Adaptive Gradient Normalization and Independent Sampling for (Stochastic) Generalized-Smooth Optimization

Posted by klaurent UCAS

Kavli Affiliate: Yi Zhou | First 5 Authors: Yufeng Yang, Yufeng Yang, , , | Summary: Recent studies have shown that many nonconvex machine learning problems satisfy a generalized-smooth condition that extends beyond traditional smooth nonconvex optimization. However, the existing algorithms are not fully adapted to such generalized-smooth nonconvex geometry and encounter significant technical limitations […]


Continue.. Adaptive Gradient Normalization and Independent Sampling for (Stochastic) Generalized-Smooth Optimization

Independently-Normalized SGD for Generalized-Smooth Nonconvex Optimization

Posted by dbos UCAS

Kavli Affiliate: Yi Zhou | First 5 Authors: Yufeng Yang, Erin Tripp, Yifan Sun, Shaofeng Zou, Yi Zhou | Summary: Recent studies have shown that many nonconvex machine learning problems meet a so-called generalized-smooth condition that extends beyond traditional smooth nonconvex optimization. However, the existing algorithms designed for generalized-smooth nonconvex optimization encounter significant limitations in […]


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Optimal Communication and Key Rate Region for Hierarchical Secure Aggregation with User Collusion

Posted by dbos Berkeley

Kavli Affiliate: Xiang Zhang | First 5 Authors: Xiang Zhang, Kai Wan, Hua Sun, Shiqiang Wang, Mingyue Ji | Summary: Secure aggregation is concerned with the task of securely uploading the inputs of multiple users to an aggregation server without letting the server know the inputs beyond their summation. It finds broad applications in distributed […]


Continue.. Optimal Communication and Key Rate Region for Hierarchical Secure Aggregation with User Collusion

Optimal Communication and Key Rate Region for Hierarchical Secure Aggregation with User Collusion

Posted by dbos Berkeley

Kavli Affiliate: Xiang Zhang | First 5 Authors: Xiang Zhang, Kai Wan, Hua Sun, Shiqiang Wang, Mingyue Ji | Summary: Secure aggregation is concerned with the task of securely uploading the inputs of multiple users to an aggregation server without letting the server know the inputs beyond their summation. It finds broad applications in distributed […]


Continue.. Optimal Communication and Key Rate Region for Hierarchical Secure Aggregation with User Collusion

Optimal Communication and Key Rate Region for Hierarchical Secure Aggregation with User Collusion

Posted by dbos Berkeley

Kavli Affiliate: Xiang Zhang | First 5 Authors: Xiang Zhang, Kai Wan, Hua Sun, Shiqiang Wang, Mingyue Ji | Summary: Secure aggregation is concerned with the task of securely uploading the inputs of multiple users to an aggregation server without letting the server know the inputs beyond their summation. It finds broad applications in distributed […]


Continue.. Optimal Communication and Key Rate Region for Hierarchical Secure Aggregation with User Collusion

GRB Redshift Estimation using Machine Learning and the Associated Web-App

Posted by dbos Stanford

Kavli Affiliate: Vahe Petrosian | First 5 Authors: Aditya Narendra, Maria Dainotti, Milind Sarkar, Aleksander Lenart, Malgorzata Bogdan | Summary: Context. Gamma-ray bursts (GRBs), observed at redshifts as high as 9.4, could serve as valuable probes for investigating the distant Universe. However, this necessitates an increase in the number of GRBs with determined redshifts, as […]


Continue.. GRB Redshift Estimation using Machine Learning and the Associated Web-App

GRB Redshift Estimation using Machine Learning and the Associated Web-App

Posted by dbos Stanford

Kavli Affiliate: Vahe Petrosian | First 5 Authors: Aditya Narendra, Maria Dainotti, Milind Sarkar, Aleksander Lenart, Malgorzata Bogdan | Summary: Context. Gamma-ray bursts (GRBs), observed at redshifts as high as 9.4, could serve as valuable probes for investigating the distant Universe. However, this necessitates an increase in the number of GRBs with determined redshifts, as […]


Continue.. GRB Redshift Estimation using Machine Learning and the Associated Web-App

GRB Redshift Estimation using Machine Learning and the Associated Web-App

Posted by dbos Stanford

Kavli Affiliate: Vahe Petrosian | First 5 Authors: Aditya Narendra, Maria Dainotti, Milind Sarkar, Aleksander Lenart, Malgorzata Bogdan | Summary: Context. Gamma-ray bursts (GRBs), observed at redshifts as high as 9.4, could serve as valuable probes for investigating the distant Universe. However, this necessitates an increase in the number of GRBs with determined redshifts, as […]


Continue.. GRB Redshift Estimation using Machine Learning and the Associated Web-App

Trojan Prompt Attacks on Graph Neural Networks

Posted by dbos Berkeley

Kavli Affiliate: Xiang Zhang | First 5 Authors: Minhua Lin, Zhiwei Zhang, Enyan Dai, Zongyu Wu, Yilong Wang | Summary: Graph Prompt Learning (GPL) has been introduced as a promising approach that uses prompts to adapt pre-trained GNN models to specific downstream tasks without requiring fine-tuning of the entire model. Despite the advantages of GPL, […]


Continue.. Trojan Prompt Attacks on Graph Neural Networks