:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Cichocki, Andrzej
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2502.17500
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Mirror Descent and Novel Exponentiated Gradient Algorithms Using Trace-Form Entropies and Deformed Logarithms
by: Cichocki, Andrzej, et al.
Published: (2025)

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

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

ONG: Orthogonal Natural Gradient Descent
by: Yadav, Yajat, et al.
Published: (2025)

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

Policy Mirror Descent with Lookahead
by: Protopapas, Kimon, et al.
Published: (2024)

Randomized Advantage Transformation (RAT): Computing Natural Policy Gradients via Direct Backpropagation
by: Sun, Mingfei
Published: (2026)

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

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

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

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

Natural Gradient Descent for Online Continual Learning
by: Khawand, Joe, et al.
Published: (2026)

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

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

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

GRADE: Replacing Policy Gradients with Backpropagation for LLM Alignment
by: Nel, Lukas Abrie
Published: (2025)

Beyond Backpropagation: Optimization with Multi-Tangent Forward Gradients
by: Flügel, Katharina, et al.
Published: (2024)

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

Optimization, Generalization and Differential Privacy Bounds for Gradient Descent on Kolmogorov-Arnold Networks
by: Wang, Puyu, et al.
Published: (2026)

Geodesic Gradient Descent: A Generic and Learning-rate-free Optimizer on Objective Function-induced Manifolds
by: Hu, Liwei, et al.
Published: (2026)

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

Reconstructing Deep Neural Networks: Unleashing the Optimization Potential of Natural Gradient Descent
by: Liu, Weihua, et al.
Published: (2024)

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

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

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

Gradient Descent Algorithm Survey
by: Fucheng, Deng, et al.
Published: (2025)

Asynchronous Stochastic Gradient Descent with Decoupled Backpropagation and Layer-Wise Updates
by: Fokam, Cabrel Teguemne, et al.
Published: (2024)

Beyond the Mean: Fisher-Orthogonal Projection for Natural Gradient Descent in Large Batch Training
by: Lu, Yishun, et al.
Published: (2025)

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

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

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

Practical Boolean Backpropagation
by: Golbert, Simon
Published: (2025)

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

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

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

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

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

Hyperdimensional Vector Tsetlin Machines with Applications to Sequence Learning and Generation
by: Blakely, Christian D.
Published: (2024)

Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning?
by: Gatmiry, Khashayar, et al.
Published: (2024)