Papers
On the Representation of Pairwise Causal Background Knowledge and Its Applications in Causal Inference
Zhuangyan Fang, Ruiqi Zhao, Yue Liu et al.
An Augmentation Overlap Theory of Contrastive Learning
Qi Zhang, Yifei Wang, Yisen Wang
Algorithms for ridge estimation with convergence guarantees
Wanli Qiao, Wolfgang Polonik
Talent: A Tabular Analytics and Learning Toolbox
Si-Yang Liu, Hao-Run Cai, Qi-Le Zhou et al.
Inferring Change Points in High-Dimensional Regression via Approximate Message Passing
Gabriel Arpino, Xiaoqi Liu, Julia Gontarek et al.
Universality of Kernel Random Matrices and Kernel Regression in the Quadratic Regime
Parthe Pandit, Zhichao Wang, Yizhe Zhu
Lexicographic Lipschitz Bandits: New Algorithms and a Lower Bound
Bo Xue, Ji Cheng, Fei Liu et al.
On the Natural Gradient of the Evidence Lower Bound
Nihat Ay, Jesse van Oostrum, Adwait Datar
Geometry and Stability of Supervised Learning Problems
Facundo Mémoli, Brantley Vose, Robert C. Williamson
Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination
Peng Wang, Xiao Li, Can Yaras et al.
Optimal Rates of Kernel Ridge Regression under Source Condition in Large Dimensions
Haobo Zhang, Yicheng Li, Weihao Lu et al.
A Hybrid Weighted Nearest Neighbour Classifier for Semi-Supervised Learning
Stephen M. S. Lee, Mehdi Soleymani
Scalable and Adaptive Variational Bayes Methods for Hawkes Processes
Deborah Sulem, Vincent Rivoirard, Judith Rousseau
Biological Sequence Kernels with Guaranteed Flexibility
Alan N. Amin, Debora S. Marks, Eli N. Weinstein
Unified Discrete Diffusion for Categorical Data
Lingxiao Zhao, Xueying Ding, Lijun Yu et al.
Reinforcement Learning for Infinite-Dimensional Systems
Wei Zhang, Jr-Shin Li
Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation
Hao Liu, Jiahui Cheng, Wenjing Liao
Learning-to-Optimize with PAC-Bayesian Guarantees: Theoretical Considerations and Practical Implementation
Michael Sucker, Jalal Fadili, Peter Ochs
Sparse Semiparametric Discriminant Analysis for High-dimensional Zero-inflated Data
Hee Cheol Chung, Yang Ni, Irina Gaynanova
Stochastic Interpolants: A Unifying Framework for Flows and Diffusions
Michael Albergo, Nicholas M. Boffi, Eric Vanden-Eijnden
Efficient Methods for Non-stationary Online Learning
Peng Zhao, Yan-Feng Xie, Lijun Zhang et al.
Decentralized Asynchronous Optimization with DADAO allows Decoupling and Acceleration
Adel Nabli, Edouard Oyallon
Mixtures of Gaussian Process Experts with SMC^2
Teemu Härkönen, Sara Wade, Kody Law et al.
Robust Point Matching with Distance Profiles
YoonHaeng Hur, Yuehaw Khoo