Zhenheng Tang | DeepAI

DeepAI AI Chat

Featured Co-authors

Wei Wang
492 publications
Bo Li
461 publications
Li Shen
141 publications
Bo Han
121 publications
Qiang Wang
84 publications
Xiaoming Liu
83 publications
Salman Avestimehr
53 publications
Mahdi Soltanolkotabi
51 publications
Xiaowen Chu
50 publications
Yuxin Wang
48 publications
Simon See
40 publications

∙ 09/03/2023

FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs

The rapid growth of memory and computation requirements of large languag...

0 Zhenheng Tang, et al. ∙

∙ 03/03/2023

FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training

Federated Learning (FL) enables collaborations among clients for train m...

2 Zhenheng Tang, et al. ∙

∙ 11/23/2022

NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension

One-shot neural architecture search (NAS) substantially improves the sea...

0 Xin He, et al. ∙

∙ 06/06/2022

Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning

In federated learning (FL), model performance typically suffers from cli...

0 Zhenheng Tang, et al. ∙

∙ 11/22/2021

FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks

Federated Learning (FL) is a distributed learning paradigm that can lear...

2 Chaoyang He, et al. ∙

∙ 05/27/2020

Communication-Efficient Distributed Deep Learning: Survey, Evaluation, and Challenges

In recent years, distributed deep learning techniques are widely deploye...

0 Shaohuai Shi, et al. ∙

∙ 03/10/2020

Communication-Efficient Distributed Deep Learning: A Comprehensive Survey

Distributed deep learning becomes very common to reduce the overall trai...

0 Zhenheng Tang, et al. ∙

∙ 02/22/2020

Communication-Efficient Decentralized Learning with Sparsification and Adaptive Peer Selection

Distributed learning techniques such as federated learning have enabled ...

0 Zhenheng Tang, et al. ∙

∙ 11/20/2019

Layer-wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees

To reduce the long training time of large deep neural network (DNN) mode...

0 Shaohuai Shi, et al. ∙

∙ 11/20/2019

Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models

Skin disease is one of the most common types of human diseases, which ma...

18 Xin He, et al. ∙

∙ 09/15/2019

Performance and Power Evaluation of AI Accelerators for Training Deep Learning Models

Deep neural networks (DNNs) have become widely used in many AI applicati...

0 Yuxin Wang, et al. ∙

∙ 05/27/2019

The Impact of GPU DVFS on the Energy and Performance of Deep Learning: an Empirical Study

Over the past years, great progress has been made in improving the compu...

0 Zhenheng Tang, et al. ∙

∙ 01/14/2019

A Distributed Synchronous SGD Algorithm with Global Top-k Sparsification for Low Bandwidth Networks

Distributed synchronous stochastic gradient descent (S-SGD) with data pa...

0 Shaohuai Shi, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world