Papers
4,122 papers found
Semi-Supervised Off-Policy Reinforcement Learning and Value Estimation for Dynamic Treatment Regimes
Aaron Sonabend-W, Nilanjana Laha, Ashwin N. Ananthakrishnan et al.
Sensing Theorems for Unsupervised Learning in Linear Inverse Problems
Julián Tachella, Dongdong Chen, Mike Davies
Sensitivity-Free Gradient Descent Algorithms
Ion Matei, Maksym Zhenirovskyy, Johan de Kleer et al.
Set-valued Classification with Out-of-distribution Detection for Many Classes
Zhou Wang, Xingye Qiao
skrl: Modular and Flexible Library for Reinforcement Learning
Antonio Serrano-Muñoz, Dimitrios Chrysostomou, Simon Bøgh et al.
Small Transformers Compute Universal Metric Embeddings
Anastasis Kratsios, Valentin Debarnot, Ivan Dokmanić
Sparse GCA and Thresholded Gradient Descent
Sheng Gao, Zongming Ma
Sparse Graph Learning from Spatiotemporal Time Series
Andrea Cini, Daniele Zambon, Cesare Alippi
Sparse Markov Models for High-dimensional Inference
Guilherme Ost, Daniel Y. Takahashi
Sparse PCA: a Geometric Approach
Dimitris Bertsimas, Driss Lahlou Kitane
Sparse Plus Low Rank Matrix Decomposition: A Discrete Optimization Approach
Dimitris Bertsimas, Ryan Cory-Wright, Nicholas A. G. Johnson
SQLFlow: An Extensible Toolkit Integrating DB and AI
Jun Zhou, Ke Zhang, Lin Wang et al.
Statistical Comparisons of Classifiers by Generalized Stochastic Dominance
Christoph Jansen, Malte Nalenz, Georg Schollmeyer et al.
Statistical Inference for Noisy Incomplete Binary Matrix
Yunxiao Chen, Chengcheng Li, Jing Ouyang et al.
Statistical Robustness of Empirical Risks in Machine Learning
Shaoyan Guo, Huifu Xu, Liwei Zhang
Stochastic Optimization under Distributional Drift
Joshua Cutler, Dmitriy Drusvyatskiy, Zaid Harchaoui
Strategic Knowledge Transfer
Max Olan Smith, Thomas Anthony, Michael P. Wellman
Surrogate Assisted Semi-supervised Inference for High Dimensional Risk Prediction
Jue Hou, Zijian Guo, Tianxi Cai
T-Cal: An Optimal Test for the Calibration of Predictive Models
Donghwan Lee, Xinmeng Huang, Hamed Hassani et al.
Temporal Abstraction in Reinforcement Learning with the Successor Representation
Marlos C. Machado, Andre Barreto, Doina Precup et al.
The Art of BART: Minimax Optimality over Nonhomogeneous Smoothness in High Dimension
Seonghyun Jeong, Veronika Rockova
The Bayesian Learning Rule
Mohammad Emtiyaz Khan, Håvard Rue