:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Li, Junfan, Liao, Shizhong
Format:	Preprint
Published:	2022
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2212.12989
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learnability in Online Kernel Selection with Memory Constraint via Data-dependent Regret Analysis
by: Li, Junfan, et al.
Published: (2024)

A Polynomial-time Algorithm for Online Sparse Linear Regression with Improved Regret Bound under Weaker Conditions
by: Li, Junfan, et al.
Published: (2025)

Kernelized Reinforcement Learning with Order Optimal Regret Bounds
by: Vakili, Sattar, et al.
Published: (2023)

Regret Bounds for Noise-Free Cascaded Kernelized Bandits
by: Li, Zihan, et al.
Published: (2022)

Open Problem: Order Optimal Regret Bounds for Kernel-Based Reinforcement Learning
by: Vakili, Sattar
Published: (2024)

Dynamic Regret Reduces to Kernelized Static Regret
by: Jacobsen, Andrew, et al.
Published: (2025)

Tighter Regret Lower Bound for Gaussian Process Bandits with Squared Exponential Kernel in Hypersphere
by: Iwazaki, Shogo
Published: (2026)

Near-Optimal Regret in Adversarial Kernel Bandits
by: Zhang, Yu-Jie, et al.
Published: (2026)

Improved Regret Bounds for Online Fair Division with Bandit Learning
by: Schiffer, Benjamin, et al.
Published: (2025)

Gradient-Variation Regret Bounds for Unconstrained Online Learning
by: Zhao, Yuheng, et al.
Published: (2026)

Generalized Kernelized Bandits: A Novel Self-Normalized Bernstein-Like Dimension-Free Inequality and Regret Bounds
by: Metelli, Alberto Maria, et al.
Published: (2025)

Algorithms for Learning Kernels Based on Centered Alignment
by: Cortes, Corinna, et al.
Published: (2012)

Descriptive Kernel Convolution Network with Improved Random Walk Kernel
by: Lee, Meng-Chieh, et al.
Published: (2024)

Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel Machines
by: Milsom, Edward, et al.
Published: (2024)

Deep Hierarchical Graph Alignment Kernels
by: Tang, Shuhao, et al.
Published: (2024)

Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm
by: Vakili, Sattar, et al.
Published: (2024)

Data- and Variance-dependent Regret Bounds for Online Tabular MDPs
by: Li, Mingyi, et al.
Published: (2026)

Learning Analysis of Kernel Ridgeless Regression with Asymmetric Kernel Learning
by: He, Fan, et al.
Published: (2024)

Tighter Confidence Bounds for Sequential Kernel Regression
by: Flynn, Hamish, et al.
Published: (2024)

Improved Regret Bounds for Bandits with Expert Advice
by: Cesa-Bianchi, Nicolò, et al.
Published: (2024)

Optimistic Regret Bounds for Online Learning in Adversarial Markov Decision Processes
by: Moon, Sang Bin, et al.
Published: (2024)

Improving the Weighting Strategy in KernelSHAP
by: Olsen, Lars Henry Berge, et al.
Published: (2024)

Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning
by: Moradipari, Ahmadreza, et al.
Published: (2023)

Improved Dynamic Regret for Online Frank-Wolfe
by: Wan, Yuanyu, et al.
Published: (2023)

On the Necessity of Collaboration for Online Model Selection with Decentralized Data
by: Li, Junfan, et al.
Published: (2024)

Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion
by: Lee, Junghyun, et al.
Published: (2023)

Online-to-PAC Conversions: Generalization Bounds via Regret Analysis
by: Lugosi, Gábor, et al.
Published: (2023)

Lower Bounds for Time-Varying Kernelized Bandits
by: Cai, Xu, et al.
Published: (2024)

Manifold Approximation leads to Robust Kernel Alignment
by: Islam, Mohammad Tariqul, et al.
Published: (2025)

Regret-Optimal Federated Transfer Learning for Kernel Regression with Applications in American Option Pricing
by: Yang, Xuwei, et al.
Published: (2023)

On Improved Regret Bounds In Bayesian Optimization with Gaussian Noise
by: Wang, Jingyi, et al.
Published: (2024)

Alignment-Sensitive Minimax Rates for Spectral Algorithms with Learned Kernels
by: Huang, Dongming, et al.
Published: (2025)

Online Optimization for Learning to Communicate over Time-Correlated Channels
by: Wu, Zheshun, et al.
Published: (2024)

Correspondence of NNGP Kernel and the Matern Kernel
by: Muyskens, Amanda, et al.
Published: (2024)

Fast Second-Order Online Kernel Learning through Incremental Matrix Sketching and Decomposition
by: Wen, Dongxie, et al.
Published: (2024)

Estimating Bidirectional Causal Effects with Large Scale Online Kernel Learning
by: Tanaka, Masahiro
Published: (2025)

Large Dimensional Kernel Ridge Regression: Extending to Product Kernels
by: Zhou, Yang, et al.
Published: (2026)

Improved Regret Bounds for Gaussian Process Upper Confidence Bound in Bayesian Optimization
by: Iwazaki, Shogo
Published: (2025)

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations
by: Liu, Wei, et al.
Published: (2026)

Online Learning of Whittle Indices for Restless Bandits with Non-Stationary Transition Kernels
by: Shisher, Md Kamran Chowdhury, et al.
Published: (2025)