Papers
Faster and Non-ergodic O(1/K) Stochastic Alternating Direction Method of Multipliers
Cong Fang, Feng Cheng, Zhouchen Lin
Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe
Quentin Berthet, Vianney Perchet
Fast, Sample-Efficient Algorithms for Structured Phase Retrieval
Gauri Jagatap, Chinmay Hegde
Fast-Slow Recurrent Neural Networks
Asier Mujika, Florian Meier, Angelika Steger
Federated Multi-Task Learning
Virginia Smith, Chao-Kai Chiang, Maziar Sanjabi et al.
Few-Shot Adversarial Domain Adaptation
Saeid Motiian, Quinn Jones, Seyed Iranmanesh et al.
Few-Shot Learning Through an Information Retrieval Lens
Eleni Triantafillou, Richard Zemel, Raquel Urtasun
f-GANs in an Information Geometric Nutshell
Richard Nock, Zac Cranko, Aditya K Menon et al.
Filtering Variational Objectives
Chris J Maddison, John Lawson, George Tucker et al.
Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting
Yue Wang, Wei Chen, Yuting Liu et al.
First-Order Adaptive Sample Size Methods to Reduce Complexity of Empirical Risk Minimization
Aryan Mokhtari, Alejandro Ribeiro
Fisher GAN
Youssef Mroueh, Tom Sercu
Fitting Low-Rank Tensors in Constant Time
Kohei Hayashi, Yuichi Yoshida
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data
Joel A Tropp, Alp Yurtsever, Madeleine Udell et al.
Flexible statistical inference for mechanistic models of neural dynamics
Jan-Matthis Lueckmann, Pedro J Goncalves, Giacomo Bassetto et al.
Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks
Urs Köster, Tristan Webb, Xin Wang et al.
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation
Matthias Hein, Maksym Andriushchenko
From Bayesian Sparsity to Gated Recurrent Nets
Hao He, Bo Xin, Satoshi Ikehata et al.
From Parity to Preference-based Notions of Fairness in Classification
Muhammad Bilal Zafar, Isabel Valera, Manuel Rodriguez et al.
From which world is your graph
Cheng Li, Felix MF Wong, Zhenming Liu et al.
Fully Decentralized Policies for Multi-Agent Systems: An Information Theoretic Approach
Roel Dobbe, David Fridovich-Keil, Claire Tomlin
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner et al.
Gated Recurrent Convolution Neural Network for OCR
Jianfeng Wang, Xiaolin Hu
Gauging Variational Inference
Sung-Soo Ahn, Michael Chertkov, Jinwoo Shin
Gaussian process based nonlinear latent structure discovery in multivariate spike train data
Anqi Wu, Nicholas A. Roy, Stephen Keeley et al.