Papers
4,122 papers found
Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training
Diego Granziol, Stefan Zohren, Stephen Roberts
Learning to Optimize: A Primer and A Benchmark
Tianlong Chen, Xiaohan Chen, Wuyang Chen et al.
Let's Make Block Coordinate Descent Converge Faster: Faster Greedy Rules, Message-Passing, Active-Set Complexity, and Superlinear Convergence
Julie Nutini, Issam Laradji, Mark Schmidt
LinCDE: Conditional Density Estimation via Lindsey's Method
Zijun Gao, Trevor Hastie
Linearization and Identification of Multiple-Attractor Dynamical Systems through Laplacian Eigenmaps
Bernardo Fichera, Aude Billard
Logarithmic Regret for Episodic Continuous-Time Linear-Quadratic Reinforcement Learning over a Finite-Time Horizon
Matteo Basei, Xin Guo, Anran Hu et al.
Low-rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization
Quanming Yao, Yaqing Wang, Bo Han et al.
LSAR: Efficient Leverage Score Sampling Algorithm for the Analysis of Big Time Series Data
Ali Eshragh, Fred Roosta, Asef Nazari et al.
Machine Learning on Graphs: A Model and Comprehensive Taxonomy
Ines Chami, Sami Abu-El-Haija, Bryan Perozzi et al.
MALTS: Matching After Learning to Stretch
Harsh Parikh, Cynthia Rudin, Alexander Volfovsky
Manifold Coordinates with Physical Meaning
Samson J. Koelle, Hanyu Zhang, Marina Meila et al.
Matrix Completion with Covariate Information and Informative Missingness
Huaqing Jin, Yanyuan Ma, Fei Jiang
Maximum sampled conditional likelihood for informative subsampling
HaiYing Wang, Jae Kwang Kim
Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks
Alexander Shevchenko, Vyacheslav Kungurtsev, Marco Mondelli
Meta-analysis of heterogeneous data: integrative sparse regression in high-dimensions
Subha Maity, Yuekai Sun, Moulinath Banerjee
Metrics of Calibration for Probabilistic Predictions
Imanol Arrieta-Ibarra, Paman Gujral, Jonathan Tannen et al.
Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling
Keru Wu, Scott Schmidler, Yuansi Chen
Minimax optimal approaches to the label shift problem in non-parametric settings
Subha Maity, Yuekai Sun, Moulinath Banerjee
Mitigating the Effects of Non-Identifiability on Inference for Bayesian Neural Networks with Latent Variables
Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez
Model Averaging Is Asymptotically Better Than Model Selection For Prediction
Tri M. Le, Bertrand S. Clarke
More Powerful Conditional Selective Inference for Generalized Lasso by Parametric Programming
Vo Nguyen Le Duy, Ichiro Takeuchi
Multi-Agent Multi-Armed Bandits with Limited Communication
Mridul Agarwal, Vaneet Aggarwal, Kamyar Azizzadenesheli
Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick et al.