Cover Image

Diverse Dictionary Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zheng, Yujia, Li, Zijian, Fan, Shunxing, Wilson, Andrew Gordon, Zhang, Kun
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Higher-Order Causal Structure Learning with Additive Models
by: Enouen, James, et al.
Published: (2025)

Nonparametric Factor Analysis and Beyond
by: Zheng, Yujia, et al.
Published: (2025)

Optimism Stabilizes Thompson Sampling for Adaptive Inference
by: Yan, Shunxing, et al.
Published: (2026)

Robustness Against Weak or Invalid Instruments: Exploring Nonlinear Treatment Models with Machine Learning
by: Guo, Zijian, et al.
Published: (2022)

A Heteroskedasticity-Robust Overidentifying Restriction Test with High-Dimensional Covariates
by: Fan, Qingliang, et al.
Published: (2022)

Detecting and Identifying Selection Structure in Sequential Data
by: Zheng, Yujia, et al.
Published: (2024)

On the Role of Depth and Looping for In-Context Learning with Task Diversity
by: Gatmiry, Khashayar, et al.
Published: (2024)

Fundamental Computational Limits in Pursuing Invariant Causal Prediction and Invariance-Guided Regularization
by: Gu, Yihong, et al.
Published: (2025)

Unbalanced Optimal Transport Dictionary Learning for Unsupervised Hyperspectral Image Clustering
by: Lentz, Joshua, et al.
Published: (2026)

Local Learning for Covariate Selection in Nonparametric Causal Effect Estimation with Latent Variables
by: Li, Zheng, et al.
Published: (2024)

An Upper Confidence Bound Approach to Estimating the Maximum Mean
by: Kun, Zhang, et al.
Published: (2024)

Structured Matrix Learning under Arbitrary Entrywise Dependence and Estimation of Markov Transition Kernel
by: Chai, Jinhang, et al.
Published: (2024)

Robust Transfer Learning with Unreliable Source Data
by: Fan, Jianqing, et al.
Published: (2023)

Transformed $\ell_1$ Regularizations for Robust Principal Component Analysis: Toward a Fine-Grained Understanding
by: Zhao, Kun, et al.
Published: (2025)

Byzantine-Robust Distributed Sparse Learning Revisited
by: Wang, Yuxuan, et al.
Published: (2026)

Learning Spectral Methods by Transformers
by: He, Yihan, et al.
Published: (2025)

When can weak latent factors be statistically inferred?
by: Fan, Jianqing, et al.
Published: (2024)

Online Learning with Unknown Constraints
by: Sridharan, Karthik, et al.
Published: (2024)

Causal Invariance Learning via Efficient Nonconvex Optimization
by: Wang, Zhenyu, et al.
Published: (2024)

Wasserstein Transfer Learning
by: Zhang, Kaicheng, et al.
Published: (2025)

Optimal Demixing of Nonparametric Densities
by: Fan, Jianqing, et al.
Published: (2026)

Provable Sample-Efficient Transfer Learning Conditional Diffusion Models via Representation Learning
by: Cheng, Ziheng, et al.
Published: (2025)

SOFARI: High-Dimensional Manifold-Based Inference
by: Zheng, Zemin, et al.
Published: (2023)

Inverting estimating equations for causal inference on quantiles
by: Cheng, Chao, et al.
Published: (2024)

Transfer Learning for Nonparametric Contextual Dynamic Pricing
by: Wang, Fan, et al.
Published: (2025)

Perfect Clustering in Very Sparse Diverse Multiplex Networks
by: Pensky, Marianna
Published: (2025)

Hierarchical Contrastive Learning for Multimodal Data
by: Li, Huichao, et al.
Published: (2026)

Asymptotic Theory of Eigenvectors for Latent Embeddings with Generalized Laplacian Matrices
by: Fan, Jianqing, et al.
Published: (2025)

General Lower Bounds for Differentially Private Federated Learning with Arbitrary Public-Transcript Interactions
by: Li, Yicheng
Published: (2026)

Bounding Neyman-Pearson Region with $f$-Divergences
by: Mullhaupt, Andrew, et al.
Published: (2025)

Transfer Learning for Contextual Multi-armed Bandits
by: Cai, Changxiao, et al.
Published: (2022)

Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning
by: Li, Zijian, et al.
Published: (2025)

Minimax-Optimal Reward-Agnostic Exploration in Reinforcement Learning
by: Li, Gen, et al.
Published: (2023)

The Fragility of Optimized Bandit Algorithms
by: Fan, Lin, et al.
Published: (2021)

Learning Perturbations to Extrapolate Your LLM
by: Cen, Zetai, et al.
Published: (2026)

Nonlinear Meta-Learning Can Guarantee Faster Rates
by: Meunier, Dimitri, et al.
Published: (2023)

Plug-In Classification of Drift Functions in Diffusion Processes Using Neural Networks
by: Zhao, Yuzhen, et al.
Published: (2026)

Covariates-Adjusted Mixed-Membership Estimation: A Novel Network Model with Optimal Guarantees
by: Fan, Jianqing, et al.
Published: (2025)

Exogenous Randomness Empowering Random Forests
by: Mei, Tianxing, et al.
Published: (2024)

P-Tensors: a General Formalism for Constructing Higher Order Message Passing Networks
by: Hands, Andrew, et al.
Published: (2023)