Papers
The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions
Raj Agrawal, Brian Trippe, Jonathan Huggins et al.
The Natural Language of Actions
Guy Tennenholtz, Shie Mannor
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples
Kevin Roth, Yannic Kilcher, Thomas Hofmann
Theoretically Principled Trade-off between Robustness and Accuracy
Hongyang Zhang, Yaodong Yu, Jiantao Jiao et al.
The Value Function Polytope in Reinforcement Learning
Robert Dadashi, Adrien Ali Taiga, Nicolas Le Roux et al.
The Variational Predictive Natural Gradient
Da Tang, Rajesh Ranganath
The Wasserstein Transform
Facundo Memoli, Zane Smith, Zhengchao Wan
TibGM: A Transferable and Information-Based Graphical Model Approach for Reinforcement Learning
Tameem Adel, Adrian Weller
Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds
Andrea Zanette, Emma Brunskill
Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel $k$-means Clustering
Taisuke Yasuda, David Woodruff, Manuel Fernandez
Topological Data Analysis of Decision Boundaries with Application to Model Selection
Karthikeyan Natesan Ramamurthy, Kush Varshney, Krishnan Mody
Toward Controlling Discrimination in Online Ad Auctions
Elisa Celis, Anay Mehrotra, Nisheeth Vishnoi
Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation
Kaichao You, Ximei Wang, Mingsheng Long et al.
Towards a Deep and Unified Understanding of Deep Neural Models in NLP
Chaoyu Guan, Xiting Wang, Quanshi Zhang et al.
Towards a Unified Analysis of Random Fourier Features
Zhu Li, Jean-Francois Ton, Dino Oglic et al.
Towards Understanding Knowledge Distillation
Mary Phuong, Christoph Lampert
Toward Understanding the Importance of Noise in Training Neural Networks
Mo Zhou, Tianyi Liu, Yan Li et al.
Trading Redundancy for Communication: Speeding up Distributed SGD for Non-convex Optimization
Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi et al.
Traditional and Heavy Tailed Self Regularization in Neural Network Models
Michael Mahoney, Charles Martin
Trainable Decoding of Sets of Sequences for Neural Sequence Models
Ashwin Kalyan, Peter Anderson, Stefan Lee et al.
Training CNNs with Selective Allocation of Channels
Jongheon Jeong, Jinwoo Shin
Training Neural Networks with Local Error Signals
Arild Nøkland, Lars Hiller Eidnes
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints
Andrew Cotter, Maya Gupta, Heinrich Jiang et al.
Trajectory-Based Off-Policy Deep Reinforcement Learning
Andreas Doerr, Michael Volpp, Marc Toussaint et al.
Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation
Xinyang Chen, Sinan Wang, Mingsheng Long et al.