Papers
4,122 papers found
Weibull Racing Survival Analysis with Competing Events, Left Truncation, and Time-Varying Covariates
Quan Zhang, Yanxun Xu, Mei-Cheng Wang et al.
Weisfeiler and Leman go Machine Learning: The Story so far
Christopher Morris, Yaron Lipman, Haggai Maron et al.
When Locally Linear Embedding Hits Boundary
Hau-Tieng Wu, Nan Wu
Wide-minima Density Hypothesis and the Explore-Exploit Learning Rate Schedule
Nikhil Iyer, V. Thejas, Nipun Kwatra et al.
Zeroth-Order Alternating Gradient Descent Ascent Algorithms for A Class of Nonconvex-Nonconcave Minimax Problems
Zi Xu, Zi-Qi Wang, Jun-Lin Wang et al.
abess: A Fast Best-Subset Selection Library in Python and R
Jin Zhu, Xueqin Wang, Liyuan Hu et al.
A Bregman Learning Framework for Sparse Neural Networks
Leon Bungert, Tim Roith, Daniel Tenbrinck et al.
Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization
Feihu Huang, Shangqian Gao, Jian Pei et al.
Accelerating Adaptive Cubic Regularization of Newton's Method via Random Sampling
Xi Chen, Bo Jiang, Tianyi Lin et al.
A Class of Conjugate Priors for Multinomial Probit Models which Includes the Multivariate Normal One
Augusto Fasano, Daniele Durante
A Closer Look at Embedding Propagation for Manifold Smoothing
Diego Velazquez, Pau Rodriguez, Josep M. Gonfaus et al.
A Computationally Efficient Framework for Vector Representation of Persistence Diagrams
Kit C Chan, Umar Islambekov, Alexey Luchinsky et al.
Active Learning for Nonlinear System Identification with Guarantees
Horia Mania, Michael I. Jordan, Benjamin Recht
Active Structure Learning of Bayesian Networks in an Observational Setting
Noa Ben-David, Sivan Sabato
Adaptive Greedy Algorithm for Moderately Large Dimensions in Kernel Conditional Density Estimation
Minh-Lien Jeanne Nguyen, Claire Lacour, Vincent Rivoirard
Additive Nonlinear Quantile Regression in Ultra-high Dimension
Ben Sherwood, Adam Maidman
A Distribution Free Conditional Independence Test with Applications to Causal Discovery
Zhanrui Cai, Runze Li, Yaowu Zhang
Advantage of Deep Neural Networks for Estimating Functions with Singularity on Hypersurfaces
Masaaki Imaizumi, Kenji Fukumizu
Adversarial Classification: Necessary Conditions and Geometric Flows
Nicolás García Trillos, Ryan Murray
Adversarial Robustness Guarantees for Gaussian Processes
Andrea Patane, Arno Blaas, Luca Laurenti et al.
A Forward Approach for Sufficient Dimension Reduction in Binary Classification
Jongkyeong Kang, Seung Jun Shin
A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning
Andrew Patterson, Adam White, Martha White
A Kernel Two-Sample Test for Functional Data
George Wynne, Andrew B. Duncan
All You Need is a Good Functional Prior for Bayesian Deep Learning
Ba-Hien Tran, Simone Rossi, Dimitrios Milios et al.
ALMA: Alternating Minimization Algorithm for Clustering Mixture Multilayer Network
Xing Fan, Marianna Pensky, Feng Yu et al.