:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Cichocki, Andrzej, Tanaka, Toshihisa, Nielsen, Frank, Cruces, Sergio
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	https://arxiv.org/abs/2503.08748
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Mirror Descent Using the Tempesta Generalized Multi-parametric Logarithms
di: Cichocki, Andrzej
Pubblicazione: (2025)

Generalized Exponentiated Gradient Algorithms and Their Application to On-Line Portfolio Selection
di: Cichocki, Andrzej, et al.
Pubblicazione: (2024)

Generalized Euler Logarithm and its Applications in Machine Learning: Natural Gradient, Backpropagation, Generalized EG, Mirror Descent and OLPS
di: Cichocki, Andrzej
Pubblicazione: (2025)

Automatically Differentiable Nonlinear Tensor Networks (ADNTNs) for Exponential Compression of Deep Neural Networks
di: Cichocki, Andrzej, et al.
Pubblicazione: (2026)

Group Entropies and Mirror Duality: A Class of Flexible Mirror Descent Updates for Machine Learning
di: Cichocki, Andrzej, et al.
Pubblicazione: (2026)

Gradient Descent Algorithm Survey
di: Fucheng, Deng, et al.
Pubblicazione: (2025)

Policy Mirror Descent with Lookahead
di: Protopapas, Kimon, et al.
Pubblicazione: (2024)

Stochastic Gradient Descent with Momentum is Algorithmically Stable
di: Lei, Yunwen, et al.
Pubblicazione: (2026)

Functional Acceleration for Policy Mirror Descent
di: Chelu, Veronica, et al.
Pubblicazione: (2024)

Bypassing the Exponential Dependency: Looped Transformers Efficiently Learn In-context by Multi-step Gradient Descent
di: Chen, Bo, et al.
Pubblicazione: (2024)

Efficient Search for Customized Activation Functions with Gradient Descent
di: Strack, Lukas, et al.
Pubblicazione: (2024)

StaQ it! Growing neural networks for Policy Mirror Descent
di: Shilova, Alena, et al.
Pubblicazione: (2025)

Adaptive Online Mirror Descent for Tchebycheff Scalarization in Multi-Objective Learning
di: Liu, Meitong, et al.
Pubblicazione: (2024)

Beyond State-Wise Mirror Descent: Offline Policy Optimization with Parametric Policies
di: Li, Xiang, et al.
Pubblicazione: (2026)

Randomness and Interpolation Improve Gradient Descent
di: Li, Jiawen, et al.
Pubblicazione: (2025)

ONG: Orthogonal Natural Gradient Descent
di: Yadav, Yajat, et al.
Pubblicazione: (2025)

Learning Associative Memories with Gradient Descent
di: Cabannes, Vivien, et al.
Pubblicazione: (2024)

Stochastic MeanFlow Policies: One-Step Generative Control with Entropic Mirror Descent
di: Wang, Zeyuan, et al.
Pubblicazione: (2026)

Policy Gradient with Adaptive Entropy Annealing for Continual Fine-Tuning
di: Zhang, Yaqian, et al.
Pubblicazione: (2026)

Adaptive Heavy-Tailed Stochastic Gradient Descent
di: Gong, Bodu, et al.
Pubblicazione: (2025)

Vanilla Gradient Descent for Oblique Decision Trees
di: Panda, Subrat Prasad, et al.
Pubblicazione: (2024)

Gradient Descent Efficiency Index
di: Dhingra, Aviral
Pubblicazione: (2024)

Optimizing Attention with Mirror Descent: Generalized Max-Margin Token Selection
di: Julistiono, Addison Kristanto, et al.
Pubblicazione: (2024)

The Initialization Determines Whether In-Context Learning Is Gradient Descent
di: Xie, Shifeng, et al.
Pubblicazione: (2025)

Elastic Multi-Gradient Descent for Parallel Continual Learning
di: Lyu, Fan, et al.
Pubblicazione: (2024)

Revisiting the Initial Steps in Adaptive Gradient Descent Optimization
di: Abuduweili, Abulikemu, et al.
Pubblicazione: (2024)

Conflict-Averse Gradient Descent for Multi-task Learning
di: Liu, Bo, et al.
Pubblicazione: (2021)

Noise Balance and Stationary Distribution of Stochastic Gradient Descent
di: Ziyin, Liu, et al.
Pubblicazione: (2023)

Can LLMs predict the convergence of Stochastic Gradient Descent?
di: Zekri, Oussama, et al.
Pubblicazione: (2024)

Local Entropy Search over Descent Sequences for Bayesian Optimization
di: Stenger, David, et al.
Pubblicazione: (2025)

Improving LLM General Preference Alignment via Optimistic Online Mirror Descent
di: Zhang, Yuheng, et al.
Pubblicazione: (2025)

Adaptive Batch Sizes Using Non-Euclidean Gradient Noise Scales for Stochastic Sign and Spectral Descent
di: Naganuma, Hiroki, et al.
Pubblicazione: (2026)

Enhancing Stochastic Gradient Descent: A Unified Framework and Novel Acceleration Methods for Faster Convergence
di: Deng, Yichuan, et al.
Pubblicazione: (2024)

Minimizing Weighted Counterfactual Regret with Optimistic Online Mirror Descent
di: Xu, Hang, et al.
Pubblicazione: (2024)

A Universal Banach--Bregman Framework for Stochastic Iterations: Unifying Stochastic Mirror Descent, Learning and LLM Training
di: Zhang, Johnny R., et al.
Pubblicazione: (2025)

Fisher-Orthogonal Projected Natural Gradient Descent for Continual Learning
di: Garg, Ishir, et al.
Pubblicazione: (2026)

Transformers Learn to Implement Multi-step Gradient Descent with Chain of Thought
di: Huang, Jianhao, et al.
Pubblicazione: (2025)

Geometrically Inspired Kernel Machines for Collaborative Learning Beyond Gradient Descent
di: Kumar, Mohit, et al.
Pubblicazione: (2024)

GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent
di: Marton, Sascha, et al.
Pubblicazione: (2023)

Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization
di: Kumar, Ramnath, et al.
Pubblicazione: (2023)