Papers
Faster Algorithms for Binary Matrix Factorization
Ravi Kumar, Rina Panigrahy, Ali Rahimi et al.
Faster Attend-Infer-Repeat with Tractable Probabilistic Models
Karl Stelzner, Robert Peharz, Kristian Kersting
Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization
Feihu Huang, Songcan Chen, Heng Huang
Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications
Pin-Yu Chen, Lingfei Wu, Sijia Liu et al.
Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise
Henry Reeve, Ata Kaban
Fault Tolerance in Iterative-Convergent Machine Learning
Aurick Qiao, Bryon Aragam, Bingjing Zhang et al.
Feature-Critic Networks for Heterogeneous Domain Generalization
Yiying Li, Yongxin Yang, Wei Zhou et al.
Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data
Sergul Aydore, Bertrand Thirion, Gael Varoquaux
Finding Mixed Nash Equilibria of Generative Adversarial Networks
Ya-Ping Hsieh, Chen Liu, Volkan Cevher
Finding Options that Minimize Planning Time
Yuu Jinnai, David Abel, David Hershkowitz et al.
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks
Sanjeev Arora, Simon Du, Wei Hu et al.
Fingerprint Policy Optimisation for Robust Reinforcement Learning
Supratik Paul, Michael A. Osborne, Shimon Whiteson
Finite-Time Analysis of Distributed TD(0) with Linear Function Approximation on Multi-Agent Reinforcement Learning
Thinh Doan, Siva Maguluri, Justin Romberg
First-Order Adversarial Vulnerability of Neural Networks and Input Dimension
Carl-Johann Simon-Gabriel, Yann Ollivier, Leon Bottou et al.
First-Order Algorithms Converge Faster than $O(1/k)$ on Convex Problems
Ching-Pei Lee, Stephen Wright
Flat Metric Minimization with Applications in Generative Modeling
Thomas Möllenhoff, Daniel Cremers
Flexibly Fair Representation Learning by Disentanglement
Elliot Creager, David Madras, Joern-Henrik Jacobsen et al.
FloWaveNet : A Generative Flow for Raw Audio
Sungwon Kim, Sang-Gil Lee, Jongyoon Song et al.
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design
Jonathan Ho, Xi Chen, Aravind Srinivas et al.
Formal Privacy for Functional Data with Gaussian Perturbations
Ardalan Mirshani, Matthew Reimherr, Aleksandra Slavković
Functional Transparency for Structured Data: a Game-Theoretic Approach
Guang-He Lee, Wengong Jin, David Alvarez-Melis et al.
Game Theoretic Optimization via Gradient-based Nikaido-Isoda Function
Arvind Raghunathan, Anoop Cherian, Devesh Jha
Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits
Branislav Kveton, Csaba Szepesvari, Sharan Vaswani et al.
Gauge Equivariant Convolutional Networks and the Icosahedral CNN
Taco Cohen, Maurice Weiler, Berkay Kicanaoglu et al.