Papers
Model Distillation for Revenue Optimization: Interpretable Personalized Pricing
Max Biggs, Wei Sun, Markus Ettl
Model-Free and Model-Based Policy Evaluation when Causality is Uncertain
David A Bruns-Smith
Model-Free Reinforcement Learning: from Clipped Pseudo-Regret to Sample Complexity
Zihan Zhang, Yuan Zhou, Xiangyang Ji
Model Fusion for Personalized Learning
Thanh Chi Lam, Nghia Hoang, Bryan Kian Hsiang Low et al.
Modeling Hierarchical Structures with Continuous Recursive Neural Networks
Jishnu Ray Chowdhury, Cornelia Caragea
Modelling Behavioural Diversity for Learning in Open-Ended Games
Nicolas Perez-Nieves, Yaodong Yang, Oliver Slumbers et al.
Model Performance Scaling with Multiple Data Sources
Tatsunori Hashimoto
Model-Targeted Poisoning Attacks with Provable Convergence
Fnu Suya, Saeed Mahloujifar, Anshuman Suri et al.
Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment
Michael Chang, Sid Kaushik, Sergey Levine et al.
Momentum Residual Neural Networks
Michael E. Sander, Pierre Ablin, Mathieu Blondel et al.
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