Copertina

A Novel Approach in Solving Stochastic Generalized Linear Regression via Nonconvex Programming

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Anh, Vu Duc, Tuan, Tran Anh, Thang, Tran Ngoc, Anh, Nguyen Thi Ngoc
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

A Steepest Gradient Method with Nonmonotone Adaptive Step-sizes for the Nonconvex Minimax and Multi-Objective Optimization Problems
di: Anh, Nguyen Duc, et al.
Pubblicazione: (2025)

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

Adaptive multi-gradient methods for quasiconvex vector optimization and applications to multi-task learning
di: Minh, Nguyen Anh, et al.
Pubblicazione: (2024)

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

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

Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization
di: Tran-Dinh, Quoc, et al.
Pubblicazione: (2024)

(Accelerated) Noise-adaptive Stochastic Heavy-Ball Momentum
di: Dang, Anh, et al.
Pubblicazione: (2024)

A Two-Phase Adaptive Balanced Penalty Method for Controllable Pareto Front Learning under Split Feasibility Conditions
di: Hoang, Nguyen Viet, et al.
Pubblicazione: (2026)

A mathematical framework for time-delay reservoir computing analysis
di: Clabaut, Anh-Tuan, et al.
Pubblicazione: (2026)

Adjusted Shuffling SARAH: Advancing Complexity Analysis via Dynamic Gradient Weighting
di: Nguyen, Duc Toan, et al.
Pubblicazione: (2025)

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

Moment Sum-of-Squares Hierarchy for Gromov Wasserstein: Continuous Extensions and Sample Complexity
di: Tran, Hoang Anh, et al.
Pubblicazione: (2025)

Sum-of-Squares Hierarchy for the Gromov Wasserstein Problem
di: Tran, Hoang Anh, et al.
Pubblicazione: (2025)

Tractable hierarchies of convex relaxations for polynomial optimization on the nonnegative orthant
di: Mai, Ngoc Hoang Anh, et al.
Pubblicazione: (2022)

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

Solving a Class of Nonconvex Quadratic Programs by Inertial DC Algorithms
di: Cuong, Tran Hung, et al.
Pubblicazione: (2024)

A Geometric Unification of Distributionally Robust Covariance Estimators: Shrinking the Spectrum by Inflating the Ambiguity Set
di: Yue, Man-Chung, et al.
Pubblicazione: (2024)

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

Private Zeroth-Order Nonsmooth Nonconvex Optimization
di: Zhang, Qinzi, et al.
Pubblicazione: (2024)

Stochastic Smoothed Primal-Dual Algorithms for Nonconvex Optimization with Linear Inequality Constraints
di: Huang, Ruichuan, et al.
Pubblicazione: (2025)

Stable Nonconvex-Nonconcave Training via Linear Interpolation
di: Pethick, Thomas, et al.
Pubblicazione: (2023)

Layer-wise Quantization for Quantized Optimistic Dual Averaging
di: Nguyen, Anh Duc, et al.
Pubblicazione: (2025)

Bregman Linearized Augmented Lagrangian Method for Nonconvex Constrained Stochastic Zeroth-order Optimization
di: Shi, Qiankun, et al.
Pubblicazione: (2025)

Fréchet Regression on the Bures-Wasserstein Manifold
di: Nguyen, Duc Toan, et al.
Pubblicazione: (2026)

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

FAIREDU: A Multiple Regression-Based Method for Enhancing Fairness in Machine Learning Models for Educational Applications
di: Pham, Nga, et al.
Pubblicazione: (2024)

VFOG: Variance-Reduced Fast Optimistic Gradient Methods for a Class of Nonmonotone Generalized Equations
di: Tran-Dinh, Quoc, et al.
Pubblicazione: (2025)

Decentralized Federated Learning with Gradient Tracking over Time-Varying Directed Networks
di: Nguyen, Duong Thuy Anh, et al.
Pubblicazione: (2024)

On the convergence rates of moment-SOS hierarchies approximation of truncated moment sequences
di: Tran, Hoang Anh, et al.
Pubblicazione: (2025)

Shuffling Momentum Gradient Algorithm for Convex Optimization
di: Tran, Trang H., et al.
Pubblicazione: (2024)

MicroRicci: A Greedy and Local Ricci Flow Solver for Self-Tuning Mesh Smoothing
di: Anh, Le Vu, et al.
Pubblicazione: (2025)

Improved Rates for Stochastic Variance-Reduced Difference-of-Convex Algorithms
di: Nguyen, Anh Duc, et al.
Pubblicazione: (2025)

Constrained Stochastic Spectral Preconditioning Converges for Nonconvex Objectives
di: Oikonomidis, Konstantinos, et al.
Pubblicazione: (2026)

Decentralized Stochastic Nonconvex Optimization under the Relaxed Smoothness
di: Luo, Luo, et al.
Pubblicazione: (2025)

In-Context Learning for Data-Driven Censored Inventory Control
di: Mukherjee, Sohom, et al.
Pubblicazione: (2026)

Quantum speed-ups for solving semidefinite relaxations of polynomial optimization
di: França, Daniel Stilck, et al.
Pubblicazione: (2025)

Nonconvex Optimization Framework for Group-Sparse Feedback Linear-Quadratic Optimal Control: Penalty Approach
di: Feng, Lechen, et al.
Pubblicazione: (2025)

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

Convergence analysis of multi-step one-shot methods for linear inverse problems
di: Bonazzoli, Marcella, et al.
Pubblicazione: (2022)

Zeroth-Order Methods for Stochastic Nonconvex Nonsmooth Composite Optimization
di: Chen, Ziyi, et al.
Pubblicazione: (2025)