Papers
4,122 papers found
Graph-Aided Online Multi-Kernel Learning
Pouya M. Ghari, Yanning Shen
Graph Attention Retrospective
Kimon Fountoulakis, Amit Levi, Shenghao Yang et al.
Graph Clustering with Graph Neural Networks
Anton Tsitsulin, John Palowitch, Bryan Perozzi et al.
Group SLOPE Penalized Low-Rank Tensor Regression
Yang Chen, Ziyan Luo
Hard-Constrained Deep Learning for Climate Downscaling
Paula Harder, Alex Hernandez-Garcia, Venkatesh Ramesh et al.
HiClass: a Python Library for Local Hierarchical Classification Compatible with Scikit-learn
Fábio M. Miranda, Niklas Köhnecke, Bernhard Y. Renard
Hierarchical Kernels in Deep Kernel Learning
Wentao Huang, Houbao Lu, Haizhang Zhang
High-Dimensional Inference for Generalized Linear Models with Hidden Confounding
Jing Ouyang, Kean Ming Tan, Gongjun Xu
Higher-Order Spectral Clustering Under Superimposed Stochastic Block Models
Subhadeep Paul, Olgica Milenkovic, Yuguo Chen
HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation
Weijie J. Su, Yuancheng Zhu
How Do You Want Your Greedy: Simultaneous or Repeated?
Moran Feldman, Christopher Harshaw, Amin Karbasi
Implicit Regularization and Entrywise Convergence of Riemannian Optimization for Low Tucker-Rank Tensor Completion
Haifeng Wang, Jinchi Chen, Ke Wei
Importance Sparsification for Sinkhorn Algorithm
Mengyu Li, Jun Yu, Tao Li et al.
Improving multiple-try Metropolis with local balancing
Philippe Gagnon, Florian Maire, Giacomo Zanella
Incremental Learning in Diagonal Linear Networks
Raphaël Berthier
Inference for a Large Directed Acyclic Graph with Unspecified Interventions
Chunlin Li, Xiaotong Shen, Wei Pan
Inference for Gaussian Processes with Matern Covariogram on Compact Riemannian Manifolds
Didong Li, Wenpin Tang, Sudipto Banerjee
Inference on the Change Point under a High Dimensional Covariance Shift
Abhishek Kaul, Hongjin Zhang, Konstantinos Tsampourakis et al.
Infinite-dimensional optimization and Bayesian nonparametric learning of stochastic differential equations
Arnab Ganguly, Riten Mitra, Jinpu Zhou
Insights into Ordinal Embedding Algorithms: A Systematic Evaluation
Leena Chennuru Vankadara, Michael Lohaus, Siavash Haghiri et al.
Instance-Dependent Confidence and Early Stopping for Reinforcement Learning
Eric Xia, Koulik Khamaru, Martin J. Wainwright et al.
Instance-Dependent Generalization Bounds via Optimal Transport
Songyan Hou, Parnian Kassraie, Anastasis Kratsios et al.