Skip to yearly menu bar Skip to main content


(426 events)   Timezone:  
Toggle Poster Visibility
Oral
Fri Jul 13 12:00 AM -- 12:20 AM (KST) @ K1
Composable Planning with Attributes
Amy Zhang · Sainbayar Sukhbaatar · Adam Lerer · Arthur Szlam · Facebook Rob Fergus
[ PDF [ Video
Oral
Fri Jul 13 12:00 AM -- 12:20 AM (KST) @ A9
Stochastic Wasserstein Barycenters
Sebastian Claici · Edward Chien · Justin Solomon
[ PDF
Oral
Fri Jul 13 12:00 AM -- 12:20 AM (KST) @ Victoria
ContextNet: Deep learning for Star Galaxy Classification
Noble Kennamer · University of California David Kirkby · Alexander Ihler · University of California Francisco Javier Sanchez-Lopez
[ PDF
Oral
Fri Jul 13 12:00 AM -- 12:20 AM (KST) @ A3
Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation
Dane Corneil · Wulfram Gerstner · Johanni Brea
[ PDF [ Video
Oral
Fri Jul 13 12:00 AM -- 12:20 AM (KST) @ A7
Synthesizing Programs for Images using Reinforced Adversarial Learning
Iaroslav Ganin · Tejas Kulkarni · Igor Babuschkin · S. M. Ali Eslami · Oriol Vinyals
[ PDF
Oral
Fri Jul 13 12:00 AM -- 12:20 AM (KST) @ A6
SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate
Aaditya Ramdas · Tijana Zrnic · Martin Wainwright · Michael Jordan
[ PDF [ Video
Oral
Fri Jul 13 12:00 AM -- 12:20 AM (KST) @ K11
Representation Tradeoffs for Hyperbolic Embeddings
Frederic Sala · Christopher De Sa · Albert Gu · Christopher Re
[ PDF [ Video
Oral
Fri Jul 13 12:00 AM -- 12:20 AM (KST) @ A1
An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning
Dhruv Malik · Malayandi Palaniappan · Jaime Fisac · Dylan Hadfield-Menell · Stuart Russell · Anca Dragan
[ PDF
Oral
Fri Jul 13 12:00 AM -- 12:20 AM (KST) @ A4
Neural Autoregressive Flows
Chin-Wei Huang · David Krueger · Alexandre Lacoste · Aaron Courville
[ PDF
Oral
Fri Jul 13 12:00 AM -- 12:20 AM (KST) @ A5
Let’s be Honest: An Optimal No-Regret Framework for Zero-Sum Games
Ehsan Asadi Kangarshahi · Ya-Ping Hsieh · Mehmet Fatih Sahin · Volkan Cevher
[ PDF [ Video
Oral
Fri Jul 13 12:20 AM -- 12:30 AM (KST) @ A9
Learning Compact Neural Networks with Regularization
Samet Oymak
[ PDF
Oral
Fri Jul 13 12:20 AM -- 12:30 AM (KST) @ A5
Weakly Consistent Optimal Pricing Algorithms in Repeated Posted-Price Auctions with Strategic Buyer
Alexey Drutsa
[ PDF [ Video
Oral
Fri Jul 13 12:20 AM -- 12:30 AM (KST) @ A1
Fast Bellman Updates for Robust MDPs
Chin Pang Ho · Marek Petrik · Wolfram Wiesemann
[ PDF
Oral
Fri Jul 13 12:20 AM -- 12:30 AM (KST) @ A4
Distilling the Posterior in Bayesian Neural Networks
Kuan-Chieh Wang · Paul Vicol · James Lucas · Li Gu · Roger Grosse · Richard Zemel
[ PDF [ Video
Oral
Fri Jul 13 12:20 AM -- 12:30 AM (KST) @ A7
MAGAN: Aligning Biological Manifolds
Matt Amodio · Smita Krishnaswamy
[ PDF
Oral
Fri Jul 13 12:20 AM -- 12:40 AM (KST) @ K1
Measuring abstract reasoning in neural networks
Adam Santoro · Feilx Hill · David GT Barrett · Ari S Morcos · Timothy Lillicrap
[ PDF [ PDF [ Video
Oral
Fri Jul 13 12:20 AM -- 12:30 AM (KST) @ Victoria
Autoregressive Convolutional Neural Networks for Asynchronous Time Series
Mikolaj Binkowski · Gautier Marti · Philippe Donnat
[ PDF
Oral
Fri Jul 13 12:20 AM -- 12:40 AM (KST) @ A3
Deep Variational Reinforcement Learning for POMDPs
Maximilian Igl · Luisa Zintgraf · Tuan Anh Le · Frank Wood · Shimon Whiteson
[ PDF [ Video
Oral
Fri Jul 13 12:20 AM -- 12:40 AM (KST) @ K11
Massively Parallel Algorithms and Hardness for Single-Linkage Clustering under $\ell_p$ Distances
Grigory Yaroslavtsev · Adithya Vadapalli
[ PDF [ Video
Oral
Fri Jul 13 12:20 AM -- 12:30 AM (KST) @ A6
Open Category Detection with PAC Guarantees
Si Liu · Risheek Garrepalli · Thomas Dietterich · Alan Fern · Dan Hendrycks
[ PDF [ Video
Oral
Fri Jul 13 12:30 AM -- 12:40 AM (KST) @ Victoria
Hierarchical Multi-Label Classification Networks
Jonatas Wehrmann · Ricardo Cerri · Rodrigo Barros
[ PDF
Oral
Fri Jul 13 12:30 AM -- 12:40 AM (KST) @ A1
Decoupling Gradient-Like Learning Rules from Representations
Philip Thomas · Christoph Dann · Emma Brunskill
[ PDF
Oral
Fri Jul 13 12:30 AM -- 12:40 AM (KST) @ A4
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks
Mattias Teye · Hossein Azizpour · Kevin Smith
[ PDF [ Video
Oral
Fri Jul 13 12:30 AM -- 12:40 AM (KST) @ A5
Self-Bounded Prediction Suffix Tree via Approximate String Matching
Dongwoo Kim · Christian Walder
[ PDF [ Video
Oral
Fri Jul 13 12:30 AM -- 12:40 AM (KST) @ A7
Max-Mahalanobis Linear Discriminant Analysis Networks
Tianyu Pang · Chao Du · Jun Zhu
[ PDF
Oral
Fri Jul 13 12:30 AM -- 12:40 AM (KST) @ A9
Riemannian Stochastic Recursive Gradient Algorithm with Retraction and Vector Transport and Its Convergence Analysis
Hiroyuki Kasai · Hiroyuki Sato · Bamdev Mishra
[ PDF
Oral
Fri Jul 13 12:30 AM -- 12:40 AM (KST) @ A6
Unbiased Objective Estimation in Predictive Optimization
Shinji Ito · Akihiro Yabe · Ryohei Fujimaki
[ PDF [ Video
Oral
Fri Jul 13 12:40 AM -- 12:50 AM (KST) @ A3
Recurrent Predictive State Policy Networks
Ahmed Hefny · Zita Marinho · Wen Sun · Siddhartha Srinivasa · Geoff Gordon
[ PDF [ Video
Oral
Fri Jul 13 12:40 AM -- 12:50 AM (KST) @ Victoria
Nonparametric variable importance using an augmented neural network with multi-task learning
Jean Feng · Brian Williamson · Noah Simon · Marco Carone
[ PDF
Oral
Fri Jul 13 12:40 AM -- 12:50 AM (KST) @ A1
PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos
Paavo Parmas · Carl E Rasmussen · Jan Peters · Kenji Doya
[ PDF
Oral
Fri Jul 13 12:40 AM -- 12:50 AM (KST) @ A4
Noisy Natural Gradient as Variational Inference
Guodong Zhang · Shengyang Sun · David Duvenaud · Roger Grosse
[ PDF [ Video
Oral
Fri Jul 13 12:40 AM -- 12:50 AM (KST) @ A9
Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering
Ahmed Douik · Babak Hassibi
[ PDF
Oral
Fri Jul 13 12:40 AM -- 12:50 AM (KST) @ A5
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection
Jeremias Knoblauch · Theodoros Damoulas
[ PDF [ Video
Oral
Fri Jul 13 12:40 AM -- 12:50 AM (KST) @ K1
GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks
Zhao Chen · Vijay Badrinarayanan · Chen-Yu Lee · Andrew Rabinovich
[ PDF [ Video
Oral
Fri Jul 13 12:40 AM -- 12:50 AM (KST) @ K11
Local Density Estimation in High Dimensions
Xian Wu · Moses Charikar · Vishnu Natchu
[ PDF [ Video
Oral
Fri Jul 13 12:40 AM -- 12:50 AM (KST) @ A7
Adversarial Time-to-Event Modeling
Paidamoyo Chapfuwa · Chenyang Tao · Chunyuan Li · Courtney Page · Benjamin Goldstein · Lawrence Carin · Ricardo Henao
[ PDF
Oral
Fri Jul 13 12:40 AM -- 12:50 AM (KST) @ A6
Goodness-of-fit Testing for Discrete Distributions via Stein Discrepancy
Jiasen Yang · Qiang Liu · Vinayak A Rao · Jennifer Neville
[ PDF [ Video
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (KST) @ K1
Explicit Inductive Bias for Transfer Learning with Convolutional Networks
Xuhong LI · Yves Grandvalet · Franck Davoine
[ PDF [ Video
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (KST) @ A9
Graphical Nonconvex Optimization via an Adaptive Convex Relaxation
Qiang Sun · Kean Ming Tan · Han Liu · Tong Zhang
[ PDF
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (KST) @ K11
Improving Sign Random Projections With Additional Information
Keegan Kang · Wei Pin Wong
[ PDF [ Video
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (KST) @ A4
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors
Soumya Ghosh · Jiayu Yao · Finale Doshi-Velez
[ PDF
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (KST) @ A7
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training
Xi Wu · Wooyeong Jang · Jiefeng Chen · Lingjiao Chen · Somesh Jha
[ PDF
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (KST) @ Victoria
Knowledge Transfer with Jacobian Matching
Suraj Srinivas · Francois Fleuret
[ PDF
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (KST) @ A3
Regret Minimization for Partially Observable Deep Reinforcement Learning
Peter Jin · EECS Kurt Keutzer · Sergey Levine
[ PDF [ Video
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (KST) @ A1
Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning
Thomas Dietterich · George Trimponias · Zhitang Chen
[ PDF
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (KST) @ A6
Towards Black-box Iterative Machine Teaching
Weiyang Liu · Bo Dai · Xingguo Li · Zhen Liu · James Rehg · Le Song
[ PDF [ Video
Oral
Fri Jul 13 12:50 AM -- 01:00 AM (KST) @ A5
Learning Localized Spatio-Temporal Models From Streaming Data
Muhammad Osama · Dave Zachariah · Thomas Schön
[ PDF [ Video
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #1
Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion
Richard Zhang · Salar Fattahi · Somayeh Sojoudi
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #2
Robust and Scalable Models of Microbiome Dynamics
Travis Gibson · Georg Gerber
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #3
Explicit Inductive Bias for Transfer Learning with Convolutional Networks
Xuhong LI · Yves Grandvalet · Franck Davoine
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #4
GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks
Zhao Chen · Vijay Badrinarayanan · Chen-Yu Lee · Andrew Rabinovich
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #5
Optimizing the Latent Space of Generative Networks
Piotr Bojanowski · Armand Joulin · David Lopez-Paz · Arthur Szlam
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #6
Theoretical Analysis of Image-to-Image Translation with Adversarial Learning
Xudong Pan · Mi Zhang · Daizong Ding
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #7
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
Tuomas Haarnoja · Aurick Zhou · Pieter Abbeel · Sergey Levine
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #8
PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos
Paavo Parmas · Carl E Rasmussen · Jan Peters · Kenji Doya
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #9
Probabilistic Recurrent State-Space Models
Andreas Doerr · Christian Daniel · Martin Schiegg · Duy Nguyen-Tuong · Stefan Schaal · Marc Toussaint · Sebastian Trimpe
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #10
Structured Variationally Auto-encoded Optimization
Xiaoyu Lu · Javier González · Zhenwen Dai · Neil Lawrence
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #11
A Robust Approach to Sequential Information Theoretic Planning
Sue Zheng · Jason Pacheco · John Fisher
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #12
Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap
Miles Lopes · Shusen Wang · Michael Mahoney
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #13
Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go?
Zhengyuan Zhou · Panayotis Mertikopoulos · Nicholas Bambos · Peter Glynn · Yinyu Ye · Li-Jia Li · Li Fei-Fei
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #14
Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization
Jiaxiang Wu · Weidong Huang · Junzhou Huang · Tong Zhang
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #15
Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering
Ahmed Douik · Babak Hassibi
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #16
Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients
Lukas Balles · Philipp Hennig
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #17
Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning
Thomas Dietterich · George Trimponias · Zhitang Chen
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #18
Differentially Private Database Release via Kernel Mean Embeddings
Matej Balog · Ilya Tolstikhin · Bernhard Schölkopf
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #19
Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples
Gail Weiss · Yoav Goldberg · Eran Yahav
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #20
Neural Dynamic Programming for Musical Self Similarity
Christian Walder · Dongwoo Kim
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #21
Learning long term dependencies via Fourier recurrent units
Jiong Zhang · Yibo Lin · Zhao Song · Inderjit Dhillon
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #22
Autoregressive Convolutional Neural Networks for Asynchronous Time Series
Mikolaj Binkowski · Gautier Marti · Philippe Donnat
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #23
Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation
Dane Corneil · Wulfram Gerstner · Johanni Brea
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #24
Regret Minimization for Partially Observable Deep Reinforcement Learning
Peter Jin · EECS Kurt Keutzer · Sergey Levine
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #25
Goodness-of-fit Testing for Discrete Distributions via Stein Discrepancy
Jiasen Yang · Qiang Liu · Vinayak A Rao · Jennifer Neville
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #26
Unbiased Objective Estimation in Predictive Optimization
Shinji Ito · Akihiro Yabe · Ryohei Fujimaki
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #27
Ultra Large-Scale Feature Selection using Count-Sketches
Amirali Aghazadeh · Ryan Spring · Daniel LeJeune · Gautam Dasarathy · Anshumali Shrivastava · Richard Baraniuk
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #28
Matrix Norms in Data Streams: Faster, Multi-Pass and Row-Order
Vladimir Braverman · Stephen Chestnut · Robert Krauthgamer · Yi Li · David Woodruff · Lin Yang
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #29
Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?
Maithra Raghu · Alexander Irpan · Jacob Andreas · Bobby Kleinberg · Quoc Le · Jon Kleinberg
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #30
The Mirage of Action-Dependent Baselines in Reinforcement Learning
George Tucker · Surya Bhupatiraju · Shixiang Gu · Richard E Turner · Zoubin Ghahramani · Sergey Levine
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #31
Composite Marginal Likelihood Methods for Random Utility Models
Zhibing Zhao · Lirong Xia
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #32
Ranking Distributions based on Noisy Sorting
Adil El Mesaoudi-Paul · Eyke Hüllermeier · Robert Busa-Fekete
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #33
DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding
Thomas Moreau · Laurent Oudre · Nicolas Vayatis
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #34
Exploring Hidden Dimensions in Accelerating Convolutional Neural Networks
Zhihao Jia · Sina Lin · Charles Qi · Alex Aiken
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #35
Deep Models of Interactions Across Sets
Jason Hartford · Devon Graham · Kevin Leyton-Brown · Siamak Ravanbakhsh
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #36
ContextNet: Deep learning for Star Galaxy Classification
Noble Kennamer · University of California David Kirkby · Alexander Ihler · University of California Francisco Javier Sanchez-Lopez
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #37
First Order Generative Adversarial Networks
Calvin Seward · Thomas Unterthiner · Urs M Bergmann · Nikolay Jetchev · Sepp Hochreiter
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #38
Max-Mahalanobis Linear Discriminant Analysis Networks
Tianyu Pang · Chao Du · Jun Zhu
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #39
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time
Asish Ghoshal · Jean Honorio
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #40
Structured Output Learning with Abstention: Application to Accurate Opinion Prediction
Alexandre Garcia · Telecom-ParisTech Chloé Clavel · Slim Essid · Florence d'Alche-Buc
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #41
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation
Bo Dai · Albert Shaw · Lihong Li · Lin Xiao · Niao He · Zhen Liu · Jianshu Chen · Le Song
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #42
Smoothed Action Value Functions for Learning Gaussian Policies
Ofir Nachum · Mohammad Norouzi · George Tucker · Dale Schuurmans
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #43
Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron
RJ Skerry-Ryan · Eric Battenberg · Ying Xiao · Yuxuan Wang · Daisy Stanton · Joel Shor · Ron Weiss · Robert Clark · Rif Saurous
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #44
Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis
Yuxuan Wang · Daisy Stanton · Yu Zhang · RJ-Skerry Ryan · Eric Battenberg · Joel Shor · Ying Xiao · Ye Jia · Fei Ren · Rif Saurous
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #45
AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning
Ahmed M. Alaa · Mihaela van der Schaar
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #46
TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service
Amartya Sanyal · Matt Kusner · Adria Gascon · Varun Kanade
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #47
End-to-End Learning for the Deep Multivariate Probit Model
Di Chen · Yexiang Xue · Carla Gomes
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #48
Differentiable Dynamic Programming for Structured Prediction and Attention
Arthur Mensch · Mathieu Blondel
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #49
Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods
Junhong Lin · Volkan Cevher
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #50
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
Dong Yin · Yudong Chen · Kannan Ramchandran · Peter Bartlett
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #51
SQL-Rank: A Listwise Approach to Collaborative Ranking
LIWEI WU · Cho-Jui Hsieh · University of California James Sharpnack
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #52
Extreme Learning to Rank via Low Rank Assumption
Minhao Cheng · Ian Davidson · Cho-Jui Hsieh
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #53
Adversarial Attack on Graph Structured Data
Hanjun Dai · Hui Li · Tian Tian · Xin Huang · Lin Wang · Jun Zhu · Le Song
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #54
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training
Xi Wu · Wooyeong Jang · Jiefeng Chen · Lingjiao Chen · Somesh Jha
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #55
Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization
Louis Filstroff · Alberto Lumbreras · Cedric Fevotte
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #56
Learning Binary Latent Variable Models: A Tensor Eigenpair Approach
Ariel Jaffe · Roi Weiss · Boaz Nadler · Shai Carmi · Yuval Kluger
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #57
Thompson Sampling for Combinatorial Semi-Bandits
Siwei Wang · Wei Chen
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #58
Let’s be Honest: An Optimal No-Regret Framework for Zero-Sum Games
Ehsan Asadi Kangarshahi · Ya-Ping Hsieh · Mehmet Fatih Sahin · Volkan Cevher
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #59
Deep Asymmetric Multi-task Feature Learning
Hae Beom Lee · Eunho Yang · Sung Ju Hwang
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #60
Learn from Your Neighbor: Learning Multi-modal Mappings from Sparse Annotations
Ashwin Kalyan · Stefan Lee · Anitha Kannan · Dhruv Batra
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #61
Stein Variational Message Passing for Continuous Graphical Models
Dilin Wang · Zhe Zeng · Qiang Liu
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #62
Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms
Yi Wu · Siddharth Srivastava · Nicholas Hay · Simon Du · Stuart Russell
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #63
Towards Binary-Valued Gates for Robust LSTM Training
Zhuohan Li · Di He · Fei Tian · Wei Chen · Tao Qin · Liwei Wang · Tie-Yan Liu
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #64
Fitting New Speakers Based on a Short Untranscribed Sample
Eliya Nachmani · Adam Polyak · Yaniv Taigman · Lior Wolf
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #65
Stochastic Variance-Reduced Policy Gradient
Matteo Papini · Damiano Binaghi · Giuseppe Canonaco · Matteo Pirotta · Marcello Restelli
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #66
Convergent Tree Backup and Retrace with Function Approximation
Ahmed Touati · Pierre-Luc Bacon · Doina Precup · Pascal Vincent
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #67
Alternating Randomized Block Coordinate Descent
Jelena Diakonikolas · Orecchia Lorenzo
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #68
Shampoo: Preconditioned Stochastic Tensor Optimization
Vineet Gupta · Tomer Koren · Yoram Singer
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #69
Stochastic Wasserstein Barycenters
Sebastian Claici · Edward Chien · Justin Solomon
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #70
Accelerating Natural Gradient with Higher-Order Invariance
Yang Song · Jiaming Song · Stefano Ermon
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #71
Learning unknown ODE models with Gaussian processes
Markus Heinonen · Cagatay Yildiz · Henrik Mannerström · Jukka Intosalmi · Harri Lähdesmäki
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #72
Constraining the Dynamics of Deep Probabilistic Models
Marco Lorenzi · Maurizio Filippone
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #73
Fast Decoding in Sequence Models Using Discrete Latent Variables
Lukasz Kaiser · Samy Bengio · Aurko Roy · Ashish Vaswani · Niki Parmar · Jakob Uszkoreit · Noam Shazeer
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #74
High Performance Zero-Memory Overhead Direct Convolutions
Jiyuan Zhang · Franz Franchetti · Tze Meng Low
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #75
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions
Shuaiwen Wang · Wenda Zhou · Haihao Lu · Arian Maleki · Vahab Mirrokni
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #76
Improved large-scale graph learning through ridge spectral sparsification
Daniele Calandriello · Alessandro Lazaric · Ioannis Koutis · Michal Valko
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #77
Distilling the Posterior in Bayesian Neural Networks
Kuan-Chieh Wang · Paul Vicol · James Lucas · Li Gu · Roger Grosse · Richard Zemel
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #78
Scalable approximate Bayesian inference for particle tracking data
Ruoxi Sun · Department of Statistics Liam Paninski
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #79
Weakly Consistent Optimal Pricing Algorithms in Repeated Posted-Price Auctions with Strategic Buyer
Alexey Drutsa
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #80
Practical Contextual Bandits with Regression Oracles
Dylan Foster · Alekh Agarwal · Miroslav Dudik · Haipeng Luo · Robert Schapire
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #81
Stochastic Variance-Reduced Hamilton Monte Carlo Methods
Difan Zou · Pan Xu · Quanquan Gu
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #82
Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization
Umut Simsekli · Cagatay Yildiz · Thanh Huy Nguyen · Ali Taylan Cemgil · Gaël RICHARD
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #83
GAIN: Missing Data Imputation using Generative Adversarial Nets
Jinsung Yoon · James Jordon · Mihaela van der Schaar
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #84
Synthesizing Programs for Images using Reinforced Adversarial Learning
Iaroslav Ganin · Tejas Kulkarni · Igor Babuschkin · S. M. Ali Eslami · Oriol Vinyals
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #85
Geometry Score: A Method For Comparing Generative Adversarial Networks
Valentin Khrulkov · Ivan Oseledets
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #86
Addressing Function Approximation Error in Actor-Critic Methods
Scott Fujimoto · Herke van Hoof · David Meger
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #87
Fast Bellman Updates for Robust MDPs
Chin Pang Ho · Marek Petrik · Wolfram Wiesemann
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #88
Configurable Markov Decision Processes
Alberto Maria Metelli · Mirco Mutti · Marcello Restelli
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #89
Prediction Rule Reshaping
Matt Bonakdarpour · Sabyasachi Chatterjee · Rina Barber · John Lafferty
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #90
Dimensionality-Driven Learning with Noisy Labels
Xingjun Ma · Yisen Wang · Michael E. Houle · Shuo Zhou · Sarah Erfani · Shutao Xia · Sudanthi Wijewickrema · James Bailey
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #91
Learning Memory Access Patterns
Milad Hashemi · Kevin Swersky · Jamie Smith · Grant Ayers · Heiner Litz · Jichuan Chang · Christos Kozyrakis · Parthasarathy Ranganathan
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #92
Geodesic Convolutional Shape Optimization
Pierre Baque · Edoardo Remelli · Francois Fleuret · EPFL Pascal Fua
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #93
Visualizing and Understanding Atari Agents
Samuel Greydanus · Anurag Koul · Jonathan Dodge · Alan Fern
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #94
An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning
Dhruv Malik · Malayandi Palaniappan · Jaime Fisac · Dylan Hadfield-Menell · Stuart Russell · Anca Dragan
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #95
Is Generator Conditioning Causally Related to GAN Performance?
Augustus Odena · Jacob Buckman · Catherine Olsson · Tom B Brown · Christopher Olah · Colin Raffel · Ian Goodfellow
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #96
K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning
Jihun Hamm · Yung-Kyun Noh
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #97
Inductive Two-Layer Modeling with Parametric Bregman Transfer
Vignesh Ganapathiraman · Zhan Shi · Xinhua Zhang · Yaoliang Yu
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #98
Does Distributionally Robust Supervised Learning Give Robust Classifiers?
Weihua Hu · Gang Niu · Issei Sato · Masashi Sugiyama
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #99
Understanding Generalization and Optimization Performance of Deep CNNs
Pan Zhou · Jiashi Feng
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #100
The Multilinear Structure of ReLU Networks
Thomas Laurent · James von Brecht
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #101
Parallel and Streaming Algorithms for K-Core Decomposition
Hossein Esfandiari · Silvio Lattanzi · Vahab Mirrokni
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #102
Fast Approximate Spectral Clustering for Dynamic Networks
Lionel Martin · Andreas Loukas · Pierre Vandergheynst
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #103
Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima
Simon Du · Jason Lee · Yuandong Tian · Aarti Singh · Barnabás Póczos
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #104
Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions
Quynh Nguyen · Mahesh Mukkamala · Matthias Hein
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #105
Greed is Still Good: Maximizing Monotone Submodular+Supermodular (BP) Functions
Wenruo Bai · Jeff Bilmes
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #106
Black-box Adversarial Attacks with Limited Queries and Information
Andrew Ilyas · Logan Engstrom · Anish Athalye · Jessy Lin
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #107
Using Inherent Structures to design Lean 2-layer RBMs
Abhishek Bansal · Abhinav Anand · Chiranjib Bhattacharyya
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #108
Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care
Patrick Schwab · Emanuela Keller · Carl Muroi · David J. Mack · Christian Strässle · Walter Karlen
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #109
Composable Planning with Attributes
Amy Zhang · Sainbayar Sukhbaatar · Adam Lerer · Arthur Szlam · Facebook Rob Fergus
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #110
Measuring abstract reasoning in neural networks
Adam Santoro · Feilx Hill · David GT Barrett · Ari S Morcos · Timothy Lillicrap
[ PDF [ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #111
Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity
Lin Chen · Christopher Harshaw · Hamed Hassani · Amin Karbasi
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #112
Self-Bounded Prediction Suffix Tree via Approximate String Matching
Dongwoo Kim · Christian Walder
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #113
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels
Lu Jiang · Zhengyuan Zhou · Thomas Leung · Li-Jia Li · Li Fei-Fei
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #114
Curriculum Learning by Transfer Learning: Theory and Experiments with Deep Networks
Daphna Weinshall · Gad A Cohen · Dan Amir
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #115
Composite Functional Gradient Learning of Generative Adversarial Models
Rie Johnson · Tong Zhang
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #116
LaVAN: Localized and Visible Adversarial Noise
Danny Karmon · Daniel Zoran · Yoav Goldberg
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #117
Approximation Guarantees for Adaptive Sampling
Eric Balkanski · Yaron Singer
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #118
Constrained Interacting Submodular Groupings
Andrew Cotter · Mahdi Milani Fard · Seungil You · Maya Gupta · Jeff Bilmes
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #119
Residual Unfairness in Fair Machine Learning from Prejudiced Data
Nathan Kallus · Angela Zhou
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #120
Adversarial Regression with Multiple Learners
Liang Tong · Sixie Yu · Scott Alfeld · Yevgeniy Vorobeychik
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #121
Representation Tradeoffs for Hyperbolic Embeddings
Frederic Sala · Christopher De Sa · Albert Gu · Christopher Re
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #122
Improving Sign Random Projections With Additional Information
Keegan Kang · Wei Pin Wong
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #123
Bandits with Delayed, Aggregated Anonymous Feedback
Ciara Pike-Burke · Shipra Agrawal · Csaba Szepesvari · Steffen Grünewälder
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #124
Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits
Zeyuan Allen-Zhu · Sebastien Bubeck · Yuanzhi Li
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #125
Learning Policy Representations in Multiagent Systems
Aditya Grover · Maruan Al-Shedivat · Jayesh K. Gupta · Yura Burda · Harrison Edwards
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #126
Learning to Coordinate with Coordination Graphs in Repeated Single-Stage Multi-Agent Decision Problems
Eugenio Bargiacchi · Timothy Verstraeten · Diederik Roijers · Ann Nowé · Hado van Hasselt
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #127
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations
Yiping Lu · Aoxiao Zhong · Quanzheng Li · Bin Dong
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #128
Compressing Neural Networks using the Variational Information Bottelneck
Bin Dai · Chen Zhu · Baining Guo · David Wipf
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #129
Scalable Bilinear Pi Learning Using State and Action Features
Yichen Chen · Lihong Li · Mengdi Wang
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #130
Time Limits in Reinforcement Learning
Fabio Pardo · Arash Tavakoli · Vitaly Levdik · Petar Kormushev
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #131
Semi-Supervised Learning on Data Streams via Temporal Label Propagation
Tal Wagner · Sudipto Guha · Shiva Kasiviswanathan · Nina Mishra
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #132
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion
Cong Ma · Kaizheng Wang · Yuejie Chi · Yuxin Chen
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #133
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models
Beilun Wang · Arshdeep Sekhon · Yanjun Qi
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #134
Bucket Renormalization for Approximate Inference
Sungsoo Ahn · Michael Chertkov · Adrian Weller · Jinwoo Shin
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #135
Kernel Recursive ABC: Point Estimation with Intractable Likelihood
Takafumi Kajihara · Motonobu Kanagawa · Keisuke Yamazaki · Kenji Fukumizu
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #136
Modeling Others using Oneself in Multi-Agent Reinforcement Learning
Roberta Raileanu · Emily Denton · Arthur Szlam · Facebook Rob Fergus
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #137
Tropical Geometry of Deep Neural Networks
Liwen Zhang · Gregory Naisat · Lek-Heng Lim
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #138
Learning Dynamics of Linear Denoising Autoencoders
Arnu Pretorius · Steve Kroon · Herman Kamper
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #139
Nonparametric variable importance using an augmented neural network with multi-task learning
Jean Feng · Brian Williamson · Noah Simon · Marco Carone
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #140
Training Neural Machines with Trace-Based Supervision
Matthew Mirman · Dimitar Dimitrov · Pavle Djordjevic · Timon Gehr · Martin Vechev
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #141
Open Category Detection with PAC Guarantees
Si Liu · Risheek Garrepalli · Thomas Dietterich · Alan Fern · Dan Hendrycks
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #142
SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate
Aaditya Ramdas · Tijana Zrnic · Martin Wainwright · Michael Jordan
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #143
Learning Localized Spatio-Temporal Models From Streaming Data
Muhammad Osama · Dave Zachariah · Thomas Schön
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #144
Feasible Arm Identification
Julian Katz-Samuels · Clay Scott
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #145
Fast Maximization of Non-Submodular, Monotonic Functions on the Integer Lattice
Alan Kuhnle · J. Smith · Victoria Crawford · My T. Thai
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #146
Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings
Aryan Mokhtari · Hamed Hassani · Amin Karbasi
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #147
Towards Fast Computation of Certified Robustness for ReLU Networks
Tsui-Wei Weng · Huan Zhang · Hongge Chen · Zhao Song · Cho-Jui Hsieh · Luca Daniel · Duane Boning · Inderjit Dhillon
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #148
A Two-Step Computation of the Exact GAN Wasserstein Distance
Huidong Liu · Xianfeng GU · Samaras Dimitris
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #149
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection
Jeremias Knoblauch · Theodoros Damoulas
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #150
Fast Stochastic AUC Maximization with $O(1/n)$-Convergence Rate
Mingrui Liu · Xiaoxuan Zhang · Zaiyi Chen · Xiaoyu Wang · Tianbao Yang
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #151
Accurate Uncertainties for Deep Learning Using Calibrated Regression
Volodymyr Kuleshov · Nathan Fenner · Stefano Ermon
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #152
Neural Autoregressive Flows
Chin-Wei Huang · David Krueger · Alexandre Lacoste · Aaron Courville
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #153
Probabilistic Boolean Tensor Decomposition
Tammo Rukat · Christopher Holmes · Christopher Yau
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #154
A Primal-Dual Analysis of Global Optimality in Nonconvex Low-Rank Matrix Recovery
Xiao Zhang · Lingxiao Wang · Yaodong Yu · Quanquan Gu
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #155
A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning
Konstantin Mishchenko · Franck Iutzeler · Jérôme Malick · Massih-Reza Amini
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #156
Randomized Block Cubic Newton Method
Nikita Doikov · Peter Richtarik
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #157
Massively Parallel Algorithms and Hardness for Single-Linkage Clustering under $\ell_p$ Distances
Grigory Yaroslavtsev · Adithya Vadapalli
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #158
Local Density Estimation in High Dimensions
Xian Wu · Moses Charikar · Vishnu Natchu
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #159
To Understand Deep Learning We Need to Understand Kernel Learning
Mikhail Belkin · Siyuan Ma · Soumik Mandal
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #160
Learning in Reproducing Kernel Kreı̆n Spaces
Dino Oglic · Thomas Gaertner
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #161
Functional Gradient Boosting based on Residual Network Perception
Atsushi Nitanda · Taiji Suzuki
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #162
Binary Classification with Karmic, Threshold-Quasi-Concave Metrics
Bowei Yan · Sanmi Koyejo · Kai Zhong · Pradeep Ravikumar
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #163
Characterizing Implicit Bias in Terms of Optimization Geometry
Suriya Gunasekar · Jason Lee · Daniel Soudry · Nati Srebro
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #164
prDeep: Robust Phase Retrieval with a Flexible Deep Network
Christopher Metzler · Phillip Schniter · Ashok Veeraraghavan · Richard Baraniuk
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #165
Adversarial Time-to-Event Modeling
Paidamoyo Chapfuwa · Chenyang Tao · Chunyuan Li · Courtney Page · Benjamin Goldstein · Lawrence Carin · Ricardo Henao
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #166
MAGAN: Aligning Biological Manifolds
Matt Amodio · Smita Krishnaswamy
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #167
Multicalibration: Calibration for the (Computationally-Identifiable) Masses
Ursula Hebert-Johnson · Michael Kim · Omer Reingold · Guy Rothblum
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #168
Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms
Xueru Zhang · Mohammad Mahdi Khalili · Mingyan Liu
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #169
PixelSNAIL: An Improved Autoregressive Generative Model
Xi Chen · Nikhil Mishra · Mostafa Rohaninejad · Pieter Abbeel
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #170
Focused Hierarchical RNNs for Conditional Sequence Processing
Rosemary Nan Ke · Konrad Zolna · Alessandro Sordoni · Zhouhan Lin · Adam Trischler · Yoshua Bengio · Joelle Pineau · Laurent Charlin · Christopher Pal
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #171
Noise2Noise: Learning Image Restoration without Clean Data
Jaakko Lehtinen · Jacob Munkberg · Jon Hasselgren · Samuli Laine · Tero Karras · Miika Aittala · Timo Aila
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #172
Learning to Reweight Examples for Robust Deep Learning
Mengye Ren · Wenyuan Zeng · Bin Yang · Raquel Urtasun
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #173
Policy and Value Transfer in Lifelong Reinforcement Learning
David Abel · Yuu Jinnai · Sophie Guo · George Konidaris · Michael L. Littman
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #174
GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms
Cédric Colas · Olivier Sigaud · Pierre-Yves Oudeyer
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #175
A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music
Adam Roberts · Jesse Engel · Colin Raffel · Curtis Hawthorne · Douglas Eck
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #176
Understanding the Loss Surface of Neural Networks for Binary Classification
SHIYU LIANG · Ruoyu Sun · Yixuan Li · R Srikant
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #177
Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks
Minmin Chen · Jeffrey Pennington · Samuel Schoenholz
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #178
Reviving and Improving Recurrent Back-Propagation
Renjie Liao · Yuwen Xiong · Ethan Fetaya · Lisa Zhang · KiJung Yoon · Zachary S Pitkow · Raquel Urtasun · Richard Zemel
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #179
Riemannian Stochastic Recursive Gradient Algorithm with Retraction and Vector Transport and Its Convergence Analysis
Hiroyuki Kasai · Hiroyuki Sato · Bamdev Mishra
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #180
Learning Compact Neural Networks with Regularization
Samet Oymak
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #181
Investigating Human Priors for Playing Video Games
Rachit Dubey · Pulkit Agrawal · Deepak Pathak · Tom Griffiths · Alexei Efros
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #182
Decoupling Gradient-Like Learning Rules from Representations
Philip Thomas · Christoph Dann · Emma Brunskill
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #183
Invariance of Weight Distributions in Rectified MLPs
Susumu Tsuchida · Fred Roosta · Marcus Gallagher
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #184
Stronger Generalization Bounds for Deep Nets via a Compression Approach
Sanjeev Arora · Rong Ge · Behnam Neyshabur · Yi Zhang
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #185
Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices
Zengfeng Huang
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #186
Loss Decomposition for Fast Learning in Large Output Spaces
En-Hsu Yen · Satyen Kale · Felix Xinnan Yu · Daniel Holtmann-Rice · Sanjiv Kumar · Pradeep Ravikumar
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #187
Stochastic Proximal Algorithms for AUC Maximization
Michael Natole Jr · Yiming Ying · Siwei Lyu
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #188
Accelerated Spectral Ranking
Arpit Agarwal · Prathamesh Patil · Shivani Agarwal
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #189
Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning
Stefan Depeweg · Jose Miguel Hernandez-Lobato · Finale Doshi-Velez · Steffen Udluft
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #190
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Mohammad Emtiyaz Khan · Didrik Nielsen · Voot Tangkaratt · Wu Lin · Yarin Gal · Akash Srivastava
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #191
Learning One Convolutional Layer with Overlapping Patches
Surbhi Goel · Adam Klivans · Raghu Meka
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #192
A Spline Theory of Deep Learning
Randall Balestriero · Richard Baraniuk
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #193
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors
Soumya Ghosh · Jiayu Yao · Finale Doshi-Velez
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #194
Variational Bayesian dropout: pitfalls and fixes
Jiri Hron · Alexander Matthews · Zoubin Ghahramani
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #195
Adversarial Learning with Local Coordinate Coding
Jiezhang Cao · Yong Guo · Qingyao Wu · Chunhua Shen · Junzhou Huang · Mingkui Tan
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #196
Learning Representations and Generative Models for 3D Point Clouds
Panagiotis Achlioptas · Olga Diamanti · Ioannis Mitliagkas · Leonidas Guibas
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #197
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks
Mattias Teye · Hossein Azizpour · Kevin Smith
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #198
Noisy Natural Gradient as Variational Inference
Guodong Zhang · Shengyang Sun · David Duvenaud · Roger Grosse
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #199
Deep Variational Reinforcement Learning for POMDPs
Maximilian Igl · Luisa Zintgraf · Tuan Anh Le · Frank Wood · Shimon Whiteson
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #200
Recurrent Predictive State Policy Networks
Ahmed Hefny · Zita Marinho · Wen Sun · Siddhartha Srinivasa · Geoff Gordon
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #201
The Mechanics of n-Player Differentiable Games
David Balduzzi · Sebastien Racaniere · James Martens · Jakob Foerster · Karl Tuyls · Thore Graepel
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #202
Improved Training of Generative Adversarial Networks Using Representative Features
Duhyeon Bang · Hyunjung Shim
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #203
Hierarchical Multi-Label Classification Networks
Jonatas Wehrmann · Ricardo Cerri · Rodrigo Barros
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #204
Knowledge Transfer with Jacobian Matching
Suraj Srinivas · Francois Fleuret
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #205
Towards Black-box Iterative Machine Teaching
Weiyang Liu · Bo Dai · Xingguo Li · Zhen Liu · James Rehg · Le Song
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #206
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising
Borja de Balle Pigem · Yu-Xiang Wang
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #207
Importance Weighted Transfer of Samples in Reinforcement Learning
Andrea Tirinzoni · Andrea Sessa · Matteo Pirotta · Marcello Restelli
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #208
Beyond the One-Step Greedy Approach in Reinforcement Learning
Yonathan Efroni · Gal Dalal · Bruno Scherrer · Shie Mannor
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #209
Optimization, fast and slow: optimally switching between local and Bayesian optimization
Mark McLeod · Stephen Roberts · Michael A Osborne
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #210
Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design
Wenlong Lyu · Fan Yang · Changhao Yan · Dian Zhou · Xuan Zeng
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #211
Graphical Nonconvex Optimization via an Adaptive Convex Relaxation
Qiang Sun · Kean Ming Tan · Han Liu · Tong Zhang
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #212
Approximate message passing for amplitude based optimization
Junjie Ma · Ji Xu · Arian Maleki
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #213
Delayed Impact of Fair Machine Learning
Lydia T. Liu · Sarah Dean · Esther Rolf · Max Simchowitz · Moritz Hardt
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #214
Tempered Adversarial Networks
Mehdi S. M. Sajjadi · Giambattista Parascandolo · Arash Mehrjou · Bernhard Schölkopf
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #215
Fast Information-theoretic Bayesian Optimisation
Binxin Ru · Michael A Osborne · Mark Mcleod · Diego Granziol
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #216
Tight Regret Bounds for Bayesian Optimization in One Dimension
Jonathan Scarlett
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #217
Image Transformer
Niki Parmar · Ashish Vaswani · Jakob Uszkoreit · Lukasz Kaiser · Noam Shazeer · Alexander Ku · Dustin Tran
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #218
Kernelized Synaptic Weight Matrices
Lorenz Müller · Julien Martel · Giacomo Indiveri
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #219
A Distributed Second-Order Algorithm You Can Trust
Celestine Mendler-Dünner · Aurelien Lucchi · Matilde Gargiani · Yatao Bian · Thomas Hofmann · Martin Jaggi
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #220
On Acceleration with Noise-Corrupted Gradients
Michael Cohen · Jelena Diakonikolas · Orecchia Lorenzo
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #221
Gradient Coding from Cyclic MDS Codes and Expander Graphs
Netanel Raviv · Rashish Tandon · Alexandros Dimakis · Itzhak Tamo
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #222
Accelerating Greedy Coordinate Descent Methods
Haihao Lu · Robert Freund · Vahab Mirrokni
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #223
Finding Influential Training Samples for Gradient Boosted Decision Trees
Boris Sharchilev · Yury Ustinovskiy · Pavel Serdyukov · Maarten de Rijke
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #224
Improving Regression Performance with Distributional Losses
Ehsan Imani · Martha White
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #225
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
Tabish Rashid · Mikayel Samvelyan · Christian Schroeder · Gregory Farquhar · Jakob Foerster · Shimon Whiteson
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #226
Learning to Act in Decentralized Partially Observable MDPs
Jilles Dibangoye · Olivier Buffet
[ PDF
Poster
Fri Jul 13 01:15 AM -- 04:00 AM (KST) @ Hall B #227
Local Convergence Properties of SAGA/Prox-SVRG and Acceleration
Clarice Poon · Jingwei Liang · Carola-Bibiane Schönlieb
[ PDF
Break
Fri Jul 13 02:30 AM -- 03:00 AM (KST) @ Hall B
Coffee Break
Break
Fri Jul 13 04:00 AM -- 05:30 AM (KST)
Lunch - on your own
Break
Fri Jul 13 07:30 AM -- 08:00 AM (KST) @ Hall B
Coffee Break
Break
Fri Jul 13 10:15 AM -- 11:15 AM (KST) @ Hall B
Light Evening Snack
Workshop
Fri Jul 13 03:30 PM -- 01:00 AM (KST) @ K23
31st International Workshop on Qualitative Reasoning (QR 2018)
Workshop
Fri Jul 13 03:30 PM -- 01:00 AM (KST) @ K24
6th Goal Reasoning Workshop
Workshop
Fri Jul 13 03:30 PM -- 01:00 AM (KST) @ T4
Computer Games Workshop
Workshop
Fri Jul 13 03:30 PM -- 01:00 AM (KST) @ K12
FCA4AI 2018
Workshop
Fri Jul 13 03:30 PM -- 01:00 AM (KST) @ B2
Joint Workshop on AI in Health (day 1)
Workshop
Fri Jul 13 03:30 PM -- 01:00 AM (KST) @ B9
Linguistic and Cognitive Approaches To Dialog Agents (LaCATODA 2018)
Workshop
Fri Jul 13 03:30 PM -- 07:30 PM (KST) @ K22
Tenth International Workshop Modelling and Reasoning in Context (MRC)
Workshop
Fri Jul 13 03:30 PM -- 01:00 AM (KST) @ B3
The 3rd International workshop on biomedical informatics with optimization and machine learning (BOOM)
Workshop
Fri Jul 13 03:30 PM -- 01:00 AM (KST) @ B5
The 3rd International Workshop on Knowledge Discovery in Healthcare Data
Workshop
Fri Jul 13 03:30 PM -- 01:00 AM (KST) @ T3
Towards learning with limited labels: Equivariance, Invariance, and Beyond
Workshop
Fri Jul 13 03:30 PM -- 01:00 AM (KST) @ K2
Fairness, Interpretability, and Explainability Federation of Workshops (day 1)
Workshop
Fri Jul 13 03:30 PM -- 01:00 AM (KST) @ K16
Autonomy in Teams -- Joint Workshop on Sharing Autonomy in Human-Robot Interaction
Session
Fri Jul 13 04:00 PM -- 04:20 PM (KST) @ A1
Test of Time Award
Oral
Fri Jul 13 04:30 PM -- 04:50 PM (KST) @ K11
Out-of-sample extension of graph adjacency spectral embedding
Keith Levin · Fred Roosta · Michael Mahoney · Carey Priebe
[ PDF [ Video
Oral
Fri Jul 13 04:30 PM -- 04:50 PM (KST) @ A7
Mixed batches and symmetric discriminators for GAN training
Thomas LUCAS · Corentin Tallec · Yann Ollivier · Jakob Verbeek
[ PDF [ Video
Oral
Fri Jul 13 04:30 PM -- 04:50 PM (KST) @ A3
Learning Registered Point Processes from Idiosyncratic Observations
Hongteng Xu · Lawrence Carin · Hongyuan Zha
[ PDF
Oral
Fri Jul 13 04:30 PM -- 04:50 PM (KST) @ A9
Convergence guarantees for a class of non-convex and non-smooth optimization problems
Koulik Khamaru · Martin Wainwright
[ PDF
Oral
Fri Jul 13 04:30 PM -- 04:50 PM (KST) @ K1
Solving Partial Assignment Problems using Random Clique Complexes
Charu Sharma · Deepak Nathani · Manu Kaul
[ PDF [ Video
Oral
Fri Jul 13 04:30 PM -- 04:50 PM (KST) @ Victoria
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
Been Kim · Martin Wattenberg · Justin Gilmer · Carrie Cai · James Wexler · Fernanda Viégas · Rory sayres
[ PDF
Oral
Fri Jul 13 04:30 PM -- 04:50 PM (KST) @ A1
RLlib: Abstractions for Distributed Reinforcement Learning
Eric Liang · Richard Liaw · Robert Nishihara · Philipp Moritz · Roy Fox · Ken Goldberg · Joseph E Gonzalez · Michael Jordan · Ion Stoica
[ PDF
Oral
Fri Jul 13 04:30 PM -- 04:50 PM (KST) @ A5
Dynamic Regret of Strongly Adaptive Methods
Lijun Zhang · Tianbao Yang · rong jin · Zhi-Hua Zhou
[ PDF [ Video
Oral
Fri Jul 13 04:30 PM -- 04:50 PM (KST) @ A6
A Reductions Approach to Fair Classification
Alekh Agarwal · Alina Beygelzimer · Miroslav Dudik · John Langford · Hanna Wallach
[ PDF [ Video
Oral
Fri Jul 13 04:30 PM -- 04:50 PM (KST) @ A4
Learning in Integer Latent Variable Models with Nested Automatic Differentiation
Daniel Sheldon · Kevin Winner · Debora Sujono
[ PDF
Oral
Fri Jul 13 04:50 PM -- 05:00 PM (KST) @ K1
Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction
Siyuan Qi · Baoxiong Jia · Song-Chun Zhu
[ PDF [ Video
Oral
Fri Jul 13 04:50 PM -- 05:10 PM (KST) @ A3
Deep Bayesian Nonparametric Tracking
Aonan Zhang · John Paisley
[ PDF
Oral
Fri Jul 13 04:50 PM -- 05:00 PM (KST) @ A7
Mutual Information Neural Estimation
Mohamed Belghazi · Aristide Baratin · Sai Rajeswar · Sherjil Ozair · Yoshua Bengio · R Devon Hjelm · Aaron Courville
[ PDF [ Video
Oral
Fri Jul 13 04:50 PM -- 05:00 PM (KST) @ A5
Online Learning with Abstention
Corinna Cortes · Giulia DeSalvo · Claudio Gentile · Mehryar Mohri · Scott Yang
[ PDF [ Video
Oral
Fri Jul 13 04:50 PM -- 05:00 PM (KST) @ A4
Sound Abstraction and Decomposition of Probabilistic Programs
Steven Holtzen · Guy Van den Broeck · Todd Millstein
[ PDF
Oral
Fri Jul 13 04:50 PM -- 05:00 PM (KST) @ Victoria
Learning equations for extrapolation and control
Subham S Sahoo · Christoph H. Lampert · Georg Martius
[ PDF
Oral
Fri Jul 13 04:50 PM -- 05:10 PM (KST) @ A9
A Progressive Batching L-BFGS Method for Machine Learning
Vijaya Raghavendra Bollapragada · Jorge Nocedal · Dheevatsa Mudigere · Hao-Jun M Shi · Peter Tang
[ PDF
Oral
Fri Jul 13 04:50 PM -- 05:10 PM (KST) @ 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
[ PDF
Oral
Fri Jul 13 04:50 PM -- 05:00 PM (KST) @ K11
Bayesian Model Selection for Change Point Detection and Clustering
othmane mazhar · Cristian R. Rojas · Inst. of Technology Carlo Fischione · Mohammad Reza Hesamzadeh
[ PDF [ Video
Oral
Fri Jul 13 04:50 PM -- 05:10 PM (KST) @ A6
Probably Approximately Metric-Fair Learning
Gal Yona · Guy Rothblum
[ PDF [ Video
Oral
Fri Jul 13 05:00 PM -- 05:10 PM (KST) @ K1
Video Prediction with Appearance and Motion Conditions
Yunseok Jang · Gunhee Kim · Yale Song
[ PDF [ Video
Oral
Fri Jul 13 05:00 PM -- 05:10 PM (KST) @ Victoria
PDE-Net: Learning PDEs from Data
Zichao Long · Yiping Lu · Xianzhong Ma · Bin Dong
[ PDF
Oral
Fri Jul 13 05:00 PM -- 05:10 PM (KST) @ A7
Adversarially Regularized Autoencoders
Jake Zhao · Yoon Kim · Kelly Zhang · Alexander Rush · Yann LeCun
[ PDF [ Video
Oral
Fri Jul 13 05:00 PM -- 05:10 PM (KST) @ K11
An Iterative, Sketching-based Framework for Ridge Regression
Agniva Chowdhury · Jiasen Yang · Petros Drineas
[ PDF [ Video
Oral
Fri Jul 13 05:00 PM -- 05:10 PM (KST) @ A5
Multi-Fidelity Black-Box Optimization with Hierarchical Partitions
Rajat Sen · kirthevasan kandasamy · Sanjay Shakkottai
[ PDF [ Video
Oral
Fri Jul 13 05:00 PM -- 05:10 PM (KST) @ A4
Parallel Bayesian Network Structure Learning
Tian Gao · Dennis Wei
[ PDF
Oral
Fri Jul 13 05:10 PM -- 05:20 PM (KST) @ K1
Neural Program Synthesis from Diverse Demonstration Videos
Shao-Hua Sun · Hyeonwoo Noh · Sriram Somasundaram · Joseph Lim
[ PDF [ Video
Oral
Fri Jul 13 05:10 PM -- 05:20 PM (KST) @ A5
Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits
Huasen Wu · Xueying Guo · Xin Liu
[ PDF [ Video
Oral
Fri Jul 13 05:10 PM -- 05:20 PM (KST) @ A4
The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference
Hao Lu · Yuan Cao · Junwei Lu · Han Liu · Zhaoran Wang
[ PDF
Oral
Fri Jul 13 05:10 PM -- 05:20 PM (KST) @ Victoria
Transformation Autoregressive Networks
Junier Oliva · Kumar Avinava Dubey · Manzil Zaheer · Barnabás Póczos · Ruslan Salakhutdinov · Eric Xing · Jeff Schneider
[ PDF
Oral
Fri Jul 13 05:10 PM -- 05:20 PM (KST) @ A9
Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solution for Nonconvex Distributed Optimization Over Networks
Mingyi Hong · Meisam Razaviyayn · Jason Lee
[ PDF
Oral
Fri Jul 13 05:10 PM -- 05:20 PM (KST) @ A3
Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling
Kejun Huang · Xiao Fu · Nicholas Sidiropoulos
[ PDF
Oral
Fri Jul 13 05:10 PM -- 05:20 PM (KST) @ A1
Mix & Match - Agent Curricula for Reinforcement Learning
Wojciech Czarnecki · Siddhant Jayakumar · Max Jaderberg · Leonard Hasenclever · Yee Teh · Nicolas Heess · Simon Osindero · Razvan Pascanu
[ PDF
Oral
Fri Jul 13 05:10 PM -- 05:20 PM (KST) @ 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
[ PDF [ Video
Oral
Fri Jul 13 05:10 PM -- 05:20 PM (KST) @ A6
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
Michael Kearns · Seth Neel · Aaron Roth · Steven Wu
[ PDF
Oral
Fri Jul 13 05:10 PM -- 05:20 PM (KST) @ K11
Provable Variable Selection for Streaming Features
Jing Wang · Jie Shen · Ping Li
[ PDF [ Video
Oral
Fri Jul 13 05:20 PM -- 05:30 PM (KST) @ A9
Estimation of Markov Chain via Rank-constrained Likelihood
XUDONG LI · Mengdi Wang · Anru Zhang
[ PDF
Oral
Fri Jul 13 05:20 PM -- 05:30 PM (KST) @ A6
Blind Justice: Fairness with Encrypted Sensitive Attributes
Niki Kilbertus · Adria Gascon · Matt Kusner · Michael Veale · Krishna Gummadi · Adrian Weller
[ PDF [ Video
Oral
Fri Jul 13 05:20 PM -- 05:30 PM (KST) @ K11
Learning Low-Dimensional Temporal Representations
Bing Su · Ying Wu
[ PDF [ Video
Oral
Fri Jul 13 05:20 PM -- 05:30 PM (KST) @ A4
Temporal Poisson Square Root Graphical Models
Sinong Geng · Zhaobin Kuang · Peggy Peissig · University of Wisconsin David Page
[ PDF
Oral
Fri Jul 13 05:20 PM -- 05:30 PM (KST) @ A5
Firing Bandits: Optimizing Crowdfunding
Lalit Jain · Kevin Jamieson
[ PDF [ Video
Oral
Fri Jul 13 05:20 PM -- 05:30 PM (KST) @ 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
[ PDF
Oral
Fri Jul 13 05:20 PM -- 05:30 PM (KST) @ A1
Learning to Explore via Meta-Policy Gradient
Tianbing Xu · Qiang Liu · Liang Zhao · Jian Peng
[ PDF
Oral
Fri Jul 13 05:20 PM -- 05:30 PM (KST) @ A7
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data
Amjad Almahairi · Sai Rajeswar · Alessandro Sordoni · Philip Bachman · Aaron Courville
[ PDF [ Video
Oral
Fri Jul 13 06:00 PM -- 06:20 PM (KST) @ A6
Theoretical Analysis of Sparse Subspace Clustering with Missing Entries
Manolis Tsakiris · Rene Vidal
[ PDF [ Video
Oral
Fri Jul 13 06:00 PM -- 06:20 PM (KST) @ A7
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin · Regina Barzilay · Tommi Jaakkola
[ PDF [ Video
Oral
Fri Jul 13 06:00 PM -- 06:20 PM (KST) @ K1
Spurious Local Minima are Common in Two-Layer ReLU Neural Networks
Itay Safran · Ohad Shamir
[ PDF [ Video
Oral
Fri Jul 13 06:00 PM -- 06:20 PM (KST) @ A9
A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming
Alp Yurtsever · Olivier Fercoq · Francesco Locatello · Volkan Cevher
[ PDF
Oral
Fri Jul 13 06:00 PM -- 06:20 PM (KST) @ 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
[ PDF
Oral
Fri Jul 13 06:00 PM -- 06:20 PM (KST) @ A1
Hierarchical Imitation and Reinforcement Learning
Hoang Le · Nan Jiang · Alekh Agarwal · Miroslav Dudik · Yisong Yue · Hal Daumé III
[ PDF
Oral
Fri Jul 13 06:00 PM -- 06:20 PM (KST) @ A4
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)
Trefor Evans · Prasanth B Nair
[ PDF
Oral
Fri Jul 13 06:00 PM -- 06:20 PM (KST) @ A5
Online Linear Quadratic Control
Alon Cohen · Avinatan Hasidim · Tomer Koren · Nevena Lazic · Yishay Mansour · Kunal Talwar
[ PDF
Oral
Fri Jul 13 06:00 PM -- 06:20 PM (KST) @ K11
Competitive Caching with Machine Learned Advice
Thodoris Lykouris · Sergei Vassilvitskii
[ PDF [ Video
Oral
Fri Jul 13 06:00 PM -- 06:20 PM (KST) @ A3
Learning Adversarially Fair and Transferable Representations
David Madras · Elliot Creager · Toniann Pitassi · Richard Zemel
[ PDF
Oral
Fri Jul 13 06:20 PM -- 06:40 PM (KST) @ A7
Semi-Amortized Variational Autoencoders
Yoon Kim · Sam Wiseman · Andrew Miller · David Sontag · Alexander Rush
[ PDF [ Video
Oral
Fri Jul 13 06:20 PM -- 06:30 PM (KST) @ K11
Distributed Clustering via LSH Based Data Partitioning
Aditya Bhaskara · Pruthuvi Maheshakya Wijewardena
[ PDF [ Video
Oral
Fri Jul 13 06:20 PM -- 06:40 PM (KST) @ 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
[ PDF
Oral
Fri Jul 13 06:20 PM -- 06:30 PM (KST) @ A3
Learning Semantic Representations for Unsupervised Domain Adaptation
Shaoan Xie · Zibin Zheng · Liang Chen · Chuan Chen
[ PDF
Oral
Fri Jul 13 06:20 PM -- 06:40 PM (KST) @ K1
Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks
Peter Bartlett · Dave Helmbold · Phil Long
[ PDF [ Video
Oral
Fri Jul 13 06:20 PM -- 06:40 PM (KST) @ Victoria
Understanding and Simplifying One-Shot Architecture Search
Gabriel Bender · Pieter-Jan Kindermans · Barret Zoph · Vijay Vasudevan · Quoc Le
[ PDF
Oral
Fri Jul 13 06:20 PM -- 06:40 PM (KST) @ A9
Frank-Wolfe with Subsampling Oracle
Thomas Kerdreux · Fabian Pedregosa · Alexandre d'Aspremont
[ PDF
Oral
Fri Jul 13 06:20 PM -- 06:40 PM (KST) @ A4
State Space Gaussian Processes with Non-Gaussian Likelihood
Hannes Nickisch · Arno Solin · Alexander Grigorevskiy
[ PDF
Oral
Fri Jul 13 06:20 PM -- 06:40 PM (KST) @ A5
Semiparametric Contextual Bandits
Akshay Krishnamurthy · Steven Wu · Vasilis Syrgkanis
[ PDF
Oral
Fri Jul 13 06:20 PM -- 06:30 PM (KST) @ A6
Improved nearest neighbor search using auxiliary information and priority functions
Omid Keivani · Kaushik Sinha
[ PDF [ Video
Oral
Fri Jul 13 06:30 PM -- 06:40 PM (KST) @ K11
Learning to Branch
Nina Balcan · Travis Dick · Tuomas Sandholm · Ellen Vitercik
[ PDF [ Video
Oral
Fri Jul 13 06:30 PM -- 06:40 PM (KST) @ A6
QuantTree: Histograms for Change Detection in Multivariate Data Streams
Giacomo Boracchi · Diego Carrera · Cristiano Cervellera · Danilo Macciò
[ PDF [ Video
Oral
Fri Jul 13 06:30 PM -- 06:40 PM (KST) @ A3
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
Judy Hoffman · Eric Tzeng · Taesung Park · Jun-Yan Zhu · Philip Isola · Kate Saenko · Alexei Efros · Trevor Darrell
[ PDF
Oral
Fri Jul 13 06:40 PM -- 06:50 PM (KST) @ K11
Compiling Combinatorial Prediction Games
Frederic Koriche
[ PDF [ Video
Oral
Fri Jul 13 06:40 PM -- 06:50 PM (KST) @ A6
Topological mixture estimation
Steve Huntsman
[ PDF [ Video
Oral
Fri Jul 13 06:40 PM -- 06:50 PM (KST) @ A4
Constant-Time Predictive Distributions for Gaussian Processes
Geoff Pleiss · Jacob Gardner · Kilian Weinberger · Andrew Wilson
[ PDF
Oral
Fri Jul 13 06:40 PM -- 06:50 PM (KST) @ K1
On the Power of Over-parametrization in Neural Networks with Quadratic Activation
Simon Du · Jason Lee
[ PDF [ Video
Oral
Fri Jul 13 06:40 PM -- 06:50 PM (KST) @ Victoria
Path-Level Network Transformation for Efficient Architecture Search
Han Cai · Jiacheng Yang · Weinan Zhang · Song Han · Yong Yu
[ PDF
Oral
Fri Jul 13 06:40 PM -- 06:50 PM (KST) @ A3
Rectify Heterogeneous Models with Semantic Mapping
Han-Jia Ye · De-Chuan Zhan · Yuan Jiang · Zhi-Hua Zhou
[ PDF [ PDF
Oral
Fri Jul 13 06:40 PM -- 06:50 PM (KST) @ A9
On Matching Pursuit and Coordinate Descent
Francesco Locatello · Anant Raj · Sai Praneeth Reddy Karimireddy · Gunnar Ratsch · Bernhard Schölkopf · Sebastian Stich · Martin Jaggi
[ PDF
Oral
Fri Jul 13 06:40 PM -- 06:50 PM (KST) @ A1
State Abstractions for Lifelong Reinforcement Learning
David Abel · Dilip S. Arumugam · Lucas Lehnert · Michael L. Littman
[ PDF
Oral
Fri Jul 13 06:40 PM -- 06:50 PM (KST) @ A5
Minimax Concave Penalized Multi-Armed Bandit Model with High-Dimensional Covariates
xue wang · Mingcheng Wei · Tao Yao
[ PDF [ Video
Oral
Fri Jul 13 06:40 PM -- 06:50 PM (KST) @ A7
Iterative Amortized Inference
Joe Marino · Yisong Yue · Stephan Mandt
[ PDF [ Video
Oral
Fri Jul 13 06:50 PM -- 07:00 PM (KST) @ A1
Policy Optimization with Demonstrations
Bingyi Kang · Zequn Jie · Jiashi Feng
[ PDF
Oral
Fri Jul 13 06:50 PM -- 07:00 PM (KST) @ K11
Approximation Algorithms for Cascading Prediction Models
Matthew Streeter
[ PDF [ Video
Oral
Fri Jul 13 06:50 PM -- 07:00 PM (KST) @ A4
Large-Scale Cox Process Inference using Variational Fourier Features
ST John · James Hensman
[ PDF
Oral
Fri Jul 13 06:50 PM -- 07:00 PM (KST) @ A3
Detecting and Correcting for Label Shift with Black Box Predictors
Zachary Lipton · Yu-Xiang Wang · Alexander Smola
[ PDF
Oral
Fri Jul 13 06:50 PM -- 07:00 PM (KST) @ A5
Racing Thompson: an Efficient Algorithm for Thompson Sampling with Non-conjugate Priors
Yichi Zhou · Jun Zhu · Jingwei Zhuo
[ PDF
Oral
Fri Jul 13 06:50 PM -- 07:00 PM (KST) @ A9
Adaptive Three Operator Splitting
Fabian Pedregosa · Gauthier Gidel
[ PDF
Oral
Fri Jul 13 06:50 PM -- 07:00 PM (KST) @ A7
DVAE++: Discrete Variational Autoencoders with Overlapping Transformations
Arash Vahdat · William Macready · Zhengbing Bian · Amir Khoshaman · Evgeny Andriyash
[ PDF [ Video
Oral
Fri Jul 13 06:50 PM -- 07:00 PM (KST) @ A6
Revealing Common Statistical Behaviors in Heterogeneous Populations
Andrey Zhitnikov · Rotem Mulayoff · Tomer Michaeli
[ PDF [ Video
Oral
Fri Jul 13 06:50 PM -- 07:00 PM (KST) @ K1
Optimization Landscape and Expressivity of Deep CNNs
Quynh Nguyen · Matthias Hein
[ PDF [ Video
Oral
Fri Jul 13 06:50 PM -- 07:00 PM (KST) @ Victoria
Learning Longer-term Dependencies in RNNs with Auxiliary Losses
Trieu H Trinh · Andrew Dai · Thang Luong · Quoc Le
[ PDF
Invited Talk
Fri Jul 13 08:30 PM -- 09:30 PM (KST) @ A1
Language to Action: towards Interactive Task Learning with Physical Agents
Joyce Chai
Workshop
Fri Jul 13 09:00 PM -- 01:00 AM (KST) @ K22
Learning and Reasoning: Principles & Applications to Everyday Spatial and Temporal Knowledge (day 1)
Invited Talk
Fri Jul 13 09:30 PM -- 10:30 PM (KST) @ A1
Building Machines that Learn and Think Like People
Josh Tenenbaum
Oral
Fri Jul 13 11:00 PM -- 11:20 PM (KST) @ K1
Efficient end-to-end learning for quantizable representations
Yeonwoo Jeong · Hyun Oh Song
[ PDF [ Video
Oral
Fri Jul 13 11:00 PM -- 11:20 PM (KST) @ Victoria
Progress & Compress: A scalable framework for continual learning
Jonathan Schwarz · Wojciech Czarnecki · Jelena Luketina · Agnieszka Grabska-Barwinska · Yee Teh · Razvan Pascanu · Raia Hadsell
[ PDF
Oral
Fri Jul 13 11:00 PM -- 11:20 PM (KST) @ A9
SADAGRAD: Strongly Adaptive Stochastic Gradient Methods
Zaiyi Chen · Yi Xu · Enhong Chen · Tianbao Yang
[ PDF
Oral
Fri Jul 13 11:00 PM -- 11:20 PM (KST) @ K11
On the Spectrum of Random Features Maps of High Dimensional Data
Zhenyu Liao · Romain Couillet
[ PDF [ Video
Oral
Fri Jul 13 11:00 PM -- 11:20 PM (KST) @ A5
Causal Bandits with Propagating Inference
Akihiro Yabe · Daisuke Hatano · Hanna Sumita · Shinji Ito · Naonori Kakimura · Takuro Fukunaga · Ken-ichi Kawarabayashi
[ PDF
Oral
Fri Jul 13 11:00 PM -- 11:20 PM (KST) @ A4
Stein Variational Gradient Descent Without Gradient
Jun Han · Qiang Liu
[ PDF
Oral
Fri Jul 13 11:00 PM -- 11:20 PM (KST) @ A3
The Hidden Vulnerability of Distributed Learning in Byzantium
El Mahdi El Mhamdi · Rachid Guerraoui · Sébastien Rouault
[ PDF
Oral
Fri Jul 13 11:00 PM -- 11:20 PM (KST) @ A1
Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator
Maryam Fazel · Rong Ge · Sham Kakade · Mehran Mesbahi
[ PDF
Oral
Fri Jul 13 11:00 PM -- 11:20 PM (KST) @ A6
Candidates vs. Noises Estimation for Large Multi-Class Classification Problem
Lei Han · Yiheng Huang · Tong Zhang
[ PDF [ Video
Oral
Fri Jul 13 11:00 PM -- 11:20 PM (KST) @ 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
[ PDF [ Video
Oral
Fri Jul 13 11:20 PM -- 11:40 PM (KST) @ A3
Asynchronous Byzantine Machine Learning (the case of SGD)
Georgios Damaskinos · El Mahdi El Mhamdi · Rachid Guerraoui · Rhicheek Patra · Mahsa Taziki
[ PDF
Oral
Fri Jul 13 11:20 PM -- 11:40 PM (KST) @ A5
Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions
Karren Yang · Abigail Katoff · Caroline Uhler
[ PDF
Oral
Fri Jul 13 11:20 PM -- 11:30 PM (KST) @ K11
SMAC: Simultaneous Mapping and Clustering Using Spectral Decompositions
chandrajit bajaj · Tingran Gao · Zihang He · Qixing Huang · Zhenxiao Liang
[ PDF [ Video
Oral
Fri Jul 13 11:20 PM -- 11:40 PM (KST) @ A4
Minibatch Gibbs Sampling on Large Graphical Models
Christopher De Sa · Vincent Chen · Wong
[ PDF [ PDF
Oral
Fri Jul 13 11:20 PM -- 11:30 PM (KST) @ K1
High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach
Tim Pearce · Alexandra Brintrup · Mohamed Zaki · Andy Neely
[ PDF [ Video
Oral
Fri Jul 13 11:20 PM -- 11:30 PM (KST) @ A9
Level-Set Methods for Finite-Sum Constrained Convex Optimization
Qihang Lin · Runchao Ma · Tianbao Yang
[ PDF
Oral
Fri Jul 13 11:20 PM -- 11:40 PM (KST) @ Victoria
Overcoming Catastrophic Forgetting with Hard Attention to the Task
Joan Serrà · Didac Suris · Marius Miron · Alexandros Karatzoglou
[ PDF
Oral
Fri Jul 13 11:20 PM -- 11:30 PM (KST) @ A1
Policy Optimization as Wasserstein Gradient Flows
RUIYI (ROY) ZHANG · Changyou Chen · Chunyuan Li · Lawrence Carin
[ PDF
Oral
Fri Jul 13 11:20 PM -- 11:40 PM (KST) @ A7
Autoregressive Quantile Networks for Generative Modeling
Georg Ostrovski · Will Dabney · Remi Munos
[ PDF [ Video
Oral
Fri Jul 13 11:20 PM -- 11:30 PM (KST) @ A6
CRAFTML, an Efficient Clustering-based Random Forest for Extreme Multi-label Learning
Wissam Siblini · Frank Meyer · Pascale Kuntz
[ PDF [ Video
Oral
Fri Jul 13 11:30 PM -- 11:40 PM (KST) @ K11
Spectrally Approximating Large Graphs with Smaller Graphs
Andreas Loukas · Pierre Vandergheynst
[ PDF [ Video
Oral
Fri Jul 13 11:30 PM -- 11:40 PM (KST) @ A6
Attention-based Deep Multiple Instance Learning
Maximilian Ilse · Jakub Tomczak · Max Welling
[ PDF [ Video
Oral
Fri Jul 13 11:30 PM -- 11:40 PM (KST) @ K1
A Boo(n) for Evaluating Architecture Performance
Ondrej Bajgar · Rudolf Kadlec · Jan Kleindienst
[ PDF [ Video
Oral
Fri Jul 13 11:30 PM -- 11:40 PM (KST) @ A9
Local Convergence Properties of SAGA/Prox-SVRG and Acceleration
Clarice Poon · Jingwei Liang · Carola-Bibiane Schönlieb
[ PDF
Oral
Fri Jul 13 11:30 PM -- 11:40 PM (KST) @ A1
Clipped Action Policy Gradient
Yasuhiro Fujita · Shin-ichi Maeda
[ PDF
Oral
Fri Jul 13 11:40 PM -- 11:50 PM (KST) @ A6
Learning and Memorization
Sat Chatterjee
[ PDF [ Video
Oral
Fri Jul 13 11:40 PM -- 11:50 PM (KST) @ A5
Budgeted Experiment Design for Causal Structure Learning
AmirEmad Ghassami · Saber Salehkaleybar · Negar Kiyavash · Elias Bareinboim
[ PDF
Oral
Fri Jul 13 11:40 PM -- 11:50 PM (KST) @ A7
Stochastic Video Generation with a Learned Prior
Emily Denton · Rob Fergus
[ PDF [ Video
Oral
Fri Jul 13 11:40 PM -- 11:50 PM (KST) @ A4
On Nesting Monte Carlo Estimators
Tom Rainforth · Rob Cornish · Hongseok Yang · andrew warrington · Frank Wood
[ PDF
Oral
Fri Jul 13 11:40 PM -- 11:50 PM (KST) @ A3
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients
Lingjiao Chen · Hongyi Wang · Zachary Charles · Dimitris Papailiopoulos
[ PDF
Oral
Fri Jul 13 11:40 PM -- 11:50 PM (KST) @ 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
[ PDF
Oral
Fri Jul 13 11:40 PM -- 11:50 PM (KST) @ Victoria
Rapid Adaptation with Conditionally Shifted Neurons
Tsendsuren Munkhdalai · Xingdi Yuan · Soroush Mehri · Adam Trischler
[ PDF
Oral
Fri Jul 13 11:40 PM -- 11:50 PM (KST) @ A9
Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions
Pan Xu · Tianhao Wang · Quanquan Gu
[ PDF
Oral
Fri Jul 13 11:40 PM -- 11:50 PM (KST) @ A1
Fourier Policy Gradients
Matthew Fellows · Kamil Ciosek · Shimon Whiteson
[ PDF
Oral
Fri Jul 13 11:40 PM -- 11:50 PM (KST) @ K11
Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering
Pan Li · Olgica Milenkovic
[ PDF [ Video
Oral
Fri Jul 13 11:50 PM -- 12:00 AM (KST) @ K11
Rates of Convergence of Spectral Methods for Graphon Estimation
Jiaming Xu
[ PDF [ Video
Oral
Fri Jul 13 11:50 PM -- 12:00 AM (KST) @ A5
The Hierarchical Adaptive Forgetting Variational Filter
Vincent Moens
[ PDF
Oral
Fri Jul 13 11:50 PM -- 12:00 AM (KST) @ A3
Communication-Computation Efficient Gradient Coding
Min Ye · Emmanuel Abbe
[ PDF
Oral
Fri Jul 13 11:50 PM -- 12:00 AM (KST) @ A9
Fast Gradient-Based Methods with Exponential Rate: A Hybrid Control Framework
Arman Sharifi Kolarijani · Peyman Mohajerin Esfahani · Tamas Keviczky
[ PDF
Oral
Fri Jul 13 11:50 PM -- 12:00 AM (KST) @ K1
On the Limitations of First-Order Approximation in GAN Dynamics
Jerry Li · Aleksander Madry · John Peebles · Ludwig Schmidt
[ PDF [ Video
Oral
Fri Jul 13 11:50 PM -- 12:00 AM (KST) @ Victoria
Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace
Yoonho Lee · Seungjin Choi
[ PDF
Oral
Fri Jul 13 11:50 PM -- 12:00 AM (KST) @ A7
Disentangled Sequential Autoencoder
Yingzhen Li · Stephan Mandt
[ PDF [ Video
Oral
Fri Jul 13 11:50 PM -- 12:00 AM (KST) @ A1
Self-Imitation Learning
Junhyuk Oh · Yijie Guo · Satinder Singh · Honglak Lee
[ PDF
Oral
Fri Jul 13 11:50 PM -- 12:00 AM (KST) @ A6
Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings
Aviral Kumar · Sunita Sarawagi · Ujjwal Jain
[ PDF [ Video
Oral
Fri Jul 13 11:50 PM -- 12:00 AM (KST) @ A4
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo
Niladri Chatterji · Nicolas Flammarion · Yian Ma · Peter Bartlett · Michael Jordan
[ PDF