activity
20172022
most citedFaster On-Device Training Using New Federated Momentum Algorithm

36 citations · 235 across the 31 of their papers we have counts for

collaborators

39 papers

cs.LG2022

Communication-Efficient Adam-Type Algorithms for Distributed Data Mining

Wenhan Xian, Feihu Huang, Heng Huang

Distributed data mining is an emerging research topic to effectively and efficiently address hard data mining tasks using big data, which are partitioned and computed on different…

cs.CV20222 cited

Interpretations Steered Network Pruning via Amortized Inferred Saliency Maps

Alireza Ganjdanesh, Shangqian Gao, Heng Huang

Convolutional Neural Networks (CNNs) compression is crucial to deploying these models in edge devices with limited resources. Existing channel pruning algorithms for CNNs have achi…

cs.LG20222 cited

Local Stochastic Bilevel Optimization with Momentum-Based Variance Reduction

Junyi Li, Feihu Huang, Heng Huang

Bilevel Optimization has witnessed notable progress recently with new emerging efficient algorithms and has been applied to many machine learning tasks such as data cleaning, few-s…

cs.LG20221 cited

Distributed Dynamic Safe Screening Algorithms for Sparse Regularization

Runxue Bao, Xidong Wu, Wenhan Xian +1

Distributed optimization has been widely used as one of the most efficient approaches for model training with massive samples. However, large-scale learning problems with both mass…

cs.LG20228 cited

Desirable Companion for Vertical Federated Learning: New Zeroth-Order Gradient Based Algorithm

Qingsong Zhang, Bin Gu, Zhiyuan Dang +2

Vertical federated learning (VFL) attracts increasing attention due to the emerging demands of multi-party collaborative modeling and concerns of privacy leakage. A complete list o…

cs.CV2021

Adaptive Hierarchical Similarity Metric Learning with Noisy Labels

Jiexi Yan, Lei Luo, Cheng Deng +1

Deep Metric Learning (DML) plays a critical role in various machine learning tasks. However, most existing deep metric learning methods with binary similarity are sensitive to nois…