"gradient descent optimization" Papers
11 papers found
Conference
Curl Descent : Non-Gradient Learning Dynamics with Sign-Diverse Plasticity
Hugo Ninou, Jonathan Kadmon, N Alex Cayco Gajic
NEURIPS 2025spotlightarXiv:2510.02765
Gradient descent with generalized Newton’s method
Zhiqi Bu, Shiyun Xu
ICLR 2025arXiv:2407.02772
8
citations
Scaling Laws for Gradient Descent and Sign Descent for Linear Bigram Models under Zipf’s Law
Frederik Kunstner, Francis Bach
NEURIPS 2025arXiv:2505.19227
12
citations
Variational Inference with Mixtures of Isotropic Gaussians
Marguerite Petit-Talamon, Marc Lambert, Anna Korba
NEURIPS 2025arXiv:2506.13613
Benign Overfitting in Two-Layer ReLU Convolutional Neural Networks for XOR Data
Xuran Meng, Difan Zou, Yuan Cao
ICML 2024arXiv:2310.01975
10
citations
How Graph Neural Networks Learn: Lessons from Training Dynamics
Chenxiao Yang, Qitian Wu, David Wipf et al.
ICML 2024arXiv:2310.05105
2
citations
Improving Sharpness-Aware Minimization by Lookahead
Runsheng Yu, Youzhi Zhang, James Kwok
ICML 2024
LoRA Training in the NTK Regime has No Spurious Local Minima
Uijeong Jang, Jason Lee, Ernest Ryu
ICML 2024arXiv:2402.11867
35
citations
Offline and Online Optical Flow Enhancement for Deep Video Compression
Chuanbo Tang, Xihua Sheng, Zhuoyuan Li et al.
AAAI 2024paperarXiv:2307.05092
28
citations
QLABGrad: A Hyperparameter-Free and Convergence-Guaranteed Scheme for Deep Learning
Fang-Xiang Wu, Minghan Fu
AAAI 2024paperarXiv:2302.00252
12
citations
Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians
Tom Huix, Anna Korba, Alain Oliviero Durmus et al.
ICML 2024arXiv:2406.04012
10
citations