b'Shuai Zheng'

research

∙ 04/30/2022

MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud

Existing general purpose frameworks for gigantic model training, i.e., m...

Zhen Zhang, et al. ∙

research

∙ 09/24/2021

ZSD-YOLO: Zero-Shot YOLO Detection using Vision-Language KnowledgeDistillation

Real-world object sampling produces long-tailed distributions requiring ...

Johnathan Xie, et al. ∙

research

∙ 07/19/2021

CETransformer: Casual Effect Estimation via Transformer Based Representation Learning

Treatment effect estimation, which refers to the estimation of causal ef...

Zhenyu Guo, et al. ∙

research

∙ 05/17/2021

Compressed Communication for Distributed Training: Adaptive Methods and System

Communication overhead severely hinders the scalability of distributed m...

Yuchen Zhong, et al. ∙

research

∙ 03/16/2021

Deep Time Series Models for Scarce Data

Time series data have grown at an explosive rate in numerous domains and...

Qiyao Wang, et al. ∙

research

∙ 03/12/2021

Adversarial Graph Disentanglement

A real-world graph has a complex topology structure, which is often form...

Shuai Zheng, et al. ∙

research

∙ 10/17/2020

LID 2020: The Learning from Imperfect Data Challenge Results

Learning from imperfect data becomes an issue in many industrial applica...

Yunchao Wei, et al. ∙

research

∙ 10/02/2020

Taking Modality-free Human Identification as Zero-shot Learning

Human identification is an important topic in event detection, person tr...

Zhizhe Liu, et al. ∙

research

∙ 08/24/2020

Dynamic Dispatching for Large-Scale Heterogeneous Fleet via Multi-agent Deep Reinforcement Learning

Dynamic dispatching is one of the core problems for operation optimizati...

Chi Zhang, et al. ∙

research

∙ 07/26/2020

CSER: Communication-efficient SGD with Error Reset

The scalability of Distributed Stochastic Gradient Descent (SGD) is toda...

Cong Xie, et al. ∙

research

∙ 06/24/2020

Accelerated Large Batch Optimization of BERT Pretraining in 54 minutes

BERT has recently attracted a lot of attention in natural language under...

Shuai Zheng, et al. ∙

research

∙ 12/04/2019

Distribution-induced Bidirectional Generative Adversarial Network for Graph Representation Learning

Graph representation learning aims to encode all nodes of a graph into l...

Shuai Zheng, et al. ∙

research

∙ 10/04/2019

Manufacturing Dispatching using Reinforcement and Transfer Learning

Efficient dispatching rule in manufacturing industry is key to ensure pr...

Shuai Zheng, et al. ∙

research

∙ 10/04/2019

Generative Adversarial Networks for Failure Prediction

Prognostics and Health Management (PHM) is an emerging engineering disci...

Shuai Zheng, et al. ∙

research

∙ 07/11/2019

Edge Heuristic GAN for Non-uniform Blind Deblurring

Non-uniform blur, mainly caused by camera shake and motions of multiple ...

Shuai Zheng, et al. ∙

research

∙ 07/09/2019

GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing

We present GluonCV and GluonNLP, the deep learning toolkits for computer...

Jian Guo, et al. ∙

research

∙ 05/27/2019

Communication-Efficient Distributed Blockwise Momentum SGD with Error-Feedback

Communication overhead is a major bottleneck hampering the scalability o...

Shuai Zheng, et al. ∙

research

∙ 05/23/2019

Blockwise Adaptivity: Faster Training and Better Generalization in Deep Learning

Stochastic methods with coordinate-wise adaptive stepsize (such as RMSpr...

Shuai Zheng, et al. ∙

research

∙ 04/12/2019

Remaining Useful Life Estimation Using Functional Data Analysis

Remaining Useful Life (RUL) of an equipment or one of its components is ...

Qiyao Wang, et al. ∙

research

∙ 09/24/2018

Give me a hint! Navigating Image Databases using Human-in-the-loop Feedback

In this paper, we introduce an attribute-based interactive image search ...

Bryan A. Plummer, et al. ∙

research

∙ 07/03/2018

ModaNet: A Large-Scale Street Fashion Dataset with Polygon Annotations

Understanding clothes from a single image has strong commercial and cult...

Shuai Zheng, et al. ∙

research

∙ 06/08/2018

Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data

Variance reduction has been commonly used in stochastic optimization. It...

Shuai Zheng, et al. ∙

research

∙ 04/13/2018

Regularized Singular Value Decomposition and Application to Recommender System

Singular value decomposition (SVD) is the mathematical basis of principa...

Shuai Zheng, et al. ∙

research

∙ 04/06/2018

Minimal Support Vector Machine

Support Vector Machine (SVM) is an efficient classification approach, wh...

Shuai Zheng, et al. ∙

research

∙ 03/15/2018

Fast End-to-End Trainable Guided Filter

Image processing and pixel-wise dense prediction have been advanced by h...

Huikai Wu, et al. ∙

research

∙ 11/22/2017

Conditional Image-Text Embedding Networks

This paper presents an approach for grounding phrases in images which jo...

Bryan A. Plummer, et al. ∙

research

∙ 03/21/2017

GP-GAN: Towards Realistic High-Resolution Image Blending

Recent advances in generative adversarial networks (GANs) have shown pro...

Huikai Wu, et al. ∙

research

∙ 01/24/2017

Learning Arbitrary Pairwise Potentials in CRFs for Semantic Segmentation

Are we using the right potential functions in the Conditional Random Fie...

Måns Larsson, et al. ∙

research

∙ 10/14/2016

A Harmonic Mean Linear Discriminant Analysis for Robust Image Classification

Linear Discriminant Analysis (LDA) is a widely-used supervised dimension...

Shuai Zheng, et al. ∙

research

∙ 10/14/2016

Kernel Alignment Inspired Linear Discriminant Analysis

Kernel alignment measures the degree of similarity between two kernels. ...

Shuai Zheng, et al. ∙

research

∙ 09/12/2016

Fully-Trainable Deep Matching

Deep Matching (DM) is a popular high-quality method for quasi-dense imag...

James Thewlis, et al. ∙

research

∙ 05/04/2016

Accelerating Deep Learning with Shrinkage and Recall

Deep Learning is a very powerful machine learning model. Deep Learning t...

Shuai Zheng, et al. ∙

research

∙ 04/24/2016

Stochastic Variance-Reduced ADMM

The alternating direction method of multipliers (ADMM) is a powerful opt...

Shuai Zheng, et al. ∙

research

∙ 02/25/2016

Fast Nonsmooth Regularized Risk Minimization with Continuation

In regularized risk minimization, the associated optimization problem be...

Shuai Zheng, et al. ∙

research

∙ 02/11/2015

Conditional Random Fields as Recurrent Neural Networks

Pixel-level labelling tasks, such as semantic segmentation, play a centr...

Shuai Zheng, et al. ∙

research

∙ 10/16/2013

ImageSpirit: Verbal Guided Image Parsing

Humans describe images in terms of nouns and adjectives while algorithms...

Ming-Ming Cheng, et al. ∙

research

∙ 10/26/2010

Translation-Invariant Representation for Cumulative Foot Pressure Images

Human can be distinguished by different limb movements and unique ground...

Shuai Zheng, et al. ∙

Shuai Zheng

Featured Co-authors