b'Jiaqi Zhang'

research

∙ 03/30/2022

Polarized deep diffractive neural network for classification, generation, multiplexing and de-multiplexing of orbital angular momentum modes

The multiplexing and de-multiplexing of orbital angular momentum (OAM) b...

Jiaqi Zhang, et al. ∙

research

∙ 01/19/2022

RunnerDNA: Interpretable indicators and model to characterize human activity pattern and individual difference

Human activity analysis based on sensor data plays a significant role in...

Yao Yao, et al. ∙

research

∙ 11/26/2021

Simple Contrastive Representation Adversarial Learning for NLP Tasks

Self-supervised learning approach like contrastive learning is attached ...

Deshui Miao, et al. ∙

research

∙ 11/09/2021

Machine Learning for Multimodal Electronic Health Records-based Research: Challenges and Perspectives

Background: Electronic Health Records (EHRs) contain rich information of...

Ziyi Liu, et al. ∙

research

∙ 07/28/2021

Subjective evaluation of traditional and learning-based image coding methods

We conduct a subjective experiment to compare the performance of traditi...

Zhigao Fang, et al. ∙

research

∙ 07/05/2021

Matching a Desired Causal State via Shift Interventions

Transforming a causal system from a given initial state to a desired tar...

Jiaqi Zhang, et al. ∙

research

∙ 05/14/2021

Innovation Compression for Communication-efficient Distributed Optimization with Linear Convergence

Information compression is essential to reduce communication cost in dis...

Jiaqi Zhang, et al. ∙

research

∙ 04/12/2021

Optimizing the Whole-life Cost in End-to-end CNN Acceleration

The acceleration of CNNs has gained increasing atten-tion since their su...

Jiaqi Zhang, et al. ∙

research

∙ 09/02/2020

DARWIN: A Highly Flexible Platform for Imaging Research in Radiology

To conduct a radiomics or deep learning research experiment, the radiolo...

Lufan Chang, et al. ∙

research

∙ 03/29/2020

Defect segmentation: Mapping tunnel lining internal defects with ground penetrating radar data using a convolutional neural network

This research proposes a Ground Penetrating Radar (GPR) data processing ...

Senlin Yang, et al. ∙

research

∙ 03/01/2020

Asynchronous Policy Evaluation in Distributed Reinforcement Learning over Networks

This paper proposes a fully asynchronous scheme for policy evaluation of...

Xingyu Sha, et al. ∙

research

∙ 02/18/2020

Distributed Adaptive Newton Methods with Globally Superlinear Convergence

This paper considers the distributed optimization problem over a network...

Jiaqi Zhang, et al. ∙

research

∙ 11/29/2019

Fast and Scalable Estimator for Sparse and Unit-Rank Higher-Order Regression Models

Because tensor data appear more and more frequently in various scientifi...

Jiaqi Zhang, et al. ∙

research

∙ 11/29/2019

Sparse and Low-Rank Tensor Regression via Parallel Proximal Method

Motivated by applications in various scientific fields having demand of ...

Jiaqi Zhang, et al. ∙

research

∙ 09/22/2019

Distributed Conjugate Gradient Tracking for Resource Allocation in Unbalanced Networks

This paper proposes a distributed conjugate gradient tracking algorithm ...

Jiaqi Zhang, et al. ∙

research

∙ 09/06/2019

Decentralized Stochastic Gradient Tracking for Non-convex Empirical Risk Minimization

This paper studies a decentralized stochastic gradient tracking (DSGT) a...

Jiaqi Zhang, et al. ∙

research

∙ 09/06/2019

Decentralized Stochastic Gradient Tracking for Empirical Risk Minimization

Recent works have shown superiorities of decentralized SGD to centralize...

Jiaqi Zhang, et al. ∙

research

∙ 02/12/2019

A system for generating complex physically accurate sensor images for automotive applications

We describe an open-source simulator that creates sensor irradiance and ...

Zhenyi Liu, et al. ∙

research

∙ 01/24/2019

Asynchronous Decentralized Optimization in Directed Networks

A popular asynchronous protocol for decentralized optimization is random...

Jiaqi Zhang, et al. ∙

research

∙ 11/01/2018

Pixel Level Data Augmentation for Semantic Image Segmentation using Generative Adversarial Networks

Semantic segmentation is one of the basic topics in computer vision, it ...

Shuangting Liu, et al. ∙

research

∙ 08/13/2018

AsySPA: An Exact Asynchronous Algorithm for Convex Optimization Over Digraphs

This paper proposes a novel exact asynchronous subgradient-push algorith...

Jiaqi Zhang, et al. ∙

research

∙ 03/29/2017

Efficient Private ERM for Smooth Objectives

In this paper, we consider efficient differentially private empirical ri...

Jiaqi Zhang, et al. ∙

Jiaqi Zhang

Featured Co-authors

Xin Li

Liwei Wang

Hao Liu

Yuxin Chen

Jing Wang

Ge Li

Tao Li

Tamer Basar

Yang Xiang

Caroline Uhler

Lihua Xie

Polarized deep diffractive neural network for classification, generation, multiplexing and de-multiplexing of orbital angular momentum modes

RunnerDNA: Interpretable indicators and model to characterize human activity pattern and individual difference

Simple Contrastive Representation Adversarial Learning for NLP Tasks

Machine Learning for Multimodal Electronic Health Records-based Research: Challenges and Perspectives

Subjective evaluation of traditional and learning-based image coding methods

Matching a Desired Causal State via Shift Interventions

Innovation Compression for Communication-efficient Distributed Optimization with Linear Convergence

Optimizing the Whole-life Cost in End-to-end CNN Acceleration

DARWIN: A Highly Flexible Platform for Imaging Research in Radiology

Defect segmentation: Mapping tunnel lining internal defects with ground penetrating radar data using a convolutional neural network

Asynchronous Policy Evaluation in Distributed Reinforcement Learning over Networks

Distributed Adaptive Newton Methods with Globally Superlinear Convergence

Fast and Scalable Estimator for Sparse and Unit-Rank Higher-Order Regression Models

Sparse and Low-Rank Tensor Regression via Parallel Proximal Method

Distributed Conjugate Gradient Tracking for Resource Allocation in Unbalanced Networks

Decentralized Stochastic Gradient Tracking for Non-convex Empirical Risk Minimization

Decentralized Stochastic Gradient Tracking for Empirical Risk Minimization

A system for generating complex physically accurate sensor images for automotive applications

Asynchronous Decentralized Optimization in Directed Networks

Pixel Level Data Augmentation for Semantic Image Segmentation using Generative Adversarial Networks

AsySPA: An Exact Asynchronous Algorithm for Convex Optimization Over Digraphs

Efficient Private ERM for Smooth Objectives