Papers
Mirrorless Mirror Descent: A Natural Derivation of Mirror Descent
Suriya Gunasekar, Blake Woodworth, Nathan Srebro
Misspecification in Prediction Problems and Robustness via Improper Learning
Annie Marsden, John Duchi, Gregory Valiant
Model updating after interventions paradoxically introduces bias
James Liley, Samuel Emerson, Bilal Mateen et al.
Moment-Based Variational Inference for Stochastic Differential Equations
Christian Wildner, Heinz Koeppl
Momentum Improves Optimization on Riemannian Manifolds
Foivos Alimisis, Antonio Orvieto, Gary Becigneul et al.
Multi-Armed Bandits with Cost Subsidy
Deeksha Sinha, Karthik Abinav Sankararaman, Abbas Kazerouni et al.
Multi-Fidelity High-Order Gaussian Processes for Physical Simulation
Zheng Wang, Wei Xing, Robert Kirby et al.
Multitask Bandit Learning Through Heterogeneous Feedback Aggregation
Zhi Wang, Chicheng Zhang, Manish Kumar Singh et al.
Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications
Guillaume Ausset, Stephan Clémencon, François Portier
Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning
Ming Yin, Yu Bai, Yu-Xiang Wang
Nested Barycentric Coordinate System as an Explicit Feature Map
Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich et al.
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference
Maxime Vandegar, Michael Kagan, Antoine Wehenkel et al.
Neural Enhanced Belief Propagation on Factor Graphs
Víctor Garcia Satorras, Max Welling
Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers
Alex Lamb, Anirudh Goyal, Agnieszka Słowik et al.
Noise Contrastive Meta-Learning for Conditional Density Estimation using Kernel Mean Embeddings
Jean-Francois Ton, Lucian CHAN, Yee Whye Teh et al.
Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization
Tianyi Liu, Yan Li, Song Wei et al.
Non-asymptotic Performance Guarantees for Neural Estimation of f-Divergences
Sreejith Sreekumar, Zhengxin Zhang, Ziv Goldfeld
Nonlinear Functional Output Regression: A Dictionary Approach
Dimitri Bouche, Marianne Clausel, François Roueff et al.
Nonlinear Projection Based Gradient Estimation for Query Efficient Blackbox Attacks
Huichen Li, Linyi Li, Xiaojun Xu et al.
Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms
Alicia Curth, Mihaela van der Schaar
Nonparametric Variable Screening with Optimal Decision Stumps
Jason Klusowski, Peter Tian
Non-Stationary Off-Policy Optimization
Joey Hong, Branislav Kveton, Manzil Zaheer et al.
Non-Volume Preserving Hamiltonian Monte Carlo and No-U-TurnSamplers
Hadi Mohasel Afshar, Rafael Oliveira, Sally Cripps
No-regret Algorithms for Multi-task Bayesian Optimization
Sayak Ray Chowdhury, Aditya Gopalan