Papers
Teaching a black-box learner
Sanjoy Dasgupta, Daniel Hsu, Stefanos Poulis et al.
Temporal Gaussian Mixture Layer for Videos
Aj Piergiovanni, Michael Ryoo
TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing
Augustus Odena, Catherine Olsson, David Andersen et al.
Tensor Variable Elimination for Plated Factor Graphs
Fritz Obermeyer, Eli Bingham, Martin Jankowiak et al.
The advantages of multiple classes for reducing overfitting from test set reuse
Vitaly Feldman, Roy Frostig, Moritz Hardt
The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects
Zhanxing Zhu, Jingfeng Wu, Bing Yu et al.
The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study
Daniel Park, Jascha Sohl-Dickstein, Quoc Le et al.
The Evolved Transformer
David So, Quoc Le, Chen Liang
The Implicit Fairness Criterion of Unconstrained Learning
Lydia T. Liu, Max Simchowitz, Moritz Hardt
The information-theoretic value of unlabeled data in semi-supervised learning
Alexander Golovnev, David Pal, Balazs Szorenyi
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.