Papers
4,025 papers found
Robust and Agnostic Learning of Conditional Distributional Treatment Effects
Nathan Kallus, Miruna Oprescu
Robust Linear Regression for General Feature Distribution
Tom Norman, Nir Weinberger, Kfir Y. Levy
Robust Linear Regression: Gradient-descent, Early-stopping, and Beyond
Meyer Scetbon, Elvis Dohmatob
Robust Variational Autoencoding with Wasserstein Penalty for Novelty Detection
Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman
Root Cause Identification for Collective Anomalies in Time Series given an Acyclic Summary Causal Graph with Loops
Charles K. Assaad, Imad Ez-Zejjari, Lei Zan
Safe Sequential Testing and Effect Estimation in Stratified Count Data
Rosanne Turner, Peter Grunwald
Sample Complexity of Distinguishing Cause from Effect
Jayadev Acharya, Sourbh Bhadane, Arnab Bhattacharyya et al.
Sample Complexity of Kernel-Based Q-Learning
Sing-Yuan Yeh, Fu-Chieh Chang, Chang-Wei Yueh et al.
Sample Efficiency of Data Augmentation Consistency Regularization
Shuo Yang, Yijun Dong, Rachel Ward et al.
Sampling From a Schrödinger Bridge
Austin Stromme
Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes
Felix Jimenez, Matthias Katzfuss
Scalable Bicriteria Algorithms for Non-Monotone Submodular Cover
Victoria Crawford
Scalable marked point processes for exchangeable and non-exchangeable event sequences
Aristeidis Panos, Ioannis Kosmidis, Petros Dellaportas
Scalable Spectral Clustering with Group Fairness Constraints
Ji Wang, Ding Lu, Ian Davidson et al.
Scalable Unbalanced Sobolev Transport for Measures on a Graph
Tam Le, Truyen Nguyen, Kenji Fukumizu
Score-based Quickest Change Detection for Unnormalized Models
Suya Wu, Enmao Diao, Taposh Banerjee et al.
Second Order Path Variationals in Non-Stationary Online Learning
Dheeraj Baby, Yu-Xiang Wang
Select and Optimize: Learning to solve large-scale TSP instances
Hanni Cheng, Haosi Zheng, Ya Cong et al.
Semantic Strengthening of Neuro-Symbolic Learning
Kareem Ahmed, Kai-Wei Chang, Guy Van den Broeck
Semi-Verified PAC Learning from the Crowd
Shiwei Zeng, Jie Shen
Sequential Gradient Descent and Quasi-Newton’s Method for Change-Point Analysis
Xianyang Zhang, Trisha Dawn
Simulator-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems
Luca Masserano, Tommaso Dorigo, Rafael Izbicki et al.
Singular Value Representation: A New Graph Perspective On Neural Networks
Dan Meller, Nicolas Berkouk
SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals
Alexander K. Lew, George Matheos, Tan Zhi-Xuan et al.
Smoothly Giving up: Robustness for Simple Models
Tyler Sypherd, Nathaniel Stromberg, Richard Nock et al.