Papers
Submodular Maximization beyond Non-negativity: Guarantees, Fast Algorithms, and Applications
Chris Harshaw, Moran Feldman, Justin Ward et al.
Submodular Observation Selection and Information Gathering for Quadratic Models
Abolfazl Hashemi, Mahsa Ghasemi, Haris Vikalo et al.
Submodular Streaming in All Its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity
Ehsan Kazemi, Marko Mitrovic, Morteza Zadimoghaddam et al.
Subspace Robust Wasserstein Distances
François-Pierre Paty, Marco Cuturi
Sum-of-Squares Polynomial Flow
Priyank Jaini, Kira A. Selby, Yaoliang Yu
Supervised Hierarchical Clustering with Exponential Linkage
Nishant Yadav, Ari Kobren, Nicholas Monath et al.
Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization
Zhenxun Zhuang, Ashok Cutkosky, Francesco Orabona
SWALP : Stochastic Weight Averaging in Low Precision Training
Guandao Yang, Tianyi Zhang, Polina Kirichenko et al.
Switching Linear Dynamics for Variational Bayes Filtering
Philip Becker-Ehmck, Jan Peters, Patrick Van Der Smagt
Taming MAML: Efficient unbiased meta-reinforcement learning
Hao Liu, Richard Socher, Caiming Xiong
TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning
Sung Whan Yoon, Jun Seo, Jaekyun Moon
Target-Based Temporal-Difference Learning
Donghwan Lee, Niao He
Target Tracking for Contextual Bandits: Application to Demand Side Management
Margaux Brégère, Pierre Gaillard, Yannig Goude et al.
TarMAC: Targeted Multi-Agent Communication
Abhishek Das, Théophile Gervet, Joshua Romoff et al.
Task-Agnostic Dynamics Priors for Deep Reinforcement Learning
Yilun Du, Karthic Narasimhan
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