Papers
4,122 papers found
Integrating Random Effects in Deep Neural Networks
Giora Simchoni, Saharon Rosset
Interpolating Classifiers Make Few Mistakes
Tengyuan Liang, Benjamin Recht
Interpretable and Fair Boolean Rule Sets via Column Generation
Connor Lawless, Sanjeeb Dash, Oktay Gunluk et al.
Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics
Mu Niu, Zhenwen Dai, Pokman Cheung et al.
Intrinsic Persistent Homology via Density-based Metric Learning
Ximena Fernández, Eugenio Borghini, Gabriel Mindlin et al.
Iterated Block Particle Filter for High-dimensional Parameter Learning: Beating the Curse of Dimensionality
Ning Ning, Edward L. Ionides
Jump Interval-Learning for Individualized Decision Making with Continuous Treatments
Hengrui Cai, Chengchun Shi, Rui Song et al.
Kernel-based estimation for partially functional linear model: Minimax rates and randomized sketches
Shaogao Lv, Xin He, Junhui Wang
Kernel-Matrix Determinant Estimates from stopped Cholesky Decomposition
Simon Bartels, Wouter Boomsma, Jes Frellsen et al.
Knowledge Hypergraph Embedding Meets Relational Algebra
Bahare Fatemi, Perouz Taslakian, David Vazquez et al.
L0Learn: A Scalable Package for Sparse Learning using L0 Regularization
Hussein Hazimeh, Rahul Mazumder, Tim Nonet
Label Distribution Changing Learning with Sample Space Expanding
Chao Xu, Hong Tao, Jing Zhang et al.
Labels, Information, and Computation: Efficient Learning Using Sufficient Labels
Shiyu Duan, Spencer Chang, Jose C. Principe
LapGym - An Open Source Framework for Reinforcement Learning in Robot-Assisted Laparoscopic Surgery
Paul Maria Scheikl, Balázs Gyenes, Rayan Younis et al.
Large data limit of the MBO scheme for data clustering: convergence of the dynamics
Tim Laux, Jona Lelmi
Large sample spectral analysis of graph-based multi-manifold clustering
Nicolas Garcia Trillos, Pengfei He, Chenghui Li
Learning an Explicit Hyper-parameter Prediction Function Conditioned on Tasks
Jun Shu, Deyu Meng, Zongben Xu
Learning-augmented count-min sketches via Bayesian nonparametrics
Emanuele Dolera, Stefano Favaro, Stefano Peluchetti
Learning Conditional Generative Models for Phase Retrieval
Tobias Uelwer, Sebastian Konietzny, Alexander Oberstrass et al.
Learning Good State and Action Representations for Markov Decision Process via Tensor Decomposition
Chengzhuo Ni, Yaqi Duan, Munther Dahleh et al.
Learning Mean-Field Games with Discounted and Average Costs
Berkay Anahtarci, Can Deha Kariksiz, Naci Saldi
Learning Optimal Feedback Operators and their Sparse Polynomial Approximations
Karl Kunisch, Donato Vásquez-Varas, Daniel Walter
Learning Optimal Group-structured Individualized Treatment Rules with Many Treatments
Haixu Ma, Donglin Zeng, Yufeng Liu
Learning Partial Differential Equations in Reproducing Kernel Hilbert Spaces
George Stepaniants