Image de couverture de livre

Break recovery in graphical networks with D-trace loss

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Lin, Ying, Poignard, Benjamin, Pong, Ting Kei, Takeda, Akiko
Format:	Preprint
Publié:	2024
Sujets:	Statistics Theory 62F12, 90C25, 90C90
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Low Rank Convex Clustering For Matrix-Valued Observations
par: Lin, Meixia, et autres
Publié: (2024)

Bayesian Multi-Topology Express Transportation Network Design under Posterior Predictive Demand, Sorting-Efficiency and Delivery-Time Uncertainty
par: Chatterjee, Debashis
Publié: (2026)

Low solution rank of the matrix LASSO under RIP with consequences for rank-constrained algorithms
par: McRae, Andrew D.
Publié: (2024)

On robust recovery of signals from indirect observations
par: Bekri, Yannis, et autres
Publié: (2025)

Regularized Rényi divergence minimization through Bregman proximal gradient algorithms
par: Guilmeau, Thomas, et autres
Publié: (2022)

Estimating the errors for solutions of the SAA method to solve compound and risk averse stochastic programs
par: Kratschmer, Volker
Publié: (2021)

The radius of statistical efficiency
par: Cutler, Joshua, et autres
Publié: (2024)

Inference for max-linear Bayesian networks with noise
par: Adams, Mark, et autres
Publié: (2025)

Identifiable Convex-Concave Regression via Sub-gradient Regularised Least Squares
par: Chung, William
Publié: (2025)

Marginal minimization and sup-norm expansions in perturbed optimization
par: Spokoiny, Vladimir
Publié: (2025)

Entropy-Guided Multiplicative Updates: KL Projections for Multi-Factor Target Exposures
par: Qiu, Yimeng
Publié: (2025)

Fast Frank--Wolfe Algorithms with Adaptive Bregman Step-Size for Weakly Convex Functions
par: Takahashi, Shota, et autres
Publié: (2025)

Kurdyka-Łojasiewicz exponent via Hadamard parametrization
par: Ouyang, Wenqing, et autres
Publié: (2024)

Tight Semidefinite Relaxations for Verifying Robustness of Neural Networks
par: Azuma, Godai, et autres
Publié: (2025)

Measure This, Not That: Optimizing the Cost and Model-Based Information Content of Measurements
par: Wang, Jialu, et autres
Publié: (2024)

Generalized Scaling for the Constrained Maximum-Entropy Sampling Problem
par: Chen, Zhongzhu, et autres
Publié: (2023)

From Non-Identifiability to Goal-Integrated Decision-Making in Parametric Inverse Optimization
par: Ahmadi, Farzin, et autres
Publié: (2026)

Vanishing L2 regularization for the softmax Multi Armed Bandit
par: Anita, Stefana-Lucia, et autres
Publié: (2026)

Efficient Data-Driven Leverage Score Sampling Algorithm for the Minimum Volume Covering Ellipsoid Problem in Big Data
par: Harris, Elizabeth, et autres
Publié: (2024)

Sharp bounds in perturbed smooth optimization
par: Spokoiny, Vladimir
Publié: (2025)

Asymptotic Consistency for Nonconvex Risk-Averse Stochastic Optimization with Infinite Dimensional Decision Spaces
par: Milz, Johannes, et autres
Publié: (2022)

On Difference-of-SOS and Difference-of-Convex-SOS Decompositions for Polynomials
par: Niu, Yi-Shuai, et autres
Publié: (2018)

Robust Moment-Based Estimation via Spectral Gradient Reweighting
par: Zhang, Liu, et autres
Publié: (2026)

Removal of Redundant Candidate Points for the Exact D-Optimal Design Problem
par: Harman, Radoslav, et autres
Publié: (2025)

A Regression-Based Prediction-Correction Method for Stochastic Time-Varying Optimization Problems
par: Kamijima, Tomoya, et autres
Publié: (2025)

Quantifying the Value of Seismic Structural Health Monitoring for post-earthquake recovery of electric power system in terms of resilience enhancement
par: Liang, Huangbin, et autres
Publié: (2025)

Entropic Risk-Averse Generalized Momentum Methods
par: Can, Bugra, et autres
Publié: (2022)

Geometry of rational quasi-independence models as toric fiber products
par: Coons, Jane Ivy, et autres
Publié: (2024)

Bayesian Linear Programming under Learned Uncertainty: Posterior Feasibility Guarantees, Scenario Certification, and Applications
par: Chatterjee, Debashis
Publié: (2026)

Randomized Subspace Nesterov Accelerated Gradient
par: Omiya, Gaku, et autres
Publié: (2026)

A Benson-Type Algorithm for Bounded Convex Vector Optimization Problems with Vertex Selection
par: Dörfler, Daniel, et autres
Publié: (2020)

On $O(n)$ Algorithms for Projection onto the Top-$k$-sum Sublevel Set
par: Roth, Jake, et autres
Publié: (2023)

A symmetric primal-dual algorithmic framework for saddle point problems
par: He, Hongjin, et autres
Publié: (2022)

An efficient proximal algorithm for squared L1 over L2 regularized sparse recovery
par: Zhang, Na, et autres
Publié: (2025)

Polynomial-Time Algorithms for Computing the Nucleolus: An Assessment
par: Meinhardt, Holger I.
Publié: (2025)

Global optimality conditions for sensor placement, with extensions to binary low-rank A-optimal designs
par: Aarset, Christian
Publié: (2024)

Zeroth-order Random Subspace Algorithm for Non-smooth Convex Optimization
par: Nozawa, Ryota, et autres
Publié: (2024)

A Riemannian Accelerated Proximal Gradient Method
par: Feng, Shuailing, et autres
Publié: (2025)

A feasible smoothing accelerated projected gradient method for nonsmooth convex optimization
par: Nishioka, Akatsuki, et autres
Publié: (2023)

Long-Step Path-Following Algorithm for Quantum Information Theory: Some Numerical Aspects and Applications
par: Faybusovich, Leonid, et autres
Publié: (2019)