Hongyi Wang | DeepAI

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Hao Chen
339 publications
Yu Wang
276 publications
Eric P Xing
147 publications
Kai Zhang
131 publications
Hao Sun
91 publications
Liu Yang
73 publications
Eric Xing
70 publications
Lichao Sun
67 publications
Carl Yang
55 publications
Mikhail Yurochkin
43 publications
Andrew Gelman
43 publications

∙ 08/28/2023

Maestro: Uncovering Low-Rank Structures via Trainable Decomposition

Deep Neural Networks (DNNs) have been a large driver and enabler for AI ...

0 Samuel Horvath, et al. ∙

∙ 05/04/2023

Cuttlefish: Low-Rank Model Training without All the Tuning

Recent research has shown that training low-rank neural networks can eff...

0 Hongyi Wang, et al. ∙

∙ 03/28/2023

Iteratively Coupled Multiple Instance Learning from Instance to Bag Classifier for Whole Slide Image Classification

Whole Slide Image (WSI) classification remains a challenge due to their ...

0 Hongyi Wang, et al. ∙

∙ 03/08/2023

Memory-adaptive Depth-wise Heterogenous Federated Learning

Federated learning is a promising paradigm that allows multiple clients ...

0 Kai Zhang, et al. ∙

∙ 02/08/2023

Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach

The canonical formulation of federated learning treats it as a distribut...

0 Han Guo, et al. ∙

∙ 01/06/2023

Does compressing activations help model parallel training?

Large-scale Transformer models are known for their exceptional performan...

0 Song Bian, et al. ∙

∙ 10/26/2022

Super-Resolution Based Patch-Free 3D Medical Image Segmentation with Self-Supervised Guidance

High resolution (HR) 3D medical image segmentation plays an important ro...

0 Hongyi Wang, et al. ∙

∙ 07/28/2022

CubeMLP: An MLP-based Model for Multimodal Sentiment Analysis and Depression Estimation

Multimodal sentiment analysis and depression estimation are two importan...

7 Hao Sun, et al. ∙

∙ 03/17/2022

Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation

Federated Learning (FL) on knowledge graphs (KGs) has yet to be as well ...

7 Kai Zhang, et al. ∙

∙ 02/24/2022

Rare Gems: Finding Lottery Tickets at Initialization

It has been widely observed that large neural networks can be pruned to ...

5 Kartik Sreenivasan, et al. ∙

∙ 12/13/2021

Hformer: Hybrid CNN-Transformer for Fringe Order Prediction in Phase Unwrapping of Fringe Projection

Recently, deep learning has attracted more and more attention in phase u...

3 Xinjun Zhu, et al. ∙

∙ 11/08/2021

Mixed Transformer U-Net For Medical Image Segmentation

Though U-Net has achieved tremendous success in medical image segmentati...

14 Hongyi Wang, et al. ∙

∙ 10/04/2021

Solon: Communication-efficient Byzantine-resilient Distributed Training via Redundant Gradients

There has been a growing need to provide Byzantine-resilience in distrib...

3 Lingjiao Chen, et al. ∙

∙ 08/16/2021

Memtrade: A Disaggregated-Memory Marketplace for Public Clouds

We present Memtrade, the first memory disaggregation system for public c...

0 Hasan Al Maruf, et al. ∙

∙ 03/05/2021

Pufferfish: Communication-efficient Models At No Extra Cost

To mitigate communication overheads in distributed model training, sever...

10 Hongyi Wang, et al. ∙

∙ 02/28/2021

On the Utility of Gradient Compression in Distributed Training Systems

Rapid growth in data sets and the scale of neural network architectures ...

16 Saurabh Agarwal, et al. ∙

∙ 02/25/2021

BPF for storage: an exokernel-inspired approach

The overhead of the kernel storage path accounts for half of the access ...

0 Yu Jian Wu, et al. ∙

∙ 10/29/2020

Accordion: Adaptive Gradient Communication via Critical Learning Regime Identification

Distributed model training suffers from communication bottlenecks due to...

1 Saurabh Agarwal, et al. ∙

∙ 07/09/2020

Attack of the Tails: Yes, You Really Can Backdoor Federated Learning

Due to its decentralized nature, Federated Learning (FL) lends itself to...

18 Hongyi Wang, et al. ∙

∙ 02/15/2020

Federated Learning with Matched Averaging

Federated learning allows edge devices to collaboratively learn a shared...

0 Hongyi Wang, et al. ∙

∙ 07/29/2019

DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation

To improve the resilience of distributed training to worst-case, or Byza...

0 Shashank Rajput, et al. ∙

∙ 01/28/2019

ErasureHead: Distributed Gradient Descent without Delays Using Approximate Gradient Coding

We present ErasureHead, a new approach for distributed gradient descent ...

0 Hongyi Wang, et al. ∙

∙ 06/11/2018

ATOMO: Communication-efficient Learning via Atomic Sparsification

Distributed model training suffers from communication overheads due to f...

0 Hongyi Wang, et al. ∙

∙ 06/11/2018

The Effect of Network Width on the Performance of Large-batch Training

Distributed implementations of mini-batch stochastic gradient descent (S...

0 Lingjiao Chen, et al. ∙

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