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Oral
Tue Dec 05 09:50 AM -- 10:10 AM (PST) @ Hall A
Test of Time Award
ali rahimi · Benjamin Recht
Oral
Tue Dec 05 10:40 AM -- 10:55 AM (PST) @ Hall A
Diffusion Approximations for Online Principal Component Estimation and Global Convergence
In Algorithms
Chris Junchi Li · Mengdi Wang · Tong Zhang
Oral
Tue Dec 05 10:40 AM -- 10:55 AM (PST) @ Hall C
On the Optimization Landscape of Tensor Decompositions
In Optimization
Rong Ge · Tengyu Ma
Oral
Tue Dec 05 10:55 AM -- 11:10 AM (PST) @ Hall A
Positive-Unlabeled Learning with Non-Negative Risk Estimator
In Algorithms
Ryuichi Kiryo · Gang Niu · Marthinus C du Plessis · Masashi Sugiyama
Oral
Tue Dec 05 10:55 AM -- 11:10 AM (PST) @ Hall C
Robust Optimization for Non-Convex Objectives
In Optimization
Robert S Chen · Brendan Lucier · Yaron Singer · Vasilis Syrgkanis
Oral
Tue Dec 05 11:10 AM -- 11:25 AM (PST) @ Hall A
Approximation Bounds for Hierarchical Clustering: Average Linkage, Bisecting K-means, and Local Search
In Algorithms
Benjamin Moseley · Joshua Wang
Oral
Tue Dec 05 11:10 AM -- 11:25 AM (PST) @ Hall C
Bayesian Optimization with Gradients
In Optimization
Jian Wu · Matthias Poloczek · Andrew Wilson · Peter Frazier
Oral
Tue Dec 05 02:50 PM -- 03:05 PM (PST) @ Hall A
Streaming Weak Submodularity: Interpreting Neural Networks on the Fly
In Algorithms, Optimization
Ethan Elenberg · Alex Dimakis · Moran Feldman · Amin Karbasi
Oral
Tue Dec 05 02:50 PM -- 03:05 PM (PST) @ Hall C
Safe and Nested Subgame Solving for Imperfect-Information Games
In Theory
Noam Brown · Tuomas Sandholm
Oral
Tue Dec 05 03:05 PM -- 03:20 PM (PST) @ Hall A
A unified approach to interpreting model predictions
In Algorithms, Optimization
Scott M Lundberg · Su-In Lee
Oral
Tue Dec 05 03:05 PM -- 03:20 PM (PST) @ Hall C
A graph-theoretic approach to multitasking
In Theory
Noga Alon · Daniel Reichman · Igor Shinkar · Tal Wagner · Sebastian Musslick · Jonathan D Cohen · Tom Griffiths · Biswadip dey · Kayhan Ozcimder
Oral
Tue Dec 05 04:20 PM -- 04:35 PM (PST) @ Hall A
Unsupervised learning of object frames by dense equivariant image labelling
In Deep Learning, Applications
James Thewlis · Hakan Bilen · Andrea Vedaldi
Oral
Tue Dec 05 04:20 PM -- 04:35 PM (PST) @ Hall C
A Linear-Time Kernel Goodness-of-Fit Test
In Algorithms
Wittawat Jitkrittum · Wenkai Xu · Zoltan Szabo · Kenji Fukumizu · Arthur Gretton
Oral
Tue Dec 05 04:35 PM -- 04:50 PM (PST) @ Hall A
Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts
In Deep Learning, Applications
Raymond A. Yeh · Jinjun Xiong · Wen-Mei Hwu · Minh Do · Alex Schwing
Oral
Tue Dec 05 04:35 PM -- 04:50 PM (PST) @ Hall C
Generalization Properties of Learning with Random Features
In Algorithms
Alessandro Rudi · Lorenzo Rosasco
Oral
Tue Dec 05 04:50 PM -- 05:05 PM (PST) @ Hall A
Eigen-Distortions of Hierarchical Representations
In Deep Learning, Applications
Alexander Berardino · Valero Laparra · Johannes Ballé · Eero Simoncelli
Oral
Tue Dec 05 04:50 PM -- 05:05 PM (PST) @ Hall C
Communication-Efficient Distributed Learning of Discrete Distributions
In Algorithms
Ilias Diakonikolas · Elena Grigorescu · Jerry Li · Abhiram Natarajan · Krzysztof Onak · Ludwig Schmidt
Oral
Wed Dec 06 10:20 AM -- 10:35 AM (PST) @ Hall A
On Structured Prediction Theory with Calibrated Convex Surrogate Losses
In Theory, Probabilistic Methods
Anton Osokin · Francis Bach · Simon Lacoste-Julien
Oral
Wed Dec 06 10:20 AM -- 10:35 AM (PST) @ Hall C
TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning
In Deep Learning
Wei Wen · Cong Xu · Feng Yan · Chunpeng Wu · Yandan Wang · Yiran Chen · Hai Li
Oral
Wed Dec 06 10:35 AM -- 10:50 AM (PST) @ Hall A
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
In Theory, Probabilistic Methods
George Tucker · Andriy Mnih · Chris J Maddison · John Lawson · Jascha Sohl-Dickstein
Oral
Wed Dec 06 10:35 AM -- 10:50 AM (PST) @ Hall C
Train longer, generalize better: closing the generalization gap in large batch training of neural networks
In Deep Learning
Elad Hoffer · Itay Hubara · Daniel Soudry
Oral
Wed Dec 06 10:50 AM -- 11:05 AM (PST) @ Hall A
Variance-based Regularization with Convex Objectives
In Theory, Probabilistic Methods
Hongseok Namkoong · John Duchi
Oral
Wed Dec 06 10:50 AM -- 11:05 AM (PST) @ Hall C
End-to-end Differentiable Proving
In Deep Learning
Tim Rocktäschel · Sebastian Riedel
Oral
Wed Dec 06 11:05 AM -- 11:20 AM (PST) @ Hall A
Online control of the false discovery rate with decaying memory
In Theory, Probabilistic Methods
Aaditya Ramdas · Fanny Yang · Martin Wainwright · Michael Jordan
Oral
Wed Dec 06 11:05 AM -- 11:20 AM (PST) @ Hall C
Gradient descent GAN optimization is locally stable
In Deep Learning
Vaishnavh Nagarajan · J. Zico Kolter
Oral
Wed Dec 06 02:50 PM -- 03:05 PM (PST) @ Hall A
ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games
In Reinforcement Learning, Deep Learning
Yuandong Tian · Qucheng Gong · Wendy Shang · Yuxin Wu · Larry Zitnick
Oral
Wed Dec 06 02:50 PM -- 03:05 PM (PST) @ Hall C
The Marginal Value of Adaptive Gradient Methods in Machine Learning
In Optimization
Ashia C Wilson · Becca Roelofs · Mitchell Stern · Nati Srebro · Benjamin Recht
Oral
Wed Dec 06 03:05 PM -- 03:20 PM (PST) @ Hall A
Imagination-Augmented Agents for Deep Reinforcement Learning
In Reinforcement Learning, Deep Learning
Sébastien Racanière · Theophane Weber · David Reichert · Lars Buesing · Arthur Guez · Danilo Jimenez Rezende · Adrià Puigdomènech Badia · Oriol Vinyals · Nicolas Heess · Yujia Li · Razvan Pascanu · Peter Battaglia · Demis Hassabis · David Silver · Daan Wierstra
Oral
Wed Dec 06 03:05 PM -- 03:20 PM (PST) @ Hall C
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent
In Optimization
Xiangru Lian · Ce Zhang · Huan Zhang · Cho-Jui Hsieh · Wei Zhang · Ji Liu
Oral
Wed Dec 06 04:20 PM -- 04:35 PM (PST) @ Hall A
Off-policy evaluation for slate recommendation
In Reinforcement Learning, Algorithms, Applications
Adith Swaminathan · Akshay Krishnamurthy · Alekh Agarwal · Miro Dudik · John Langford · Damien Jose · Imed Zitouni
Oral
Wed Dec 06 04:20 PM -- 04:35 PM (PST) @ Hall C
Reliable Decision Support using Counterfactual Models
In Probabilistic Methods, Applications
Peter Schulam · Suchi Saria
Oral
Wed Dec 06 04:35 PM -- 04:50 PM (PST) @ Hall A
Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes
In Reinforcement Learning, Algorithms, Applications
Taylor Killian · Samuel Daulton · Finale Doshi-Velez · George Konidaris
Oral
Wed Dec 06 04:35 PM -- 04:50 PM (PST) @ Hall C
Convolutional Gaussian Processes
In Probabilistic Methods, Applications
Mark van der Wilk · Carl Edward Rasmussen · James Hensman
Oral
Wed Dec 06 04:50 PM -- 05:05 PM (PST) @ Hall A
Inverse Reward Design
In Reinforcement Learning, Algorithms, Applications
Dylan Hadfield-Menell · Smitha Milli · Pieter Abbeel · Stuart J Russell · Anca Dragan
Oral
Wed Dec 06 04:50 PM -- 05:05 PM (PST) @ Hall C
Counterfactual Fairness
In Probabilistic Methods, Applications
Matt Kusner · Joshua Loftus · Chris Russell · Ricardo Silva
Oral
Thu Dec 07 11:10 AM -- 11:25 AM (PST) @ Hall A
Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System
In Neuroscience
Chengxu Zhuang · Jonas Kubilius · Mitra JZ Hartmann · Daniel Yamins
Oral
Thu Dec 07 11:10 AM -- 11:25 AM (PST) @ Hall C
Masked Autoregressive Flow for Density Estimation
In Deep Learning, Algorithms
George Papamakarios · Iain Murray · Theo Pavlakou
Oral
Thu Dec 07 11:25 AM -- 11:40 AM (PST) @ Hall A
Model-based Bayesian inference of neural activity and connectivity from all-optical interrogation of a neural circuit
In Neuroscience
Laurence Aitchison · Lloyd Russell · Adam Packer · Jinyao Yan · Philippe Castonguay · Michael Hausser · Srinivas C Turaga
Oral
Thu Dec 07 11:25 AM -- 11:40 AM (PST) @ Hall C
Deep Sets
In Deep Learning, Algorithms
Manzil Zaheer · Satwik Kottur · Siamak Ravanbakhsh · Barnabas Poczos · Ruslan Salakhutdinov · Alexander Smola
Oral
Thu Dec 07 11:40 AM -- 11:55 AM (PST) @ Hall A
Quantifying how much sensory information in a neural code is relevant for behavior
In Neuroscience
Giuseppe Pica · Eugenio Piasini · Houman Safaai · Caroline Runyan · Christopher Harvey · Mathew Diamond · Christoph Kayser · Tommaso Fellin · Stefano Panzeri
Oral
Thu Dec 07 11:40 AM -- 11:55 AM (PST) @ Hall C
From Bayesian Sparsity to Gated Recurrent Nets
In Deep Learning, Algorithms
Hao He · Bo Xin · Satoshi Ikehata · David Wipf