Image de couverture de livre

Curl Descent: Non-Gradient Learning Dynamics with Sign-Diverse Plasticity

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Ninou, Hugo, Kadmon, Jonathan, Cayco-Gajic, N. Alex
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Geometry-aware similarity metrics for neural representations on Riemannian and statistical manifolds
par: Cayco-Gajic, N Alex, et autres
Publié: (2026)

Training Large Neural Networks With Low-Dimensional Error Feedback
par: Hanut, Maher, et autres
Publié: (2025)

On the Optimization and Generalization of Two-layer Transformers with Sign Gradient Descent
par: Li, Bingrui, et autres
Publié: (2024)

Robust Gradient Descent for Phase Retrieval
par: Buna, Alex, et autres
Publié: (2024)

Occam Gradient Descent
par: Kausik, B. N.
Publié: (2024)

Scaling Laws for Gradient Descent and Sign Descent for Linear Bigram Models under Zipf's Law
par: Kunstner, Frederik, et autres
Publié: (2025)

Adaptive Batch Sizes Using Non-Euclidean Gradient Noise Scales for Stochastic Sign and Spectral Descent
par: Naganuma, Hiroki, et autres
Publié: (2026)

How Transformers Learn Causal Structure with Gradient Descent
par: Nichani, Eshaan, et autres
Publié: (2024)

Improving Machine Learning Performance with Synthetic Augmentation
par: Sohm, Mel, et autres
Publié: (2026)

Towards Learning Stochastic Population Models by Gradient Descent
par: Kreikemeyer, Justin N., et autres
Publié: (2024)

Sign Gradient Descent-based Neuronal Dynamics: ANN-to-SNN Conversion Beyond ReLU Network
par: Oh, Hyunseok, et autres
Publié: (2024)

A Comprehensive Survey of Challenges and Opportunities of Few-Shot Learning Across Multiple Domains
par: Gajic, Andrea, et autres
Publié: (2025)

Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions In Context
par: Cheng, Xiang, et autres
Publié: (2023)

Distributed Gradient Descent for Functional Learning
par: Yu, Zhan, et autres
Publié: (2023)

Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs
par: Cheng, Wenhua, et autres
Publié: (2023)

Unraveling the Gradient Descent Dynamics of Transformers
par: Song, Bingqing, et autres
Publié: (2024)

Agnostic Learning of General ReLU Activation Using Gradient Descent
par: Awasthi, Pranjal, et autres
Publié: (2022)

Fast Robust Kernel Regression through Sign Gradient Descent with Early Stopping
par: Allerbo, Oskar
Publié: (2023)

Tight Generalization Error Bounds for Stochastic Gradient Descent in Non-convex Learning
par: Xiong, Wenjun, et autres
Publié: (2025)

Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging
par: AlQuabeh, Hilal, et autres
Publié: (2024)

A Mirror Descent Perspective of Smoothed Sign Descent
par: Wang, Shuyang, et autres
Publié: (2024)

Learning Tree-Based Models with Gradient Descent
par: Marton, Sascha
Publié: (2026)

Characterizing Dynamical Stability of Stochastic Gradient Descent in Overparameterized Learning
par: Chemnitz, Dennis, et autres
Publié: (2024)

Comparing the Moore-Penrose Pseudoinverse and Gradient Descent for Solving Linear Regression Problems: A Performance Analysis
par: Adams, Alex
Publié: (2025)

Non-Euclidean Gradient Descent Operates at the Edge of Stability
par: Islamov, Rustem, et autres
Publié: (2026)

An Exploration of Non-Euclidean Gradient Descent: Muon and its Many Variants
par: Crawshaw, Michael, et autres
Publié: (2025)

Learning Associative Memories with Gradient Descent
par: Cabannes, Vivien, et autres
Publié: (2024)

In-context Learning and Gradient Descent Revisited
par: Deutch, Gilad, et autres
Publié: (2023)

Dynamic Scaled Gradient Descent for Stable Fine-Tuning for Classifications
par: Bui, Nghia, et autres
Publié: (2026)

The role of gap junctions and clustered connectivity in emergent synchronisation patterns of inhibitory neuronal networks
par: Todd, Hélène, et autres
Publié: (2024)

Gradient Descent with Provably Tuned Learning-rate Schedules
par: Sharma, Dravyansh
Publié: (2025)

Learning Curves of Stochastic Gradient Descent in Kernel Regression
par: Zhang, Haihan, et autres
Publié: (2025)

Personalized Federated Learning with Exact Stochastic Gradient Descent
par: Nikoloutsopoulos, Sotirios, et autres
Publié: (2022)

Partially Lazy Gradient Descent for Smoothed Online Learning
par: Mhaisen, Naram, et autres
Publié: (2026)

Hybrid Coordinate Descent for Efficient Neural Network Learning Using Line Search and Gradient Descent
par: Hsiao, Yen-Che, et autres
Publié: (2024)

Stacking as Accelerated Gradient Descent
par: Agarwal, Naman, et autres
Publié: (2024)

Implicit Bias of Gradient Descent for Non-Homogeneous Deep Networks
par: Cai, Yuhang, et autres
Publié: (2025)

Matching the Statistical Query Lower Bound for $k$-Sparse Parity Problems with Sign Stochastic Gradient Descent
par: Kou, Yiwen, et autres
Publié: (2024)

Dynamic Decoupling of Placid Terminal Attractor-based Gradient Descent Algorithm
par: Zhao, Jinwei, et autres
Publié: (2024)

Stochastic Adaptive Gradient Descent Without Descent
par: Aujol, Jean-François, et autres
Publié: (2025)