Papers
Exact Inference for Integer Latent-Variable Models
Kevin Winner, Debora Sujono, Dan Sheldon
Exact MAP Inference by Avoiding Fractional Vertices
Erik M. Lindgren, Alexandros G. Dimakis, Adam Klivans
Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms
Jialei Wang, Lin Xiao
Failures of Gradient-Based Deep Learning
Shai Shalev-Shwartz, Ohad Shamir, Shaked Shammah
Fairness in Reinforcement Learning
Shahin Jabbari, Matthew Joseph, Michael Kearns et al.
Fake News Mitigation via Point Process Based Intervention
Mehrdad Farajtabar, Jiachen Yang, Xiaojing Ye et al.
Fast Bayesian Intensity Estimation for the Permanental Process
Christian J. Walder, Adrian N. Bishop
Faster Greedy MAP Inference for Determinantal Point Processes
Insu Han, Prabhanjan Kambadur, Kyoungsoo Park et al.
Faster Principal Component Regression and Stable Matrix Chebyshev Approximation
Zeyuan Allen-Zhu, Yuanzhi Li
Fast k-Nearest Neighbour Search via Prioritized DCI
Ke Li, Jitendra Malik
FeUdal Networks for Hierarchical Reinforcement Learning
Alexander Sasha Vezhnevets, Simon Osindero, Tom Schaul et al.
Follow the Compressed Leader: Faster Online Learning of Eigenvectors and Faster MMWU
Zeyuan Allen-Zhu, Yuanzhi Li
Follow the Moving Leader in Deep Learning
Shuai Zheng, James T. Kwok
Forest-type Regression with General Losses and Robust Forest
Alexander Hanbo Li, Andrew Martin
Forward and Reverse Gradient-Based Hyperparameter Optimization
Luca Franceschi, Michele Donini, Paolo Frasconi et al.
Frame-based Data Factorizations
Sebastian Mair, Ahcène Boubekki, Ulf Brefeld
From Patches to Images: A Nonparametric Generative Model
Geng Ji, Michael C. Hughes, Erik B. Sudderth
Generalization and Equilibrium in Generative Adversarial Nets (GANs)
Sanjeev Arora, Rong Ge, Yingyu Liang et al.
Geometry of Neural Network Loss Surfaces via Random Matrix Theory
Jeffrey Pennington, Yasaman Bahri
Globally Induced Forest: A Prepruning Compression Scheme
Jean-Michel Begon, Arnaud Joly, Pierre Geurts
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs
Alon Brutzkus, Amir Globerson
Global optimization of Lipschitz functions
Cédric Malherbe, Nicolas Vayatis
Gradient Boosted Decision Trees for High Dimensional Sparse Output
Si Si, Huan Zhang, S. Sathiya Keerthi et al.
Gradient Coding: Avoiding Stragglers in Distributed Learning
Rashish Tandon, Qi Lei, Alexandros G. Dimakis et al.