Summary of Limit Theorems For Stochastic Gradient Descent with Infinite Variance, by Jose Blanchet et al.
Limit Theorems for Stochastic Gradient Descent with Infinite Varianceby Jose Blanchet, Aleksandar Mijatović, Wenhao YangFirst…
Summary of Implicit Regularization Of Sharpness-aware Minimization For Scale-invariant Problems, by Bingcong Li et al.
Implicit Regularization of Sharpness-Aware Minimization for Scale-Invariant Problemsby Bingcong Li, Liang Zhang, Niao HeFirst submitted…
Summary of Double-bayesian Learning, by Stefan Jaeger
Double-Bayesian Learningby Stefan JaegerFirst submitted to arxiv on: 16 Oct 2024CategoriesMain: Machine Learning (cs.LG)Secondary: Neural…
Summary of Age-of-gradient Updates For Federated Learning Over Random Access Channels, by Yu Heng Wu et al.
Age-of-Gradient Updates for Federated Learning over Random Access Channelsby Yu Heng Wu, Houman Asgari, Stefano…
Summary of Hessian-informed Flow Matching, by Christopher Iliffe Sprague et al.
Hessian-Informed Flow Matchingby Christopher Iliffe Sprague, Arne Elofsson, Hossein AzizpourFirst submitted to arxiv on: 15…
Summary of Non-convergence to Global Minimizers in Data Driven Supervised Deep Learning: Adam and Stochastic Gradient Descent Optimization Provably Fail to Converge to Global Minimizers in the Training Of Deep Neural Networks with Relu Activation, by Thang Do and Sonja Hannibal and Arnulf Jentzen
Non-convergence to global minimizers in data driven supervised deep learning: Adam and stochastic gradient descent…
Summary of Sharpness-aware Minimization Efficiently Selects Flatter Minima Late in Training, by Zhanpeng Zhou et al.
Sharpness-Aware Minimization Efficiently Selects Flatter Minima Late in Trainingby Zhanpeng Zhou, Mingze Wang, Yuchen Mao,…
Summary of Simultaneous Computation and Memory Efficient Zeroth-order Optimizer For Fine-tuning Large Language Models, by Fei Wang et al.
Simultaneous Computation and Memory Efficient Zeroth-Order Optimizer for Fine-Tuning Large Language Modelsby Fei Wang, Li…
Summary of Learning Orthogonal Multi-index Models: a Fine-grained Information Exponent Analysis, by Yunwei Ren et al.
Learning Orthogonal Multi-Index Models: A Fine-Grained Information Exponent Analysisby Yunwei Ren, Jason D. LeeFirst submitted…
Summary of Zeroth-order Fine-tuning Of Llms in Random Subspaces, by Ziming Yu et al.
Zeroth-Order Fine-Tuning of LLMs in Random Subspacesby Ziming Yu, Pan Zhou, Sike Wang, Jia Li,…