Copertina

A Geometric Unification of Distributionally Robust Covariance Estimators: Shrinking the Spectrum by Inflating the Ambiguity Set

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Yue, Man-Chung, Rychener, Yves, Kuhn, Daniel, Nguyen, Viet Anh
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Optimization and Control
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

SCOPE: Spectral Concentration by Distributionally Robust Joint Covariance-Precision Estimation
di: Chen, Renjie, et al.
Pubblicazione: (2025)

Metrizing Fairness
di: Rychener, Yves, et al.
Pubblicazione: (2022)

Global Group Fairness in Federated Learning via Function Tracking
di: Rychener, Yves, et al.
Pubblicazione: (2025)

Coverage-Validity-Aware Algorithmic Recourse
di: Bui, Ngoc, et al.
Pubblicazione: (2023)

Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning
di: Kuhn, Daniel, et al.
Pubblicazione: (2019)

Provably data-driven projection method for quadratic programming
di: Nguyen, Anh Tuan, et al.
Pubblicazione: (2025)

Distributionally Robust Regret Optimal Control Under Moment-Based Ambiguity Sets
di: Taha, Feras Al, et al.
Pubblicazione: (2025)

Decision Making under the Exponential Family: Distributionally Robust Optimisation with Bayesian Ambiguity Sets
di: Dellaporta, Charita, et al.
Pubblicazione: (2024)

Mean-Covariance Robust Risk Measurement
di: Nguyen, Viet Anh, et al.
Pubblicazione: (2021)

Distributional Surgery for Language Model Activations
di: Nguyen, Bao, et al.
Pubblicazione: (2025)

Wasserstein Distributionally Robust Optimization with Heterogeneous Data Sources
di: Rychener, Yves, et al.
Pubblicazione: (2024)

Selective Ambulance Dispatch Under Contextual Travel-Time Uncertainty
di: Lin, Zikun, et al.
Pubblicazione: (2026)

Efficient Algorithms for Robust Markov Decision Processes with $s$-Rectangular Ambiguity Sets
di: Ho, Chin Pang, et al.
Pubblicazione: (2026)

Distributionally Robust Optimization
di: Kuhn, Daniel, et al.
Pubblicazione: (2024)

A Hyper-Transformer model for Controllable Pareto Front Learning with Split Feasibility Constraints
di: Tuan, Tran Anh, et al.
Pubblicazione: (2024)

Unifying Distributionally Robust Optimization via Optimal Transport Theory
di: Blanchet, Jose, et al.
Pubblicazione: (2023)

Asymptotically Optimal Distributionally Robust Solutions through Forecasting and Operations Decentralization
di: Lin, Yue, et al.
Pubblicazione: (2024)

From Distributional Robustness to Robust Statistics: A Confidence Sets Perspective
di: Chan, Gabriel, et al.
Pubblicazione: (2024)

Online Covariance Estimation in Nonsmooth Stochastic Approximation
di: Jiang, Liwei, et al.
Pubblicazione: (2025)

Spatial Transformers for Radio Map Estimation
di: Viet, Pham Q., et al.
Pubblicazione: (2024)

Data-driven Reachable Set Estimation with Tunable Adversarial and Wasserstein Distributional Guarantees
di: Pantazis, Georgios, et al.
Pubblicazione: (2026)

Bayesian Ambiguity Contraction-based Adaptive Robust Markov Decision Processes for Adversarial Surveillance Missions
di: Choi, Jimin, et al.
Pubblicazione: (2025)

sparseGeoHOPCA: A Geometric Solution to Sparse Higher-Order PCA Without Covariance Estimation
di: Xu, Renjie, et al.
Pubblicazione: (2025)

Nash Equilibria, Regularization and Computation in Optimal Transport-Based Distributionally Robust Optimization
di: Shafiee, Soroosh, et al.
Pubblicazione: (2023)

A Novel Approach in Solving Stochastic Generalized Linear Regression via Nonconvex Programming
di: Anh, Vu Duc, et al.
Pubblicazione: (2024)

Distributionally Robust Deep Q-Learning
di: Lu, Chung I, et al.
Pubblicazione: (2025)

Distributionally Robust Density Control with Wasserstein Ambiguity Sets
di: Pilipovsky, Joshua, et al.
Pubblicazione: (2024)

Distributionally Robust LQG with Kullback-Leibler Ambiguity Sets
di: Fochesato, Marta, et al.
Pubblicazione: (2025)

Tight Robustness Certificates and Wasserstein Distributional Attacks for Deep Neural Networks
di: Le, Bach C., et al.
Pubblicazione: (2025)

Contextual Optimization under Covariate Shift: A Robust Approach by Intersecting Wasserstein Balls
di: Wang, Tianyu, et al.
Pubblicazione: (2024)

How to Set $β_1, β_2$ in Adam: An Online Learning Perspective
di: Nguyen, Quan
Pubblicazione: (2025)

Robustifying Conditional Portfolio Decisions via Optimal Transport
di: Nguyen, Viet Anh, et al.
Pubblicazione: (2021)

Quantum Learning and Estimation for Coordinated Operation between Distribution Networks and Energy Communities
di: Zhuang, Yingrui, et al.
Pubblicazione: (2025)

Convergence Analysis of the Lion Optimizer in Centralized and Distributed Settings
di: Jiang, Wei, et al.
Pubblicazione: (2025)

Distributionally Robust Optimization with Multimodal Decision-Dependent Ambiguity Sets
di: Yu, Xian, et al.
Pubblicazione: (2024)

Adaptive Distributionally Robust Optimal Control with Bayesian Ambiguity Sets
di: Ma, Wentao, et al.
Pubblicazione: (2026)

Nonlinear Distributionally Robust Optimization
di: Sheriff, Mohammed Rayyan, et al.
Pubblicazione: (2023)

Distributionally-Robust Learning to Optimize
di: Ranjan, Vinit, et al.
Pubblicazione: (2026)

Sinkhorn Distributionally Robust Optimization
di: Wang, Jie, et al.
Pubblicazione: (2021)

Online Optimization and Ambiguity-based Learning of Distributionally Uncertain Dynamic Systems
di: Li, Dan, et al.
Pubblicazione: (2021)