Papers
Lower Bounds for Smooth Nonconvex Finite-Sum Optimization
Dongruo Zhou, Quanquan Gu
Low Latency Privacy Preserving Inference
Alon Brutzkus, Ran Gilad-Bachrach, Oren Elisha
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations
Brian Trippe, Jonathan Huggins, Raj Agrawal et al.
Making Convolutional Networks Shift-Invariant Again
Richard Zhang
Making Decisions that Reduce Discriminatory Impacts
Matt Kusner, Chris Russell, Joshua Loftus et al.
Making Deep Q-learning methods robust to time discretization
Corentin Tallec, Léonard Blier, Yann Ollivier
Manifold Mixup: Better Representations by Interpolating Hidden States
Vikas Verma, Alex Lamb, Christopher Beckham et al.
MASS: Masked Sequence to Sequence Pre-training for Language Generation
Kaitao Song, Xu Tan, Tao Qin et al.
Matrix-Free Preconditioning in Online Learning
Ashok Cutkosky, Tamas Sarlos
Maximum Entropy-Regularized Multi-Goal Reinforcement Learning
Rui Zhao, Xudong Sun, Volker Tresp
Maximum Likelihood Estimation for Learning Populations of Parameters
Ramya Korlakai Vinayak, Weihao Kong, Gregory Valiant et al.
Memory-Optimal Direct Convolutions for Maximizing Classification Accuracy in Embedded Applications
Albert Gural, Boris Murmann
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
Yuzhe Yang, Guo Zhang, Dina Katabi et al.
Meta-Learning Neural Bloom Filters
Jack Rae, Sergey Bartunov, Timothy Lillicrap
MetricGAN: Generative Adversarial Networks based Black-box Metric Scores Optimization for Speech Enhancement
Szu-Wei Fu, Chien-Feng Liao, Yu Tsao et al.
Metric-Optimized Example Weights
Sen Zhao, Mahdi Milani Fard, Harikrishna Narasimhan et al.
Metropolis-Hastings Generative Adversarial Networks
Ryan Turner, Jane Hung, Eric Frank et al.
Minimal Achievable Sufficient Statistic Learning
Milan Cvitkovic, Günther Koliander
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets
Pierre-Alexandre Mattei, Jes Frellsen
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing
Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor et al.
Mixture Models for Diverse Machine Translation: Tricks of the Trade
Tianxiao Shen, Myle Ott, Michael Auli et al.
Model-Based Active Exploration
Pranav Shyam, Wojciech Jaśkowski, Faustino Gomez