Papers
Monotonic Robust Policy Optimization with Model Discrepancy
Yuankun Jiang, Chenglin Li, Wenrui Dai et al.
Monte Carlo Variational Auto-Encoders
Achille Thin, Nikita Kotelevskii, Arnaud Doucet et al.
Moreau-Yosida $f$-divergences
Dávid Terjék
More Powerful and General Selective Inference for Stepwise Feature Selection using Homotopy Method
Kazuya Sugiyama, Vo Nguyen Le Duy, Ichiro Takeuchi
MorphVAE: Generating Neural Morphologies from 3D-Walks using a Variational Autoencoder with Spherical Latent Space
Sophie C. Laturnus, Philipp Berens
MOTS: Minimax Optimal Thompson Sampling
Tianyuan Jin, Pan Xu, Jieming Shi et al.
MSA Transformer
Roshan M Rao, Jason Liu, Robert Verkuil et al.
Muesli: Combining Improvements in Policy Optimization
Matteo Hessel, Ivo Danihelka, Fabio Viola et al.
Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers
Luke Marris, Paul Muller, Marc Lanctot et al.
Multi-Dimensional Classification via Sparse Label Encoding
Bin-Bin Jia, Min-Ling Zhang
Multidimensional Scaling: Approximation and Complexity
Erik Demaine, Adam Hesterberg, Frederic Koehler et al.
Multi-group Agnostic PAC Learnability
Guy N Rothblum, Gal Yona
Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning
Xutong Liu, Jinhang Zuo, Xiaowei Chen et al.
Multiplicative Noise and Heavy Tails in Stochastic Optimization
Liam Hodgkinson, Michael Mahoney
Multiplying Matrices Without Multiplying
Davis Blalock, John Guttag
Multi-Receiver Online Bayesian Persuasion
Matteo Castiglioni, Alberto Marchesi, Andrea Celli et al.
Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference
Shumao Zhang, Pengchuan Zhang, Thomas Y Hou
Multi-Task Reinforcement Learning with Context-based Representations
Shagun Sodhani, Amy Zhang, Joelle Pineau
MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning
Kevin Li, Abhishek Gupta, Ashwin Reddy et al.
Narrow Margins: Classification, Margins and Fat Tails
Francois Buet-Golfouse
Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
Sam Devlin, Raluca Georgescu, Ida Momennejad et al.
Near-Optimal Algorithms for Explainable k-Medians and k-Means
Konstantin Makarychev, Liren Shan
Near-Optimal Confidence Sequences for Bounded Random Variables
Arun K Kuchibhotla, Qinqing Zheng
Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise
Vivek Farias, Andrew A Li, Tianyi Peng
Near-Optimal Linear Regression under Distribution Shift
Qi Lei, Wei Hu, Jason Lee