Saved in:
| Main Author: | Cichocki, Andrzej |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.13984 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Generalized Euler Logarithm and its Applications in Machine Learning: Natural Gradient, Backpropagation, Generalized EG, Mirror Descent and OLPS
by: Cichocki, Andrzej
Published: (2025)
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)
by: Cichocki, Andrzej, et al.
Published: (2025)
Automatically Differentiable Nonlinear Tensor Networks (ADNTNs) for Exponential Compression of Deep Neural Networks
by: Cichocki, Andrzej, et al.
Published: (2026)
by: Cichocki, Andrzej, et al.
Published: (2026)
Group Entropies and Mirror Duality: A Class of Flexible Mirror Descent Updates for Machine Learning
by: Cichocki, Andrzej, et al.
Published: (2026)
by: Cichocki, Andrzej, et al.
Published: (2026)
Policy Mirror Descent with Lookahead
by: Protopapas, Kimon, et al.
Published: (2024)
by: Protopapas, Kimon, et al.
Published: (2024)
Functional Acceleration for Policy Mirror Descent
by: Chelu, Veronica, et al.
Published: (2024)
by: Chelu, Veronica, et al.
Published: (2024)
Adaptive Online Mirror Descent for Tchebycheff Scalarization in Multi-Objective Learning
by: Liu, Meitong, et al.
Published: (2024)
by: Liu, Meitong, et al.
Published: (2024)
Stochastic MeanFlow Policies: One-Step Generative Control with Entropic Mirror Descent
by: Wang, Zeyuan, et al.
Published: (2026)
by: Wang, Zeyuan, et al.
Published: (2026)
StaQ it! Growing neural networks for Policy Mirror Descent
by: Shilova, Alena, et al.
Published: (2025)
by: Shilova, Alena, et al.
Published: (2025)
Optimizing Attention with Mirror Descent: Generalized Max-Margin Token Selection
by: Julistiono, Addison Kristanto, et al.
Published: (2024)
by: Julistiono, Addison Kristanto, et al.
Published: (2024)
Improving LLM General Preference Alignment via Optimistic Online Mirror Descent
by: Zhang, Yuheng, et al.
Published: (2025)
by: Zhang, Yuheng, et al.
Published: (2025)
Beyond State-Wise Mirror Descent: Offline Policy Optimization with Parametric Policies
by: Li, Xiang, et al.
Published: (2026)
by: Li, Xiang, et al.
Published: (2026)
Minimizing Weighted Counterfactual Regret with Optimistic Online Mirror Descent
by: Xu, Hang, et al.
Published: (2024)
by: Xu, Hang, et al.
Published: (2024)
A Universal Banach--Bregman Framework for Stochastic Iterations: Unifying Stochastic Mirror Descent, Learning and LLM Training
by: Zhang, Johnny R., et al.
Published: (2025)
by: Zhang, Johnny R., et al.
Published: (2025)
Configurable Mirror Descent: Towards a Unification of Decision Making
by: Li, Pengdeng, et al.
Published: (2024)
by: Li, Pengdeng, et al.
Published: (2024)
Reference-Sampled Boltzmann Projection for KL-Regularized RLVR: Target-Matched Weighted SFT, Finite One-Shot Gaps, and Policy Mirror Descent
by: Shu, Yao, et al.
Published: (2026)
by: Shu, Yao, et al.
Published: (2026)
Elastic Multi-Gradient Descent for Parallel Continual Learning
by: Lyu, Fan, et al.
Published: (2024)
by: Lyu, Fan, et al.
Published: (2024)
Conflict-Averse Gradient Descent for Multi-task Learning
by: Liu, Bo, et al.
Published: (2021)
by: Liu, Bo, et al.
Published: (2021)
Plasticity as the Mirror of Empowerment
by: Abel, David, et al.
Published: (2025)
by: Abel, David, et al.
Published: (2025)
PSMGD: Periodic Stochastic Multi-Gradient Descent for Fast Multi-Objective Optimization
by: Xu, Mingjing, et al.
Published: (2024)
by: Xu, Mingjing, et al.
Published: (2024)
Jacobian Descent for Multi-Objective Optimization
by: Quinton, Pierre, et al.
Published: (2024)
by: Quinton, Pierre, et al.
Published: (2024)
Transformers Learn to Implement Multi-step Gradient Descent with Chain of Thought
by: Huang, Jianhao, et al.
Published: (2025)
by: Huang, Jianhao, et al.
Published: (2025)
Embodied-RAG: General Non-parametric Embodied Memory for Retrieval and Generation
by: Xie, Quanting, et al.
Published: (2024)
by: Xie, Quanting, et al.
Published: (2024)
Optimization, Generalization and Differential Privacy Bounds for Gradient Descent on Kolmogorov-Arnold Networks
by: Wang, Puyu, et al.
Published: (2026)
by: Wang, Puyu, et al.
Published: (2026)
Bitwidth-Specific Logarithmic Arithmetic for Future Hardware-Accelerated Training
by: Hamad, Hassan, et al.
Published: (2025)
by: Hamad, Hassan, et al.
Published: (2025)
Gradient Descent Algorithm Survey
by: Fucheng, Deng, et al.
Published: (2025)
by: Fucheng, Deng, et al.
Published: (2025)
Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning?
by: Gatmiry, Khashayar, et al.
Published: (2024)
by: Gatmiry, Khashayar, et al.
Published: (2024)
Multi-Horizon Time Series Forecasting of non-parametric CDFs with Deep Lattice Networks
by: Erdmann, Niklas, et al.
Published: (2025)
by: Erdmann, Niklas, et al.
Published: (2025)
Bypassing the Exponential Dependency: Looped Transformers Efficiently Learn In-context by Multi-step Gradient Descent
by: Chen, Bo, et al.
Published: (2024)
by: Chen, Bo, et al.
Published: (2024)
Randomness and Interpolation Improve Gradient Descent
by: Li, Jiawen, et al.
Published: (2025)
by: Li, Jiawen, et al.
Published: (2025)
ONG: Orthogonal Natural Gradient Descent
by: Yadav, Yajat, et al.
Published: (2025)
by: Yadav, Yajat, et al.
Published: (2025)
Optimizing ML Training with Metagradient Descent
by: Engstrom, Logan, et al.
Published: (2025)
by: Engstrom, Logan, et al.
Published: (2025)
Learning Associative Memories with Gradient Descent
by: Cabannes, Vivien, et al.
Published: (2024)
by: Cabannes, Vivien, et al.
Published: (2024)
Mirror Learning: A Unifying Framework of Policy Optimisation
by: Kuba, Jakub Grudzien, et al.
Published: (2022)
by: Kuba, Jakub Grudzien, et al.
Published: (2022)
Adaptive Batch Sizes Using Non-Euclidean Gradient Noise Scales for Stochastic Sign and Spectral Descent
by: Naganuma, Hiroki, et al.
Published: (2026)
by: Naganuma, Hiroki, et al.
Published: (2026)
Scalable Community Detection Using Quantum Hamiltonian Descent and QUBO Formulation
by: Cheng, Jinglei, et al.
Published: (2024)
by: Cheng, Jinglei, et al.
Published: (2024)
Adaptive Heavy-Tailed Stochastic Gradient Descent
by: Gong, Bodu, et al.
Published: (2025)
by: Gong, Bodu, et al.
Published: (2025)
On The Presence of Double-Descent in Deep Reinforcement Learning
by: Veselý, Viktor, et al.
Published: (2025)
by: Veselý, Viktor, et al.
Published: (2025)
Vanilla Gradient Descent for Oblique Decision Trees
by: Panda, Subrat Prasad, et al.
Published: (2024)
by: Panda, Subrat Prasad, et al.
Published: (2024)
Stochastic Gradient Descent with Momentum is Algorithmically Stable
by: Lei, Yunwen, et al.
Published: (2026)
by: Lei, Yunwen, et al.
Published: (2026)
Similar Items
-
Generalized Euler Logarithm and its Applications in Machine Learning: Natural Gradient, Backpropagation, Generalized EG, Mirror Descent and OLPS
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) -
Automatically Differentiable Nonlinear Tensor Networks (ADNTNs) for Exponential Compression of Deep Neural Networks
by: Cichocki, Andrzej, et al.
Published: (2026) -
Group Entropies and Mirror Duality: A Class of Flexible Mirror Descent Updates for Machine Learning
by: Cichocki, Andrzej, et al.
Published: (2026) -
Policy Mirror Descent with Lookahead
by: Protopapas, Kimon, et al.
Published: (2024)