Cover Image

On decomposability and subdifferential of the tensor nuclear norm

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Guan, Jiewen, Jiang, Bo, Li, Zhening
Format:	Preprint
Published:	2025
Subjects:	Optimization and Control Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

$\ell_p$-sphere covering and approximating nuclear $p$-norm
by: Guan, Jiewen, et al.
Published: (2023)

On subdifferential chain rule of matrix factorization and beyond
by: Guan, Jiewen, et al.
Published: (2024)

$\ell_1$-norm rank-one symmetric matrix factorization has no spurious second-order stationary points
by: Guan, Jiewen, et al.
Published: (2024)

Failure of uniform laws of large numbers for subdifferentials and beyond
by: Tian, Lai, et al.
Published: (2025)

Accelerating nuclear-norm regularized low-rank matrix optimization through Burer-Monteiro decomposition
by: Lee, Ching-pei, et al.
Published: (2022)

l1-norm regularized l1-norm best-fit lines
by: Ling, Xiao, et al.
Published: (2024)

Sum-of-norms regularized Nonnegative Matrix Factorization
by: Ang, Andersen, et al.
Published: (2024)

On bounds for norms of reparameterized ReLU artificial neural network parameters: sums of fractional powers of the Lipschitz norm control the network parameter vector
by: Jentzen, Arnulf, et al.
Published: (2022)

Stochastic Halpern iteration in normed spaces and applications to reinforcement learning
by: Bravo, Mario, et al.
Published: (2024)

Constrained optimization of sensor placement for nuclear digital twins
by: Karnik, Niharika, et al.
Published: (2023)

The power of small initialization in noisy low-tubal-rank tensor recovery
by: Liu, ZHiyu, et al.
Published: (2026)

Federated Learning on Riemannian Manifolds: A Gradient-Free Projection-Based Approach
by: Wang, Hongye, et al.
Published: (2025)

Infinity-norm-based Input-to-State-Stable Long Short-Term Memory networks: a thermal systems perspective
by: De Carli, Stefano, et al.
Published: (2025)

Dynamic Rolling Horizon Optimization for Network-Constrained V2X Value Stacking of Electric Vehicles Under Uncertainties
by: Jiang, Canchen, et al.
Published: (2025)

Transit Network Design with Two-Level Demand Uncertainties: A Machine Learning and Contextual Stochastic Optimization Framework
by: Guan, Hongzhao, et al.
Published: (2026)

Efficient Duple Perturbation Robustness in Low-rank MDPs
by: Hu, Yang, et al.
Published: (2024)

Deep Generalized Schrödinger Bridges: From Image Generation to Solving Mean-Field Games
by: Liu, Guan-Horng, et al.
Published: (2024)

Provably Convergent Decentralized Optimization over Directed Graphs under Generalized Smoothness
by: Bo, Yanan, et al.
Published: (2026)

Quantization Avoids Saddle Points in Distributed Optimization
by: Bo, Yanan, et al.
Published: (2024)

Stability and Generalization for Distributed SGDA
by: Zhu, Miaoxi, et al.
Published: (2024)

Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding
by: Ren, Zhaolin, et al.
Published: (2023)

Natural Riemannian gradient for learning functional tensor networks
by: Klug, Nikolas, et al.
Published: (2026)

CaVE: A Cone-Aligned Approach for Fast Predict-then-optimize with Binary Linear Programs
by: Tang, Bo, et al.
Published: (2023)

On the Linear Speedup of Personalized Federated Reinforcement Learning with Shared Representations
by: Xiong, Guojun, et al.
Published: (2024)

Weakly Time-Coupled Approximation of Markov Decision Processes
by: Soheili, Negar, et al.
Published: (2026)

Learning to Optimize for Mixed-Integer Non-linear Programming with Feasibility Guarantees
by: Tang, Bo, et al.
Published: (2024)

Adjoint Schrödinger Bridge Sampler
by: Liu, Guan-Horng, et al.
Published: (2025)

Exploration from a Primal-Dual Lens: Value-Incentivized Actor-Critic Methods for Sample-Efficient Online RL
by: Yang, Tong, et al.
Published: (2025)

Continuous-time q-Learning for Jump-Diffusion Models under Tsallis Entropy
by: Bo, Lijun, et al.
Published: (2024)

Machine Learning-Augmented Optimization of Large Bilevel and Two-stage Stochastic Programs: Application to Cycling Network Design
by: Chan, Timothy C. Y., et al.
Published: (2022)

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

Stochastic Approximation with Block Coordinate Optimal Stepsizes
by: Jiang, Tao, et al.
Published: (2025)

Achieving Instance-dependent Sample Complexity for Constrained Markov Decision Process
by: Jiang, Jiashuo, et al.
Published: (2024)

Instance-optimal stochastic convex optimization: Can we improve upon sample-average and robust stochastic approximation?
by: Jiang, Liwei, et al.
Published: (2026)

SOREL: A Stochastic Algorithm for Spectral Risks Minimization
by: Ge, Yuze, et al.
Published: (2024)

Online Learning Guided Quasi-Newton Methods with Global Non-Asymptotic Convergence
by: Jiang, Ruichen, et al.
Published: (2024)

Generalized Schrödinger Bridge Matching
by: Liu, Guan-Horng, et al.
Published: (2023)

Improving Convergence and Generalization Using Parameter Symmetries
by: Zhao, Bo, et al.
Published: (2023)

On the B-subdifferential of proximal operators of affine-constrained $\ell_1$ regularizer
by: Li, Xudong, et al.
Published: (2025)

Optimality conditions and subdifferential calculus for infinite sums of functions
by: Hantoute, Abderrahim, et al.
Published: (2024)