM @ K1
A Boo(n) for Evaluating Architecture Performance
Ondrej Bajgar · Rudolf Kadlec · Jan Kleindienst
Oral
Fri Jul 13th 04:30 -- 04:40 PM @ A1
Clipped Action Policy Gradient
Yasuhiro Fujita · Shin-ichi Maeda
Oral
Fri Jul 13th 04:30 -- 04:40 PM @ A9
Local Convergence Properties of SAGA/Prox-SVRG and Acceleration
Clarice Poon · Jingwei Liang · Carola-Bibiane Schönlieb
Oral
Fri Jul 13th 04:30 -- 04:40 PM @ K11
Spectrally Approximating Large Graphs with Smaller Graphs
Andreas Loukas · Pierre Vandergheynst
Oral
Fri Jul 13th 04:30 -- 04:40 PM @ A6
Attention-based Deep Multiple Instance Learning
Maximilian Ilse · Jakub Tomczak · Max Welling
Oral
Fri Jul 13th 04:40 -- 04:50 PM @ K11
Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering
Pan Li · Olgica Milenkovic
Oral
Fri Jul 13th 04:40 -- 04:50 PM @ A9
Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions
Pan Xu · Tianhao Wang · Quanquan Gu
Oral
Fri Jul 13th 04:40 -- 04:50 PM @ Victoria
Rapid Adaptation with Conditionally Shifted Neurons
Tsendsuren Munkhdalai · Xingdi Yuan · Soroush Mehri · Adam Trischler
Oral
Fri Jul 13th 04:40 -- 04:50 PM @ A3
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients
Lingjiao Chen · Hongyi Wang · Zachary Charles · Dimitris Papailiopoulos
Oral
Fri Jul 13th 04:40 -- 04:50 PM @ A6
Learning and Memorization
Satrajit Chatterjee
Oral
Fri Jul 13th 04:40 -- 04:50 PM @ K1
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors
Gintare Karolina Dziugaite · Daniel Roy
Oral
Fri Jul 13th 04:40 -- 04:50 PM @ A5
Budgeted Experiment Design for Causal Structure Learning
AmirEmad Ghassami · Saber Salehkaleybar · Negar Kiyavash · Elias Bareinboim
Oral
Fri Jul 13th 04:40 -- 04:50 PM @ A4
On Nesting Monte Carlo Estimators
Tom Rainforth · Rob Cornish · Hongseok Yang · andrew warrington · Frank Wood
Oral
Fri Jul 13th 04:40 -- 04:50 PM @ A7
Stochastic Video Generation with a Learned Prior
Emily Denton · Rob Fergus
Oral
Fri Jul 13th 04:40 -- 04:50 PM @ A1
Fourier Policy Gradients
Matthew Fellows · Kamil Ciosek · Shimon Whiteson
Oral
Fri Jul 13th 04:50 -- 05:00 PM @ A7
Disentangled Sequential Autoencoder
Yingzhen Li · Stephan Mandt
Oral
Fri Jul 13th 04:50 -- 05:00 PM @ A4
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo
Niladri S Chatterji · Nicolas Flammarion · Yian Ma · Peter Bartlett · Michael Jordan
Oral
Fri Jul 13th 04:50 -- 05:00 PM @ K1
On the Limitations of First-Order Approximation in GAN Dynamics
Jerry Li · Aleksander Madry · John Peebles · Ludwig Schmidt
Oral
Fri Jul 13th 04:50 -- 05:00 PM @ A3
Communication-Computation Efficient Gradient Coding
Min Ye · Emmanuel Abbe
Oral
Fri Jul 13th 04:50 -- 05:00 PM @ Victoria
Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace
Yoonho Lee · Seungjin Choi
Oral
Fri Jul 13th 04:50 -- 05:00 PM @ A1
Self-Imitation Learning
Junhyuk Oh · Yijie Guo · Satinder Singh · Honglak Lee
Oral
Fri Jul 13th 04:50 -- 05:00 PM @ A6
Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings
Aviral Kumar · Sunita Sarawagi · Ujjwal Jain
Oral
Fri Jul 13th 04:50 -- 05:00 PM @ A9
Fast Gradient-Based Methods with Exponential Rate: A Hybrid Control Framework
Arman Sharifi Kolarijani · Peyman Mohajerin Esfahani · Tamas Keviczky
Oral
Fri Jul 13th 04:50 -- 05:00 PM @ A5
The Hierarchical Adaptive Forgetting Variational Filter
Vincent Moens
Oral
Fri Jul 13th 04:50 -- 05:00 PM @ K11
Rates of Convergence of Spectral Methods for Graphon Estimation
Jiaming Xu
Oral
Fri Jul 13th 05:00 -- 05:20 PM @ A6
A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization
Robin Vogel · Aurélien Bellet · Stéphan Clémençon
Oral
Fri Jul 13th 05:00 -- 05:20 PM @ A1
Mean Field Multi-Agent Reinforcement Learning
Yaodong Yang · Rui Luo · Minne Li · Ming Zhou · Weinan Zhang · Jun Wang
Oral
Fri Jul 13th 05:00 -- 05:20 PM @ A5
Orthogonal Machine Learning: Power and Limitations
Ilias Zadik · Lester Mackey · Vasilis Syrgkanis
Oral
Fri Jul 13th 05:00 -- 05:20 PM @ A3
Analyzing Uncertainty in Neural Machine Translation
Myle Ott · Michael Auli · David Grangier · Marc'Aurelio Ranzato
Oral
Fri Jul 13th 05:00 -- 05:20 PM @ A4
Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent
Trevor Campbell · Tamara Broderick
Oral
Fri Jul 13th 05:00 -- 05:20 PM @ K11
Convolutional Imputation of Matrix Networks
Qingyun Sun · Mengyuan Yan · David Donoho · stephen boyd
Oral
Fri Jul 13th 05:00 -- 05:20 PM @ A7
Modeling Sparse Deviations for Compressed Sensing using Generative Models
Manik Dhar · Aditya Grover · Stefano Ermon
Oral
Fri Jul 13th 05:00 -- 05:20 PM @ A9
Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis
Pengtao Xie · Wei Wu · Yichen Zhu · Eric Xing
Oral
Fri Jul 13th 05:00 -- 05:20 PM @ Victoria
WSNet: Compact and Efficient Networks Through Weight Sampling
Xiaojie Jin · Yingzhen Yang · Ning Xu · Jianchao Yang · Nebojsa Jojic · Jiashi Feng · Shuicheng Yan
Oral
Fri Jul 13th 05:00 -- 05:20 PM @ K1
On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups
Risi Kondor · Shubhendu Trivedi
Oral
Fri Jul 13th 05:20 -- 05:40 PM @ A5
Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models
Raj Agrawal · Caroline Uhler · Tamara Broderick
Oral
Fri Jul 13th 05:20 -- 05:30 PM @ A7
oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis
Samuel Ainsworth · Nicholas J Foti · Adrian KC Lee · Emily Fox
Oral
Fri Jul 13th 05:20 -- 05:40 PM @ Victoria
StrassenNets: Deep Learning with a Multiplication Budget
Michael Tschannen · Aran Khanna · Animashree Anandkumar
Oral
Fri Jul 13th 05:20 -- 05:30 PM @ A3
Generalization without Systematicity: On the Compositional Skills of Sequence-to-Sequence Recurrent Networks
Brenden Lake · Marco Baroni
Oral
Fri Jul 13th 05:20 -- 05:30 PM @ A9
Celer: a Fast Solver for the Lasso with Dual Extrapolation
Mathurin MASSIAS · Joseph Salmon · Alexandre Gramfort
Oral
Fri Jul 13th 05:20 -- 05:30 PM @ K11
Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow
Xiao Zhang · Simon Du · Quanquan Gu
Oral
Fri Jul 13th 05:20 -- 05:30 PM @ A4
CRVI: Convex Relaxation for Variational Inference
Ghazal Fazelnia · John Paisley
Oral
Fri Jul 13th 05:20 -- 05:30 PM @ A6
Classification from Pairwise Similarity and Unlabeled Data
Han Bao · Gang Niu · Masashi Sugiyama
Oral
Fri Jul 13th 05:20 -- 05:30 PM @ K1
Bounding and Counting Linear Regions of Deep Neural Networks
Thiago Serra · Christian Tjandraatmadja · Srikumar Ramalingam
Oral
Fri Jul 13th 05:20 -- 05:40 PM @ A1
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control
Yangchen Pan · Amir-massoud Farahmand · Martha White · Saleh Nabi · Piyush Grover · Daniel Nikovski
Oral
Fri Jul 13th 05:30 -- 05:40 PM @ A4
Stein Points
Wilson Ye Chen · Lester Mackey · Jackson Gorham · Francois-Xavier Briol · Chris J Oates
Oral
Fri Jul 13th 05:30 -- 05:40 PM @ A6
Comparison-Based Random Forests
Siavash Haghiri · Damien Garreau · Ulrike von Luxburg
Oral
Fri Jul 13th 05:30 -- 05:40 PM @ A3
Adaptive Sampled Softmax with Kernel Based Sampling
Guy Blanc · Steffen Rendle
Oral
Fri Jul 13th 05:30 -- 05:40 PM @ K1
DCFNet: Deep Neural Network with Decomposed Convolutional Filters
Qiang Qiu · Xiuyuan Cheng · robert Calderbank · Guillermo Sapiro
Oral
Fri Jul 13th 05:30 -- 05:40 PM @ A9
Cut-Pursuit Algorithm for Regularizing Nonsmooth Functionals with Graph Total Variation
Hugo Raguet · loic landrieu
Oral
Fri Jul 13th 05:30 -- 05:40 PM @ K11
On the Implicit Bias of Dropout
Poorya Mianjy · Raman Arora · Rene Vidal
Oral
Fri Jul 13th 05:30 -- 05:40 PM @ A7
Noisin: Unbiased Regularization for Recurrent Neural Networks
Adji Bousso Dieng · Rajesh Ranganath · Jaan Altosaar · David Blei
Oral
Fri Jul 13th 05:40 -- 05:50 PM @ A3
Hierarchical Text Generation and Planning for Strategic Dialogue
Denis Yarats · Mike Lewis
Oral
Fri Jul 13th 05:40 -- 05:50 PM @ K11
A Unified Framework for Structured Low-rank Matrix Learning
Pratik Kumar Jawanpuria · Bamdev Mishra
Oral
Fri Jul 13th 05:40 -- 05:50 PM @ A4
Message Passing Stein Variational Gradient Descent
Jingwei Zhuo · Chang Liu · Jiaxin Shi · Jun Zhu · Ning Chen · Bo Zhang
Oral
Fri Jul 13th 05:40 -- 05:50 PM @ Victoria
Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions
Junru Wu · Yue Wang · Zhenyu Wu · Zhangyang Wang · Ashok Veeraraghavan · Yingyan Lin
Oral
Fri Jul 13th 05:40 -- 05:50 PM @ A1
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents
Kaiqing Zhang · Zhuoran Yang · Han Liu · Tong Zhang · Tamer Basar
Oral
Fri Jul 13th 05:40 -- 05:50 PM @ A6
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples
Yizhen Wang · Somesh Jha · Kamalika Chaudhuri
Oral
Fri Jul 13th 05:40 -- 05:50 PM @ A7
Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series
Zhengping Che · Sanjay Purushotham · Max Guangyu Li · Bo Jiang · Yan Liu
Oral
Fri Jul 13th 05:40 -- 05:50 PM @ K1
A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations
Weili Nie · Yang Zhang · Ankit Patel
Oral
Fri Jul 13th 05:40 -- 05:50 PM @ A9
Efficient First-Order Algorithms for Adaptive Signal Denoising
Dmitrii Ostrovskii · Zaid Harchaoui
Oral
Fri Jul 13th 05:40 -- 05:50 PM @ A5
Accurate Inference for Adaptive Linear Models
Yash Deshpande · Lester Mackey · Vasilis Syrgkanis · Matt Taddy
Oral
Fri Jul 13th 05:50 -- 06:00 PM @ A4
Pathwise Derivatives Beyond the Reparameterization Trick
Martin Jankowiak · Fritz Obermeyer
Oral
Fri Jul 13th 05:50 -- 06:00 PM @ Victoria
Born Again Neural Networks
Tommaso Furlanello · Zachary Lipton · Michael Tschannen · Laurent Itti · Anima Anandkumar
Oral
Fri Jul 13th 05:50 -- 06:00 PM @ A7
Inter and Intra Topic Structure Learning with Word Embeddings
He Zhao · Lan Du · Wray Buntine · Mingyuan Zhou
Oral
Fri Jul 13th 05:50 -- 06:00 PM @ A6
Active Learning with Logged Data
Songbai Yan · Kamalika Chaudhuri · Tara Javidi
Oral
Fri Jul 13th 05:50 -- 06:00 PM @ A5
Detecting non-causal artifacts in multivariate linear regression models
Dominik Janzing · Bernhard Schölkopf
Oral
Fri Jul 13th 05:50 -- 06:00 PM @ K11
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers
Yao Ma · Alexander Olshevsky · Csaba Szepesvari · Venkatesh Saligrama
Oral
Fri Jul 13th 05:50 -- 06:00 PM @ A1
The Uncertainty Bellman Equation and Exploration
Brendan O'Donoghue · Ian Osband · Remi Munos · Vlad Mnih
Oral
Fri Jul 13th 05:50 -- 06:00 PM @ A9
An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method
Li Shen · Peng Sun · Yitong Wang · Wei Liu · Tong Zhang
Break
Fri Jul 13th 06:15 -- 07:15 PM @ Hall B
Light Evening Snack
Break
Fri Jul 13th 06:15 -- 07:00 PM @ K1
Business Meeting
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #1
Stein Points
Wilson Ye Chen · Lester Mackey · Jackson Gorham · Francois-Xavier Briol · Chris J Oates
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #2
Large-Scale Cox Process Inference using Variational Fourier Features
ST John · James Hensman
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #3
SADAGRAD: Strongly Adaptive Stochastic Gradient Methods
Zaiyi Chen · Yi Xu · Enhong Chen · Tianbao Yang
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #4
Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solution for Nonconvex Distributed Optimization Over Networks
Mingyi Hong · Meisam Razaviyayn · Jason Lee
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #5
A Progressive Batching L-BFGS Method for Machine Learning
Vijaya Raghavendra Bollapragada · Jorge Nocedal · Dheevatsa Mudigere · Hao-Jun M Shi · Peter Tang
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #6
WSNet: Compact and Efficient Networks Through Weight Sampling
Xiaojie Jin · Yingzhen Yang · Ning Xu · Jianchao Yang · Nebojsa Jojic · Jiashi Feng · Shuicheng Yan
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #7
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors
Gintare Karolina Dziugaite · Daniel Roy
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #8
High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach
Tim Pearce · Alexandra Brintrup · Mohamed Zaki · Andy Neely
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #9
Competitive Caching with Machine Learned Advice
Thodoris Lykouris · Sergei Vassilvitskii
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #10
Approximation Algorithms for Cascading Prediction Models
Matthew Streeter
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #11
Orthogonal Machine Learning: Power and Limitations
Ilias Zadik · Lester Mackey · Vasilis Syrgkanis
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #12
Causal Bandits with Propagating Inference
Akihiro Yabe · Daisuke Hatano · Hanna Sumita · Shinji Ito · Naonori Kakimura · Takuro Fukunaga · Ken-ichi Kawarabayashi
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #13
Mix & Match - Agent Curricula for Reinforcement Learning
Wojciech Czarnecki · Siddhant Jayakumar · Max Jaderberg · Leonard Hasenclever · Yee Teh · Nicolas Heess · Simon Osindero · Razvan Pascanu
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #14
The Uncertainty Bellman Equation and Exploration
Brendan O'Donoghue · Ian Osband · Remi Munos · Vlad Mnih
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #15
Hierarchical Imitation and Reinforcement Learning
Hoang M Le · Nan Jiang · Alekh Agarwal · Miroslav Dudik · Yisong Yue · Hal Daume
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #16
Policy Optimization with Demonstrations
Bingyi Kang · Zequn Jie · Jiashi Feng
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #17
Fast Gradient-Based Methods with Exponential Rate: A Hybrid Control Framework
Arman Sharifi Kolarijani · Peyman Mohajerin Esfahani · Tamas Keviczky
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #18
Level-Set Methods for Finite-Sum Constrained Convex Optimization
Qihang Lin · Runchao Ma · Tianbao Yang
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #19
A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations
Weili Nie · Yang Zhang · Ankit Patel
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #20
A Boo(n) for Evaluating Architecture Performance
Ondrej Bajgar · Rudolf Kadlec · Jan Kleindienst
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #21
RLlib: Abstractions for Distributed Reinforcement Learning
Eric Liang · Richard Liaw · Robert Nishihara · Philipp Moritz · Roy Fox · Ken Goldberg · Joseph Gonzalez · Michael Jordan · Ion Stoica
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #22
Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator
Maryam Fazel · Rong Ge · Sham Kakade · Mehran Mesbahi
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #23
The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference
Hao Lu · Yuan Cao · Junwei Lu · Han Liu · Zhaoran Wang
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #24
Sound Abstraction and Decomposition of Probabilistic Programs
Steven Holtzen · Guy Van den Broeck · Todd Millstein
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #25
Parallel WaveNet: Fast High-Fidelity Speech Synthesis
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
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #26
Modeling Sparse Deviations for Compressed Sensing using Generative Models
Manik Dhar · Aditya Grover · Stefano Ermon
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #27
Revealing Common Statistical Behaviors in Heterogeneous Populations
Andrey Zhitnikov · Rotem Mulayoff · Tomer Michaeli
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #28
Improved nearest neighbor search using auxiliary information and priority functions
Omid Keivani · Kaushik Sinha
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #29
Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings
Aviral Kumar · Sunita Sarawagi · Ujjwal Jain
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #30
QuantTree: Histograms for Change Detection in Multivariate Data Streams
Giacomo Boracchi · Diego Carrera · Cristiano Cervellera · Danilo Macciò
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #31
An Iterative, Sketching-based Framework for Ridge Regression
Agniva Chowdhury · Jiasen Yang · Petros Drineas
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #32
Learning Low-Dimensional Temporal Representations
Bing Su · Ying Wu
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #33
Rapid Adaptation with Conditionally Shifted Neurons
Tsendsuren Munkhdalai · Xingdi Yuan · Soroush Mehri · Adam Trischler
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #34
PDE-Net: Learning PDEs from Data
Zichao Long · Yiping Lu · Xianzhong Ma · Bin Dong
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #35
Theoretical Analysis of Sparse Subspace Clustering with Missing Entries
Manolis Tsakiris · Rene Vidal
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #36
Topological mixture estimation
Steve Huntsman
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #37
On Matching Pursuit and Coordinate Descent
Francesco Locatello · Anant Raj · Sai Praneeth Reddy Karimireddy · Gunnar Raetsch · Bernhard Schölkopf · Sebastian Stich · Martin Jaggi
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #38
Frank-Wolfe with Subsampling Oracle
Thomas Kerdreux · Fabian Pedregosa · Alexandre d'Aspremont
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #39
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control
Yangchen Pan · Amir-massoud Farahmand · Martha White · Saleh Nabi · Piyush Grover · Daniel Nikovski
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #40
Fourier Policy Gradients
Matthew Fellows · Kamil Ciosek · Shimon Whiteson
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #41
Adaptive Three Operator Splitting
Fabian Pedregosa · Gauthier Gidel
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #42
A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming
Alp Yurtsever · Olivier Fercoq · Francesco Locatello · Volkan Cevher
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #43
Learning Semantic Representations for Unsupervised Domain Adaptation
Shaoan Xie · Zibin Zheng · Liang Chen · Chuan Chen
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #44
Learning Adversarially Fair and Transferable Representations
David Madras · Elliot Creager · Toniann Pitassi · Richard Zemel
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #45
Spurious Local Minima are Common in Two-Layer ReLU Neural Networks
Itay Safran · Ohad Shamir
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #46
Efficient end-to-end learning for quantizable representations
Yeonwoo Jeong · Hyun Oh Song
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #47
Solving Partial Assignment Problems using Random Clique Complexes
Charu Sharma · Deepak Nathani · Manu Kaul
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #48
Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction
Siyuan Qi · Baoxiong Jia · Song-Chun Zhu
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #49
Convergence guarantees for a class of non-convex and non-smooth optimization problems
Koulik Khamaru · Martin Wainwright
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #50
Estimation of Markov Chain via Rank-constrained Likelihood
XUDONG LI · Mengdi Wang · Anru Zhang
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #51
Efficient First-Order Algorithms for Adaptive Signal Denoising
Dmitrii Ostrovskii · Zaid Harchaoui
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #52
Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions
Pan Xu · Tianhao Wang · Quanquan Gu
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #53
Noisin: Unbiased Regularization for Recurrent Neural Networks
Adji Bousso Dieng · Rajesh Ranganath · Jaan Altosaar · David Blei
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #54
Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series
Zhengping Che · Sanjay Purushotham · Max Guangyu Li · Bo Jiang · Yan Liu
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #55
Disentangled Sequential Autoencoder
Yingzhen Li · Stephan Mandt
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #56
Stochastic Video Generation with a Learned Prior
Emily Denton · Rob Fergus
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #57
Mutual Information Neural Estimation
Mohamed Belghazi · Aristide Baratin · Sai Rajeswar · Sherjil Ozair · Yoshua Bengio · R Devon Hjelm · Aaron Courville
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #58
Adversarially Regularized Autoencoders
Jake Zhao · Yoon Kim · Kelly Zhang · Alexander Rush · Yann LeCun
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #59
Policy Optimization as Wasserstein Gradient Flows
RUIYI ZHANG · Changyou Chen · Chunyuan Li · Lawrence Carin
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #60
Self-Imitation Learning
Junhyuk Oh · Yijie Guo · Satinder Singh · Honglak Lee
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #61
Spectrally Approximating Large Graphs with Smaller Graphs
Andreas Loukas · Pierre Vandergheynst
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #62
On the Spectrum of Random Features Maps of High Dimensional Data
Zhenyu Liao · Romain Couillet
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #63
Learning Registered Point Processes from Idiosyncratic Observations
Hongteng Xu · Lawrence Carin · Hongyuan Zha
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #64
Deep Bayesian Nonparametric Tracking
Aonan Zhang · John Paisley
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #65
Learning and Memorization
Satrajit Chatterjee
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #66
Attention-based Deep Multiple Instance Learning
Maximilian Ilse · Jakub Tomczak · Max Welling
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #67
Classification from Pairwise Similarity and Unlabeled Data
Han Bao · Gang Niu · Masashi Sugiyama
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #68
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples
Yizhen Wang · Somesh Jha · Kamalika Chaudhuri
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #69
On the Implicit Bias of Dropout
Poorya Mianjy · Raman Arora · Rene Vidal
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #70
Convolutional Imputation of Matrix Networks
Qingyun Sun · Mengyuan Yan · David Donoho · stephen boyd
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #71
Detecting and Correcting for Label Shift with Black Box Predictors
Zachary Lipton · Yu-Xiang Wang · Alexander Smola
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #72
Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis
Pengtao Xie · Wei Wu · Yichen Zhu · Eric Xing
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #73
Comparison-Based Random Forests
Siavash Haghiri · Damien Garreau · Ulrike von Luxburg
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #74
A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization
Robin Vogel · Aurélien Bellet · Stéphan Clémençon
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #75
Provable Variable Selection for Streaming Features
Jing Wang · Jie Shen · Ping Li
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #76
Out-of-sample extension of graph adjacency spectral embedding
Keith Levin · Fred Roosta · Michael Mahoney · Carey Priebe
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #77
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers
Yao Ma · Alexander Olshevsky · Csaba Szepesvari · Venkatesh Saligrama
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #78
Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow
Xiao Zhang · Simon Du · Quanquan Gu
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #79
DCFNet: Deep Neural Network with Decomposed Convolutional Filters
Qiang Qiu · Xiuyuan Cheng · robert Calderbank · Guillermo Sapiro
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #80
Optimization Landscape and Expressivity of Deep CNNs
Quynh Nguyen · Matthias Hein
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #81
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)
Trefor Evans · Prasanth B Nair
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #82
Learning in Integer Latent Variable Models with Nested Automatic Differentiation
Daniel Sheldon · Kevin Winner · Debora Sujono
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #83
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
Judy Hoffman · Eric Tzeng · Taesung Park · Jun-Yan Zhu · Philip Isola · Kate Saenko · Alexei Efros · Trevor Darrell
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #84
Rectify Heterogeneous Models with Semantic Mapping
Han-Jia Ye · De-Chuan Zhan · Yuan Jiang · Zhi-Hua Zhou
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #85
DVAE++: Discrete Variational Autoencoders with Overlapping Transformations
Arash Vahdat · William Macready · Zhengbing Bian · Amir Khoshaman · Evgeny Andriyash
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #86
Iterative Amortized Inference
Joseph Marino · Yisong Yue · Stephan Mandt
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #87
Blind Justice: Fairness with Encrypted Sensitive Attributes
Niki Kilbertus · Adria Gascon · Matt Kusner · Michael Veale · Krishna Gummadi · Adrian Weller
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #88
Active Learning with Logged Data
Songbai Yan · Kamalika Chaudhuri · Tara Javidi
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #89
A Reductions Approach to Fair Classification
Alekh Agarwal · Alina Beygelzimer · Miroslav Dudik · John Langford · Hanna Wallach
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #90
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
Michael Kearns · Seth V Neel · Aaron Roth · Zhiwei Wu
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #91
Bayesian Model Selection for Change Point Detection and Clustering
othmane mazhar · Cristian R. Rojas · Inst. of Technology Carlo Fischione · Mohammad Reza Hesamzadeh
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #92
A Unified Framework for Structured Low-rank Matrix Learning
Pratik Kumar Jawanpuria · Bamdev Mishra
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #93
Firing Bandits: Optimizing Crowdfunding
Lalit Jain · Kevin Jamieson
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #94
Multi-Fidelity Black-Box Optimization with Hierarchical Partitions
Rajat Sen · kirthevasan kandasamy · Sanjay Shakkottai
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #95
Compiling Combinatorial Prediction Games
Frederic Koriche
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #96
Rates of Convergence of Spectral Methods for Graphon Estimation
Jiaming Xu
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #97
Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions
Karren Yang · Abigail Katoff · Caroline Uhler
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #98
Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models
Raj Agrawal · Caroline Uhler · Tamara Broderick
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #99
StrassenNets: Deep Learning with a Multiplication Budget
Michael Tschannen · Aran Khanna · Animashree Anandkumar
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #100
Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace
Yoonho Lee · Seungjin Choi
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #101
Candidates vs. Noises Estimation for Large Multi-Class Classification Problem
Lei Han · Yiheng Huang · Tong Zhang
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #102
CRAFTML, an Efficient Clustering-based Random Forest for Extreme Multi-label Learning
Wissam Siblini · Frank Meyer · Pascale Kuntz
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #103
Overcoming Catastrophic Forgetting with Hard Attention to the Task
Joan Serrà · Didac Suris · Marius Miron · Alexandros Karatzoglou
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #104
Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions
Junru Wu · Yue Wang · Zhenyu Wu · Zhangyang Wang · Ashok Veeraraghavan · Yingyan Lin
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #105
Efficient Neural Audio Synthesis
Nal Kalchbrenner · Erich Elsen · Karen Simonyan · Seb Noury · Norman Casagrande · Edward Lockhart · Florian Stimberg · Aäron van den Oord · Sander Dieleman · koray kavukcuoglu
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #106
Born Again Neural Networks
Tommaso Furlanello · Zachary Lipton · Michael Tschannen · Laurent Itti · Anima Anandkumar
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #107
Adaptive Sampled Softmax with Kernel Based Sampling
Guy Blanc · Steffen Rendle
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #109
JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets
Yunchen Pu · Shuyang Dai · Zhe Gan · Weiyao Wang · Guoyin Wang · Yizhe Zhang · Ricardo Henao · Lawrence Carin
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #110
Autoregressive Quantile Networks for Generative Modeling
Georg Ostrovski · Will Dabney · Remi Munos
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #111
On the Power of Over-parametrization in Neural Networks with Quadratic Activation
Simon Du · Jason Lee
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #112
On the Limitations of First-Order Approximation in GAN Dynamics
Jerry Li · Aleksander Madry · John Peebles · Ludwig Schmidt
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #113
Learning to Explore via Meta-Policy Gradient
Tianbing Xu · Qiang Liu · Liang Zhao · Jian Peng
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #114
Mean Field Multi-Agent Reinforcement Learning
Yaodong Yang · Rui Luo · Minne Li · Ming Zhou · Weinan Zhang · Jun Wang
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #115
Online Linear Quadratic Control
Alon Cohen · Avinatan Hasidim · Tomer Koren · Nevena Lazic · Yishay Mansour · Kunal Talwar
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #116
Online Learning with Abstention
Corinna Cortes · Giulia DeSalvo · Claudio Gentile · Mehryar Mohri · Scott Yang
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #117
Celer: a Fast Solver for the Lasso with Dual Extrapolation
Mathurin MASSIAS · Joseph Salmon · Alexandre Gramfort
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #118
Cut-Pursuit Algorithm for Regularizing Nonsmooth Functionals with Graph Total Variation
Hugo Raguet · loic landrieu
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #119
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data
Amjad Almahairi · Sai Rajeswar · Alessandro Sordoni · Philip Bachman · Aaron Courville
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #120
Mixed batches and symmetric discriminators for GAN training
Thomas LUCAS · Corentin Tallec · Yann Ollivier · Jakob Verbeek
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #121
An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method
Li Shen · Peng Sun · Yitong Wang · Wei Liu · Tong Zhang
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #124
Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling
Kejun Huang · Xiao Fu · Nicholas Sidiropoulos
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #125
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients
Lingjiao Chen · Hongyi Wang · Zachary Charles · Dimitris Papailiopoulos
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #126
Communication-Computation Efficient Gradient Coding
Min Ye · Emmanuel Abbe
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #127
Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering
Pan Li · Olgica Milenkovic
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #128
SMAC: Simultaneous Mapping and Clustering Using Spectral Decompositions
chandrajit bajaj · Tingran Gao · Zihang He · Qixing Huang · Zhenxiao Liang
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #129
On Nesting Monte Carlo Estimators
Tom Rainforth · Rob Cornish · Hongseok Yang · andrew warrington · Frank Wood
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #130
Stein Variational Gradient Descent Without Gradient
Jun Han · Qiang Liu
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #131
Detecting non-causal artifacts in multivariate linear regression models
Dominik Janzing · Bernhard Schölkopf
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #132
The Hierarchical Adaptive Forgetting Variational Filter
Vincent Moens
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #133
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin · Regina Barzilay · Tommi Jaakkola
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #134
Semi-Amortized Variational Autoencoders
Yoon Kim · Sam Wiseman · Andrew Miller · David Sontag · Alexander Rush
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #135
Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits
Huasen Wu · Xueying Guo · Xin Liu
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #136
Semiparametric Contextual Bandits
Akshay Krishnamurthy · Zhiwei Wu · Vasilis Syrgkanis
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #137
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
Been Kim · Martin Wattenberg · Justin Gilmer · Carrie Cai · James Wexler · Fernanda B Viégas · Rory sayres
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #138
Weightless: Lossy weight encoding for deep neural network compression
Brandon Reagen · Udit Gupta · Bob Adolf · Michael Mitzenmacher · Alexander Rush · Gu-Yeon Wei · David Brooks
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #139
Parallel Bayesian Network Structure Learning
Tian Gao · Dennis Wei
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #140
Temporal Poisson Square Root Graphical Models
Sinong Geng · Zhaobin Kuang · Peggy Peissig · University of Wisconsin David Page
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #141
Minimax Concave Penalized Multi-Armed Bandit Model with High-Dimensional Covariates
xue wang · Mingcheng Wei · Tao Yao
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #142
Dynamic Regret of Strongly Adaptive Methods
Lijun Zhang · Tianbao Yang · rong jin · Zhi-Hua Zhou
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #143
Distributed Clustering via LSH Based Data Partitioning
Aditya Bhaskara · Pruthuvi Wijewardena
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #144
Learning to Branch
Nina Balcan · Travis Dick · Tuomas Sandholm · Ellen Vitercik
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #145
Minibatch Gibbs Sampling on Large Graphical Models
Chris De Sa · Vincent Chen · Wong
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #146
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo
Niladri S Chatterji · Nicolas Flammarion · Yian Ma · Peter Bartlett · Michael Jordan
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #147
Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning
Rodrigo A Toro Icarte · Toryn Q Klassen · Richard Valenzano · Sheila McIlraith
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #148
Generalization without Systematicity: On the Compositional Skills of Sequence-to-Sequence Recurrent Networks
Brenden Lake · Marco Baroni
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #149
Pathwise Derivatives Beyond the Reparameterization Trick
Martin Jankowiak · Fritz Obermeyer
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #150
Message Passing Stein Variational Gradient Descent
Jingwei Zhuo · Chang Liu · Jiaxin Shi · Jun Zhu · Ning Chen · Bo Zhang
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #151
State Space Gaussian Processes with Non-Gaussian Likelihood
Hannes Nickisch · Arno Solin · Alexander Grigorevskiy
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #152
Constant-Time Predictive Distributions for Gaussian Processes
Geoff Pleiss · Jacob Gardner · Kilian Weinberger · Andrew Wilson
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #153
Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks
Peter Bartlett · Dave Helmbold · Phil Long
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #154
On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups
Risi Kondor · Shubhendu Trivedi
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #155
Racing Thompson: an Efficient Algorithm for Thompson Sampling with Non-conjugate Priors
Yichi Zhou · Jun Zhu · Jingwei Zhuo
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #156
Probably Approximately Metric-Fair Learning
Gal Yona · Guy Rothblum
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #157
Neural Program Synthesis from Diverse Demonstration Videos
Shao-Hua Sun · Hyeonwoo Noh · Sriram Somasundaram · Joseph Lim
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #158
Video Prediction with Appearance and Motion Conditions
Yunseok Jang · Gunhee Kim · Yale Song
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #159
CRVI: Convex Relaxation for Variational Inference
Ghazal Fazelnia · John Paisley
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #160
Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent
Trevor Campbell · Tamara Broderick
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #161
Transformation Autoregressive Networks
Junier Oliva · Kumar Avinava Dubey · Manzil Zaheer · Barnabás Póczos · Ruslan Salakhutdinov · Eric Xing · Jeff Schneider
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #162
Learning equations for extrapolation and control
Subham S Sahoo · Christoph Lampert · Georg Martius
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #163
Analyzing Uncertainty in Neural Machine Translation
Myle Ott · Michael Auli · David Grangier · Marc'Aurelio Ranzato
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #164
Hierarchical Text Generation and Planning for Strategic Dialogue
Denis Yarats · Mike Lewis
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #165
Budgeted Experiment Design for Causal Structure Learning
AmirEmad Ghassami · Saber Salehkaleybar · Negar Kiyavash · Elias Bareinboim
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #166
Accurate Inference for Adaptive Linear Models
Yash Deshpande · Lester Mackey · Vasilis Syrgkanis · Matt Taddy
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #167
Path-Level Network Transformation for Efficient Architecture Search
Han Cai · Jiacheng Yang · Weinan Zhang · Song Han · Yong Yu
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #168
Progress & Compress: A scalable framework for continual learning
Jonathan Schwarz · Wojciech Czarnecki · Jelena Luketina · Agnieszka Grabska-Barwinska · Yee Teh · Razvan Pascanu · Raia Hadsell
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #169
Learning Longer-term Dependencies in RNNs with Auxiliary Losses
Trieu H Trinh · Andrew Dai · Thang Luong · Quoc Le
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #170
Understanding and Simplifying One-Shot Architecture Search
Gabriel Bender · Pieter-Jan Kindermans · Barret Zoph · Vijay Vasudevan · Quoc Le
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #171
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents
Kaiqing Zhang · Zhuoran Yang · Han Liu · Tong Zhang · Tamer Basar
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #172
State Abstractions for Lifelong Reinforcement Learning
David Abel · Dilip S. Arumugam · Lucas Lehnert · Michael L. Littman
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #173
Bounding and Counting Linear Regions of Deep Neural Networks
Thiago Serra · Christian Tjandraatmadja · Srikumar Ramalingam
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #175
Clipped Action Policy Gradient
Yasuhiro Fujita · Shin-ichi Maeda
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #176
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
Lasse Espeholt · Hubert Soyer · Remi Munos · Karen Simonyan · Vlad Mnih · Tom Ward · Yotam Doron · Vlad Firoiu · Tim Harley · Iain Dunning · Shane Legg · koray kavukcuoglu
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #177
Inter and Intra Topic Structure Learning with Word Embeddings
He Zhao · Lan Du · Wray Buntine · Mingyuan Zhou
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #178
oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis
Samuel Ainsworth · Nicholas J Foti · Adrian KC Lee · Emily Fox
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #179
The Hidden Vulnerability of Distributed Learning in Byzantium
El Mahdi El Mhamdi · Rachid Guerraoui · Sébastien Rouault
Poster
Fri Jul 13th 06:15 -- 09:00 PM @ Hall B #180
Asynchronous Byzantine Machine Learning (the case of SGD)
Georgios Damaskinos · El Mahdi El Mhamdi · Rachid Guerraoui · Rhicheek Patra · Mahsa Taziki