Papers
Mean-Variance Analysis in Bayesian Optimization under Uncertainty
Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi
Measure Transport with Kernel Stein Discrepancy
Matthew Fisher, Tui Nolan, Matthew Graham et al.
Meta-Learning Divergences for Variational Inference
Ruqi Zhang, Yingzhen Li, Christopher De Sa et al.
Meta Learning in the Continuous Time Limit
Ruitu Xu, Lin Chen, Amin Karbasi
Minimal enumeration of all possible total effects in a Markov equivalence class
Richard Guo, Emilija Perkovic
Minimax Estimation of Laplacian Constrained Precision Matrices
Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel Palomar
Minimax Model Learning
Cameron Voloshin, Nan Jiang, Yisong Yue
Minimax Optimal Regression over Sobolev Spaces via Laplacian Regularization on Neighborhood Graphs
Alden Green, Sivaraman Balakrishnan, Ryan Tibshirani
Mirror Descent View for Neural Network Quantization
Thalaiyasingam Ajanthan, Kartik Gupta, Philip Torr et al.
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.