Poster "neural network training" Papers
13 papers found
Accelerating neural network training: An analysis of the AlgoPerf competition
Priya Kasimbeg, Frank Schneider, Runa Eschenhagen et al.
ICLR 2025posterarXiv:2502.15015
17
citations
ADAM Optimization with Adaptive Batch Selection
Gyu Yeol Kim, Min-hwan Oh
ICLR 2025posterarXiv:2512.06795
1
citations
Block Coordinate Descent for Neural Networks Provably Finds Global Minima
Shunta Akiyama
NEURIPS 2025posterarXiv:2510.22667
2
citations
Efficient Representativeness-Aware Coreset Selection
Zihao Cheng, Binrui Wu, Zhiwei Li et al.
NEURIPS 2025poster
KOALA++: Efficient Kalman-Based Optimization with Gradient-Covariance Products
Zixuan XIa, Aram Davtyan, Paolo Favaro
NEURIPS 2025posterarXiv:2506.04432
Learn2Mix: Training Neural Networks Using Adaptive Data Integration
Shyam Venkatasubramanian, Vahid Tarokh
NEURIPS 2025posterarXiv:2412.16482
2
citations
Learning High-Degree Parities: The Crucial Role of the Initialization
Emmanuel Abbe, Elisabetta Cornacchia, Jan Hązła et al.
ICLR 2025posterarXiv:2412.04910
3
citations
RTop-K: Ultra-Fast Row-Wise Top-K Selection for Neural Network Acceleration on GPUs
Xi Xie, Yuebo Luo, Hongwu Peng et al.
ICLR 2025posterarXiv:2409.00822
2
citations
Sinusoidal Initialization, Time for a New Start
Alberto Fernandez-Hernandez, Jose Mestre, Manuel F. Dolz et al.
NEURIPS 2025posterarXiv:2505.12909
1
citations
Efficient Algorithms for Sum-Of-Minimum Optimization
Lisang Ding, Ziang Chen, Xinshang Wang et al.
ICML 2024posterarXiv:2402.07070
Online Learning and Information Exponents: The Importance of Batch size & Time/Complexity Tradeoffs
Luca Arnaboldi, Yatin Dandi, FLORENT KRZAKALA et al.
ICML 2024poster
Random Scaling and Momentum for Non-smooth Non-convex Optimization
Qinzi Zhang, Ashok Cutkosky
ICML 2024posterarXiv:2405.09742
Spectral Preconditioning for Gradient Methods on Graded Non-convex Functions
Nikita Doikov, Sebastian Stich, Martin Jaggi
ICML 2024posterarXiv:2402.04843