Search Results for author: Jun Zhang

Found 218 papers, 63 papers with code

BMInf: An Efficient Toolkit for Big Model Inference and Tuning

1 code implementation ACL 2022 Xu Han, Guoyang Zeng, Weilin Zhao, Zhiyuan Liu, Zhengyan Zhang, Jie zhou, Jun Zhang, Jia Chao, Maosong Sun

In recent years, large-scale pre-trained language models (PLMs) containing billions of parameters have achieved promising results on various NLP tasks.

Quantization Scheduling

KERS: A Knowledge-Enhanced Framework for Recommendation Dialog Systems with Multiple Subgoals

1 code implementation Findings (EMNLP) 2021 Jun Zhang, Yan Yang, Chencai Chen, Liang He, Zhou Yu

Recommendation dialogs require the system to build a social bond with users to gain trust and develop affinity in order to increase the chance of a successful recommendation.

Question Answering Recommendation Systems +1

Towards Real-Time Neural Video Codec for Cross-Platform Application Using Calibration Information

no code implementations20 Sep 2023 Kuan Tian, Yonghang Guan, Jinxi Xiang, Jun Zhang, Xiao Han, Wei Yang

First, to solve the problem of inconsistency of codec caused by the uncertainty of floating point calculations across platforms, we design a calibration transmitting system to guarantee the consistent quantization of entropy parameters between the encoding and decoding stages.


AI-Native Transceiver Design for Near-Field Ultra-Massive MIMO: Principles and Techniques

no code implementations18 Sep 2023 Wentao Yu, Yifan Ma, Hengtao He, Shenghui Song, Jun Zhang, Khaled B. Letaief

Ultra-massive multiple-input multiple-output (UM-MIMO) is a cutting-edge technology that promises to revolutionize wireless networks by providing an unprecedentedly high spectral and energy efficiency.

Client-side Gradient Inversion Against Federated Learning from Poisoning

1 code implementation14 Sep 2023 Jiaheng Wei, Yanjun Zhang, Leo Yu Zhang, Chao Chen, Shirui Pan, Kok-Leong Ong, Jun Zhang, Yang Xiang

For the first time, we show the feasibility of a client-side adversary with limited knowledge being able to recover the training samples from the aggregated global model.

Federated Learning

FedCiR: Client-Invariant Representation Learning for Federated Non-IID Features

no code implementations30 Aug 2023 Zijian Li, Zehong Lin, Jiawei Shao, Yuyi Mao, Jun Zhang

However, devices often have non-independent and identically distributed (non-IID) data, meaning their local data distributions can vary significantly.

Federated Learning Representation Learning

Forensic Histopathological Recognition via a Context-Aware MIL Network Powered by Self-Supervised Contrastive Learning

no code implementations27 Aug 2023 Chen Shen, Jun Zhang, Xinggong Liang, Zeyi Hao, Kehan Li, Fan Wang, Zhenyuan Wang, Chunfeng Lian

Forensic pathology is critical in analyzing death manner and time from the microscopic aspect to assist in the establishment of reliable factual bases for criminal investigation.

Contrastive Learning Domain Generalization +3

Dynamic Low-Rank Instance Adaptation for Universal Neural Image Compression

1 code implementation15 Aug 2023 Yue Lv, Jinxi Xiang, Jun Zhang, Wenming Yang, Xiao Han, Wei Yang

We thus introduce a dynamic gating network on top of the low-rank adaptation method, in order to decide which decoder layer should employ adaptation.

Image Compression

IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models

no code implementations13 Aug 2023 Hu Ye, Jun Zhang, Sibo Liu, Xiao Han, Wei Yang

Despite the simplicity of our method, an IP-Adapter with only 22M parameters can achieve comparable or even better performance to a fully fine-tuned image prompt model.

Image Generation Prompt Engineering

A new solution and concrete implementation steps for Artificial General Intelligence

no code implementations12 Aug 2023 Yongcong Chen, Ting Zeng, Jun Zhang

At present, the mainstream artificial intelligence generally adopts the technical path of "attention mechanism + deep learning" + "reinforcement learning".


Feature Matching Data Synthesis for Non-IID Federated Learning

no code implementations9 Aug 2023 Zijian Li, Yuchang Sun, Jiawei Shao, Yuyi Mao, Jessie Hui Wang, Jun Zhang

For better privacy preservation, we propose a hard feature augmentation method to transfer real features towards the decision boundary, with which the synthetic data not only improve the model generalization but also erase the information of real features.

Data Augmentation Federated Learning +1

Binary Federated Learning with Client-Level Differential Privacy

no code implementations7 Aug 2023 Lumin Liu, Jun Zhang, Shenghui Song, Khaled B. Letaief

To improve communication efficiency and achieve a better privacy-utility trade-off, we propose a communication-efficient FL training algorithm with differential privacy guarantee.

Federated Learning Privacy Preserving

L-Eval: Instituting Standardized Evaluation for Long Context Language Models

1 code implementation20 Jul 2023 Chenxin An, Shansan Gong, Ming Zhong, Mukai Li, Jun Zhang, Lingpeng Kong, Xipeng Qiu

Recently, there has been growing interest in extending the context length of instruction-following models in order to effectively process single-turn long input (e. g. summarizing a paper) and conversations with more extensive histories.

Instruction Following

A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency

no code implementations20 Jul 2023 Jiawei Shao, Zijian Li, Wenqiang Sun, Tailin Zhou, Yuchang Sun, Lumin Liu, Zehong Lin, Jun Zhang

First, we present a new taxonomy of FL methods in terms of the sharing methods, which includes three categories of shared information: model sharing, synthetic data sharing, and knowledge sharing.

Federated Learning Privacy Preserving

Large Language Models Empowered Autonomous Edge AI for Connected Intelligence

no code implementations6 Jul 2023 Yifei Shen, Jiawei Shao, Xinjie Zhang, Zehong Lin, Hao Pan, Dongsheng Li, Jun Zhang, Khaled B. Letaief

The evolution of wireless networks gravitates towards connected intelligence, a concept that envisions seamless interconnectivity among humans, objects, and intelligence in a hyper-connected cyber-physical world.

Code Generation Federated Learning +3

MimiC: Combating Client Dropouts in Federated Learning by Mimicking Central Updates

no code implementations21 Jun 2023 Yuchang Sun, Yuyi Mao, Jun Zhang

Federated learning (FL) is a promising framework for privacy-preserving collaborative learning, where model training tasks are distributed to clients and only the model updates need to be collected at a server.

Federated Learning Privacy Preserving

CIF-PT: Bridging Speech and Text Representations for Spoken Language Understanding via Continuous Integrate-and-Fire Pre-Training

no code implementations27 May 2023 Linhao Dong, Zhecheng An, Peihao Wu, Jun Zhang, Lu Lu, Zejun Ma

We also observe the cross-modal representation extracted by CIF-PT obtains better performance than other neural interfaces for the tasks of SLU, including the dominant speech representation learned from self-supervised pre-training.

intent-classification Intent Classification +5

Channel and Gradient-Importance Aware Device Scheduling for Over-the-Air Federated Learning

no code implementations26 May 2023 Yuchang Sun, Zehong Lin, Yuyi Mao, Shi Jin, Jun Zhang

In this paper, we propose a probabilistic device scheduling framework for over-the-air FL, named PO-FL, to mitigate the negative impact of channel noise, where each device is scheduled according to a certain probability and its model update is reweighted using this probability in aggregation.

Federated Learning Privacy Preserving +1

Towards Large-scale Single-shot Millimeter-wave Imaging for Low-cost Security Inspection

no code implementations25 May 2023 Liheng Bian, Daoyu Li, Shuoguang Wang, Chunyang Teng, Huteng Liu, Hanwen Xu, Xuyang Chang, Guoqiang Zhao, Shiyong Li, Jun Zhang

These elements are then sampled based on the ranking, building the experimentally optimal sparse sampling strategy that reduces the cost of antenna array by up to one order of magnitude.

Image Reconstruction object-detection +1

Joint Activity-Delay Detection and Channel Estimation for Asynchronous Massive Random Access

no code implementations21 May 2023 Xinyu Bian, Yuyi Mao, Jun Zhang

Most existing studies on joint activity detection and channel estimation for grant-free massive random access (RA) systems assume perfect synchronization among all active users, which is hard to achieve in practice.

Action Detection Activity Detection

Task-Oriented Communication with Out-of-Distribution Detection: An Information Bottleneck Framework

no code implementations21 May 2023 Hongru Li, Wentao Yu, Hengtao He, Jiawei Shao, Shenghui Song, Jun Zhang, Khaled B. Letaief

Task-oriented communication is an emerging paradigm for next-generation communication networks, which extracts and transmits task-relevant information, instead of raw data, for downstream applications.

Informativeness Out-of-Distribution Detection

Understanding Model Averaging in Federated Learning on Heterogeneous Data

no code implementations13 May 2023 Tailin Zhou, Zehong Lin, Jun Zhang, Danny H. K. Tsang

To further understand this phenomenon, we decompose the expected prediction error of the global model into five factors related to client models.

Federated Learning

Novel deep learning methods for 3D flow field segmentation and classification

no code implementations10 May 2023 Xiaorui Bai, Wenyong Wang, Jun Zhang, Yueqing Wang, Yu Xiang

Flow field segmentation and classification help researchers to understand vortex structure and thus turbulent flow.


Machine-Learned Invertible Coarse Graining for Multiscale Molecular Modeling

no code implementations2 May 2023 Jun Zhang, Xiaohan Lin, Weinan E, Yi Qin Gao

Multiscale molecular modeling is widely applied in scientific research of molecular properties over large time and length scales.

DABS: Data-Agnostic Backdoor attack at the Server in Federated Learning

no code implementations2 May 2023 Wenqiang Sun, Sen Li, Yuchang Sun, Jun Zhang

Federated learning (FL) attempts to train a global model by aggregating local models from distributed devices under the coordination of a central server.

Backdoor Attack Federated Learning

Evaluation of a Canonical Image Representation for Sidescan Sonar

no code implementations18 Apr 2023 Weiqi Xu, Li Ling, Yiping Xie, Jun Zhang, John Folkesson

In this paper, a canonical transformation method consisting of intensity correction and slant range correction is proposed to decrease the above distortion.

Template Matching

Grant-free Massive Random Access with Retransmission: Receiver Optimization and Performance Analysis

no code implementations12 Apr 2023 Xinyu Bian, Yuyi Mao, Jun Zhang

Specifically, by jointly leveraging the user activity correlation between adjacent transmission blocks and the historical channel estimation results, we first develop an activity-correlation-aware receiver for grant-free massive RA systems with retransmission based on the correlated approximate message passing (AMP) algorithm.

Action Detection Activity Detection

A Survey on Distributed Evolutionary Computation

no code implementations12 Apr 2023 Wei-neng Chen, Feng-Feng Wei, Tian-Fang Zhao, Kay Chen Tan, Jun Zhang

Based on this taxonomy, existing studies on DEC are reviewed in terms of purpose, parallel structure of the algorithm, parallel model for implementation, and the implementation environment.

Distributed Computing Distributed Optimization

CEC: Crowdsourcing-based Evolutionary Computation for Distributed Optimization

no code implementations12 Apr 2023 Feng-Feng Wei, Wei-neng Chen, Xiao-Qi Guo, Bowen Zhao, Sang-Woon Jeon, Jun Zhang

Inspired by this, this paper intends to introduce crowdsourcing into evolutionary computation (EC) to propose a crowdsourcing-based evolutionary computation (CEC) paradigm for distributed optimization.

Distributed Optimization

Selective Knowledge Sharing for Privacy-Preserving Federated Distillation without A Good Teacher

no code implementations4 Apr 2023 Jiawei Shao, Fangzhao Wu, Jun Zhang

While federated learning is promising for privacy-preserving collaborative learning without revealing local data, it remains vulnerable to white-box attacks and struggles to adapt to heterogeneous clients.

Federated Learning Knowledge Distillation +2

Generalized Relation Modeling for Transformer Tracking

1 code implementation CVPR 2023 Shenyuan Gao, Chunluan Zhou, Jun Zhang

Compared with previous two-stream trackers, the recent one-stream tracking pipeline, which allows earlier interaction between the template and search region, has achieved a remarkable performance gain.

When Evolutionary Computation Meets Privacy

no code implementations22 Mar 2023 Bowen Zhao, Wei-neng Chen, Xiaoguo Li, Ximeng Liu, Qingqi Pei, Jun Zhang

To this end, in this paper, we discuss three typical optimization paradigms (i. e., \textit{centralized optimization, distributed optimization, and data-driven optimization}) to characterize optimization modes of evolutionary computation and propose BOOM to sort out privacy concerns in evolutionary computation.

Distributed Computing Distributed Optimization +1

Low-complexity Deep Video Compression with A Distributed Coding Architecture

1 code implementation21 Mar 2023 Xinjie Zhang, Jiawei Shao, Jun Zhang

This has inspired a distributed coding architecture aiming at reducing the encoding complexity.

Motion Estimation Video Compression

DSDP: A Blind Docking Strategy Accelerated by GPUs

no code implementations16 Mar 2023 Yupeng Huang, Hong Zhang, Siyuan Jiang, Dajiong Yue, Xiaohan Lin, Jun Zhang, Yi Qin Gao

In this study, we take the advantage of both traditional and machine-learning based methods, and present a method Deep Site and Docking Pose (DSDP) to improve the performance of blind docking.

Blind Docking Drug Discovery

CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

no code implementations11 Mar 2023 Simon Graham, Quoc Dang Vu, Mostafa Jahanifar, Martin Weigert, Uwe Schmidt, Wenhua Zhang, Jun Zhang, Sen yang, Jinxi Xiang, Xiyue Wang, Josef Lorenz Rumberger, Elias Baumann, Peter Hirsch, Lihao Liu, Chenyang Hong, Angelica I. Aviles-Rivero, Ayushi Jain, Heeyoung Ahn, Yiyu Hong, Hussam Azzuni, Min Xu, Mohammad Yaqub, Marie-Claire Blache, Benoît Piégu, Bertrand Vernay, Tim Scherr, Moritz Böhland, Katharina Löffler, Jiachen Li, Weiqin Ying, Chixin Wang, Dagmar Kainmueller, Carola-Bibiane Schönlieb, Shuolin Liu, Dhairya Talsania, Yughender Meda, Prakash Mishra, Muhammad Ridzuan, Oliver Neumann, Marcel P. Schilling, Markus Reischl, Ralf Mikut, Banban Huang, Hsiang-Chin Chien, Ching-Ping Wang, Chia-Yen Lee, Hong-Kun Lin, Zaiyi Liu, Xipeng Pan, Chu Han, Jijun Cheng, Muhammad Dawood, Srijay Deshpande, Raja Muhammad Saad Bashir, Adam Shephard, Pedro Costa, João D. Nunes, Aurélio Campilho, Jaime S. Cardoso, Hrishikesh P S, Densen Puthussery, Devika R G, Jiji C V, Ye Zhang, Zijie Fang, Zhifan Lin, Yongbing Zhang, Chunhui Lin, Liukun Zhang, Lijian Mao, Min Wu, Vi Thi-Tuong Vo, Soo-Hyung Kim, Taebum Lee, Satoshi Kondo, Satoshi Kasai, Pranay Dumbhare, Vedant Phuse, Yash Dubey, Ankush Jamthikar, Trinh Thi Le Vuong, Jin Tae Kwak, Dorsa Ziaei, Hyun Jung, Tianyi Miao, David Snead, Shan E Ahmed Raza, Fayyaz Minhas, Nasir M. Rajpoot

Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome.

Nuclear Segmentation Survival Analysis +1

AC2C: Adaptively Controlled Two-Hop Communication for Multi-Agent Reinforcement Learning

no code implementations24 Feb 2023 Xuefeng Wang, Xinran Li, Jiawei Shao, Jun Zhang

Learning communication strategies in cooperative multi-agent reinforcement learning (MARL) has recently attracted intensive attention.

Multi-agent Reinforcement Learning reinforcement-learning +2

Message Passing Meets Graph Neural Networks: A New Paradigm for Massive MIMO Systems

no code implementations14 Feb 2023 Hengtao He, Xianghao Yu, Jun Zhang, Shenghui Song, Khaled B. Letaief

As one of the core technologies for 5G systems, massive multiple-input multiple-output (MIMO) introduces dramatic capacity improvements along with very high beamforming and spatial multiplexing gains.

Hyperspectral Image Super Resolution with Real Unaligned RGB Guidance

no code implementations13 Feb 2023 Zeqiang Lai, Ying Fu, Jun Zhang

The features of RGB reference images are then processed by a multi-stage alignment module to explicitly align the features of RGB reference with the LR HSI.

Hyperspectral Image Super-Resolution Image Super-Resolution

In-Context Learning with Many Demonstration Examples

1 code implementation9 Feb 2023 Mukai Li, Shansan Gong, Jiangtao Feng, Yiheng Xu, Jun Zhang, Zhiyong Wu, Lingpeng Kong

Based on EVALM, we scale up the size of examples efficiently in both instruction tuning and in-context learning to explore the boundary of the benefits from more annotated data.

Language Modelling

Artificial intelligence for diagnosing and predicting survival of patients with renal cell carcinoma: Retrospective multi-center study

no code implementations12 Jan 2023 Siteng Chen, Xiyue Wang, Jun Zhang, Liren Jiang, Ning Zhang, Feng Gao, Wei Yang, Jinxi Xiang, Sen yang, Junhua Zheng, Xiao Han

The OSrisk for the prediction of 5-year survival status achieved AUC of 0. 784 (0. 746-0. 819) in the TCGA cohort, which was further verified in the independent General cohort and the CPTAC cohort, with AUC of 0. 774 (0. 723-0. 820) and 0. 702 (0. 632-0. 765), respectively.

whole slide images

Machine Learning for Large-Scale Optimization in 6G Wireless Networks

no code implementations3 Jan 2023 Yandong Shi, Lixiang Lian, Yuanming Shi, Zixin Wang, Yong Zhou, Liqun Fu, Lin Bai, Jun Zhang, Wei zhang

The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from "connected things" to "connected intelligence", featured by ultra high density, large-scale, dynamic heterogeneity, diversified functional requirements and machine learning capabilities, which leads to a growing need for highly efficient intelligent algorithms.

Distributed Optimization Federated Learning +1

Large-scale single-photon imaging

no code implementations28 Dec 2022 Liheng Bian, Haoze Song, Lintao Peng, Xuyang Chang, Xi Yang, Roarke Horstmeyer, Lin Ye, Tong Qin, Dezhi Zheng, Jun Zhang

Benefiting from its single-photon sensitivity, single-photon avalanche diode (SPAD) array has been widely applied in various fields such as fluorescence lifetime imaging and quantum computing.


Scattering-induced entropy boost for highly-compressed optical sensing and encryption

no code implementations16 Dec 2022 Liheng Bian, Xinrui Zhan, Xuyang Chang, Daoyu Li, Rong Yan, Yinuo Zhang, Haowen Ruan, Jun Zhang

In the proposed framework of single-pixel detection, the optical field from a target is first scattered by an optical diffuser and then two-dimensionally modulated by a spatial light modulator.

Image Classification

RLogist: Fast Observation Strategy on Whole-slide Images with Deep Reinforcement Learning

1 code implementation4 Dec 2022 Boxuan Zhao, Jun Zhang, Deheng Ye, Jian Cao, Xiao Han, Qiang Fu, Wei Yang

Most of the existing methods rely on a multiple instance learning framework that requires densely sampling local patches at high magnification.

Benchmarking Decision Making +4

iEnhancer-ELM: improve enhancer identification by extracting position-related multiscale contextual information based on enhancer language models

1 code implementation3 Dec 2022 Jiahao Li, Zhourun Wu, Wenhao Lin, Jiawei Luo, Jun Zhang, Qingcai Chen, Junjie Chen

Although many feature extraction methods have been proposed to improve the performance of enhancer identification, they cannot learn position-related multiscale contextual information from raw DNA sequences.

Language Modelling

An Adaptive and Robust Deep Learning Framework for THz Ultra-Massive MIMO Channel Estimation

1 code implementation29 Nov 2022 Wentao Yu, Yifei Shen, Hengtao He, Xianghao Yu, Shenghui Song, Jun Zhang, Khaled B. Letaief

For practical usage, the proposed framework is further extended to wideband THz UM-MIMO systems with beam squint effect.

Lightweight and Flexible Deep Equilibrium Learning for CSI Feedback in FDD Massive MIMO

no code implementations28 Nov 2022 Yifan Ma, Wentao Yu, Xianghao Yu, Jun Zhang, Shenghui Song, Khaled B. Letaief

In this paper, we propose a lightweight and flexible deep learning-based CSI feedback approach by capitalizing on deep equilibrium models.

A Self-adaptive Neuroevolution Approach to Constructing Deep Neural Network Architectures Across Different Types

2 code implementations27 Nov 2022 Zhenhao Shuai, Hongbo Liu, Zhaolin Wan, Wei-Jie Yu, Jun Zhang

One of the key settings in SANE is the search space defined by cells and organs self-adapted to different DNN types.

Task-Oriented Communication for Edge Video Analytics

1 code implementation25 Nov 2022 Jiawei Shao, Xinjie Zhang, Jun Zhang

With the development of artificial intelligence (AI) techniques and the increasing popularity of camera-equipped devices, many edge video analytics applications are emerging, calling for the deployment of computation-intensive AI models at the network edge.


FedFA: Federated Learning with Feature Anchors to Align Features and Classifiers for Heterogeneous Data

no code implementations17 Nov 2022 Tailin Zhou, Jun Zhang, Danny H. K. Tsang

However, we discover that these approaches fall short of the expected performance because they ignore the existence of a vicious cycle between classifier divergence and feature mapping inconsistency across clients, such that client models are updated in inconsistent feature space with diverged classifiers.

Federated Learning Image Classification

Blind Performance Prediction for Deep Learning Based Ultra-Massive MIMO Channel Estimation

no code implementations15 Nov 2022 Wentao Yu, Hengtao He, Xianghao Yu, Shenghui Song, Jun Zhang, Khaled B. Letaief

Reliability is of paramount importance for the physical layer of wireless systems due to its decisive impact on end-to-end performance.

Stochastic Coded Federated Learning: Theoretical Analysis and Incentive Mechanism Design

no code implementations8 Nov 2022 Yuchang Sun, Jiawei Shao, Yuyi Mao, Songze Li, Jun Zhang

During training, the server computes gradients on the global coded dataset to compensate for the missing model updates of the straggling devices.

Federated Learning Privacy Preserving

Deep Latent Mixture Model for Recommendation

no code implementations27 Oct 2022 Jun Zhang, Ping Li, Wei Wang

Recent advances in neural networks have been successfully applied to many tasks in online recommendation applications.

CAB: Comprehensive Attention Benchmarking on Long Sequence Modeling

1 code implementation14 Oct 2022 Jun Zhang, Shuyang Jiang, Jiangtao Feng, Lin Zheng, Lingpeng Kong

In this paper, we propose Comprehensive Attention Benchmark (CAB) under a fine-grained attention taxonomy with four distinguishable attention patterns, namely, noncausal self, causal self, noncausal cross, and causal cross attentions.

Benchmarking Long-range modeling

PARAGEN : A Parallel Generation Toolkit

1 code implementation7 Oct 2022 Jiangtao Feng, Yi Zhou, Jun Zhang, Xian Qian, Liwei Wu, Zhexi Zhang, Yanming Liu, Mingxuan Wang, Lei LI, Hao Zhou

PARAGEN is a PyTorch-based NLP toolkit for further development on parallel generation.

Model Selection

DReS-FL: Dropout-Resilient Secure Federated Learning for Non-IID Clients via Secret Data Sharing

no code implementations6 Oct 2022 Jiawei Shao, Yuchang Sun, Songze Li, Jun Zhang

Federated learning (FL) strives to enable collaborative training of machine learning models without centrally collecting clients' private data.

Federated Learning

SoccerNet 2022 Challenges Results

7 code implementations5 Oct 2022 Silvio Giancola, Anthony Cioppa, Adrien Deliège, Floriane Magera, Vladimir Somers, Le Kang, Xin Zhou, Olivier Barnich, Christophe De Vleeschouwer, Alexandre Alahi, Bernard Ghanem, Marc Van Droogenbroeck, Abdulrahman Darwish, Adrien Maglo, Albert Clapés, Andreas Luyts, Andrei Boiarov, Artur Xarles, Astrid Orcesi, Avijit Shah, Baoyu Fan, Bharath Comandur, Chen Chen, Chen Zhang, Chen Zhao, Chengzhi Lin, Cheuk-Yiu Chan, Chun Chuen Hui, Dengjie Li, Fan Yang, Fan Liang, Fang Da, Feng Yan, Fufu Yu, Guanshuo Wang, H. Anthony Chan, He Zhu, Hongwei Kan, Jiaming Chu, Jianming Hu, Jianyang Gu, Jin Chen, João V. B. Soares, Jonas Theiner, Jorge De Corte, José Henrique Brito, Jun Zhang, Junjie Li, Junwei Liang, Leqi Shen, Lin Ma, Lingchi Chen, Miguel Santos Marques, Mike Azatov, Nikita Kasatkin, Ning Wang, Qiong Jia, Quoc Cuong Pham, Ralph Ewerth, Ran Song, RenGang Li, Rikke Gade, Ruben Debien, Runze Zhang, Sangrok Lee, Sergio Escalera, Shan Jiang, Shigeyuki Odashima, Shimin Chen, Shoichi Masui, Shouhong Ding, Sin-wai Chan, Siyu Chen, Tallal El-Shabrawy, Tao He, Thomas B. Moeslund, Wan-Chi Siu, Wei zhang, Wei Li, Xiangwei Wang, Xiao Tan, Xiaochuan Li, Xiaolin Wei, Xiaoqing Ye, Xing Liu, Xinying Wang, Yandong Guo, YaQian Zhao, Yi Yu, YingYing Li, Yue He, Yujie Zhong, Zhenhua Guo, Zhiheng Li

The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team.

Action Spotting Camera Calibration +3

Text-Adaptive Multiple Visual Prototype Matching for Video-Text Retrieval

no code implementations27 Sep 2022 Chengzhi Lin, AnCong Wu, Junwei Liang, Jun Zhang, Wenhang Ge, Wei-Shi Zheng, Chunhua Shen

To address this problem, we propose a Text-Adaptive Multiple Visual Prototype Matching model, which automatically captures multiple prototypes to describe a video by adaptive aggregation of video token features.

Cross-Modal Retrieval Retrieval +2

Multi-dataset Training of Transformers for Robust Action Recognition

1 code implementation26 Sep 2022 Junwei Liang, Enwei Zhang, Jun Zhang, Chunhua Shen

We study the task of robust feature representations, aiming to generalize well on multiple datasets for action recognition.

Action Recognition Temporal Action Localization

DeepNoise: Signal and Noise Disentanglement based on Classifying Fluorescent Microscopy Images via Deep Learning

1 code implementation13 Sep 2022 Sen yang, Tao Shen, Yuqi Fang, Xiyue Wang, Jun Zhang, Wei Yang, Junzhou Huang, Xiao Han

The high-content image-based assay is commonly leveraged for identifying the phenotypic impact of genetic perturbations in biology field.

Disentanglement Drug Discovery +1

Augmented Deep Unfolding for Downlink Beamforming in Multi-cell Massive MIMO With Limited Feedback

no code implementations3 Sep 2022 Yifan Ma, Xianghao Yu, Jun Zhang, S. H. Song, Khaled B. Letaief

In limited feedback multi-user multiple-input multiple-output (MU-MIMO) cellular networks, users send quantized information about the channel conditions to the associated base station (BS) for downlink beamforming.


Few-Shot Learning of Accurate Folding Landscape for Protein Structure Prediction

2 code implementations20 Aug 2022 Jun Zhang, Sirui Liu, Mengyun Chen, Haotian Chu, Min Wang, Zidong Wang, Jialiang Yu, Ningxi Ni, Fan Yu, Diqing Chen, Yi Isaac Yang, Boxin Xue, Lijiang Yang, YuAn Liu, Yi Qin Gao

Data-driven predictive methods which can efficiently and accurately transform protein sequences into biologically active structures are highly valuable for scientific research and therapeutical development.

Denoising Few-Shot Learning +2

A Manifold-based Airfoil Geometric-feature Extraction and Discrepant Data Fusion Learning Method

no code implementations23 Jun 2022 Yu Xiang, Guangbo Zhang, Liwei Hu, Jun Zhang, Wenyong Wang

Geometrical shape of airfoils, together with the corresponding flight conditions, are crucial factors for aerodynamic performances prediction.

Multi-Task Learning

Resource-Constrained Edge AI with Early Exit Prediction

no code implementations15 Jun 2022 Rongkang Dong, Yuyi Mao, Jun Zhang

In this paper, we propose an early exit prediction mechanism to reduce the on-device computation overhead in a device-edge co-inference system supported by early-exit networks.

Federated Learning with GAN-based Data Synthesis for Non-IID Clients

no code implementations11 Jun 2022 Zijian Li, Jiawei Shao, Yuyi Mao, Jessie Hui Wang, Jun Zhang

A combination of the local private dataset and synthetic dataset with confident pseudo labels leads to nearly identical data distributions among clients, which improves the consistency among local models and benefits the global aggregation.

Federated Learning Privacy Preserving

Sparse Mixture-of-Experts are Domain Generalizable Learners

1 code implementation8 Jun 2022 Bo Li, Yifei Shen, Jingkang Yang, Yezhen Wang, Jiawei Ren, Tong Che, Jun Zhang, Ziwei Liu

It is motivated by an empirical finding that transformer-based models trained with empirical risk minimization (ERM) outperform CNN-based models employing state-of-the-art (SOTA) DG algorithms on multiple DG datasets.

Ranked #9 on Domain Generalization on DomainNet (using extra training data)

Domain Generalization Object Recognition

Evolution as a Service: A Privacy-Preserving Genetic Algorithm for Combinatorial Optimization

no code implementations27 May 2022 Bowen Zhao, Wei-neng Chen, Feng-Feng Wei, Ximeng Liu, Qingqi Pei, Jun Zhang

Specifically, PEGA enables users outsourcing COPs to the cloud server holding a competitive GA and approximating the optimal solution in a privacy-preserving manner.

Combinatorial Optimization Evolutionary Algorithms +2

Hybrid Far- and Near-Field Channel Estimation for THz Ultra-Massive MIMO via Fixed Point Networks

1 code implementation10 May 2022 Wentao Yu, Yifei Shen, Hengtao He, Xianghao Yu, Jun Zhang, Khaled B. Letaief

We draw inspirations from fixed point theory to develop an efficient deep learning based channel estimator with adaptive complexity and linear convergence guarantee.

Deep learning-based approach to reveal tumor mutational burden status from whole slide images across multiple cancer types

no code implementations7 Apr 2022 Siteng Chen, Jinxi Xiang, Xiyue Wang, Jun Zhang, Sen yang, Junzhou Huang, Wei Yang, Junhua Zheng, Xiao Han

MC-TMB algorithm also exhibited good generalization on the external validation cohort with an AUC of 0. 732 (0. 683-0. 761), and better performance when compared to other methods.

whole slide images

Making DeepFakes more spurious: evading deep face forgery detection via trace removal attack

no code implementations22 Mar 2022 Chi Liu, Huajie Chen, Tianqing Zhu, Jun Zhang, Wanlei Zhou

To evaluate the attack efficacy, we crafted heterogeneous security scenarios where the detectors were embedded with different levels of defense and the attackers' background knowledge of data varies.

Face Swapping

Graph Neural Networks for Wireless Communications: From Theory to Practice

1 code implementation21 Mar 2022 Yifei Shen, Jun Zhang, S. H. Song, Khaled B. Letaief

For design guidelines, we propose a unified framework that is applicable to general design problems in wireless networks, which includes graph modeling, neural architecture design, and theory-guided performance enhancement.

Communication-Efficient Federated Distillation with Active Data Sampling

no code implementations14 Mar 2022 Lumin Liu, Jun Zhang, S. H. Song, Khaled B. Letaief

Federated Distillation (FD) is a recently proposed alternative to enable communication-efficient and robust FL, which achieves orders of magnitude reduction of the communication overhead compared with FedAvg and is flexible to handle heterogeneous models at the clients.

Federated Learning Privacy Preserving +1

AugHover-Net: Augmenting Hover-net for Nucleus Segmentation and Classification

no code implementations4 Mar 2022 Wenhua Zhang, Jun Zhang

Connective nuclei may look very different from each other while some of them share a similar shape with the epithelial ones.


The Gene of Scientific Success

no code implementations17 Feb 2022 Xiangjie Kong, Jun Zhang, Da Zhang, Yi Bu, Ying Ding, Feng Xia

Under this consideration, our paper presents and analyzes the causal factors that are crucial for scholars' academic success.

Stochastic Coded Federated Learning with Convergence and Privacy Guarantees

no code implementations25 Jan 2022 Yuchang Sun, Jiawei Shao, Songze Li, Yuyi Mao, Jun Zhang

Federated learning (FL) has attracted much attention as a privacy-preserving distributed machine learning framework, where many clients collaboratively train a machine learning model by exchanging model updates with a parameter server instead of sharing their raw data.

Federated Learning Privacy Preserving

Data-Driven Deep Learning Based Hybrid Beamforming for Aerial Massive MIMO-OFDM Systems with Implicit CSI

no code implementations18 Jan 2022 Zhen Gao, Minghui Wu, Chun Hu, Feifei Gao, Guanghui Wen, Dezhi Zheng, Jun Zhang

To this end, by modeling the key transmission modules as an end-to-end (E2E) neural network, this paper proposes a data-driven deep learning (DL)-based unified hybrid beamforming framework for both the time division duplex (TDD) and frequency division duplex (FDD) systems with implicit channel state information (CSI).

Quantization Transfer Learning

A Critical Analysis of Image-based Camera Pose Estimation Techniques

no code implementations15 Jan 2022 Meng Xu, Youchen Wang, Bin Xu, Jun Zhang, Jian Ren, Stefan Poslad, Pengfei Xu

Camera, and associated with its objects within the field of view, localization could benefit many computer vision fields, such as autonomous driving, robot navigation, and augmented reality (AR).

Autonomous Driving Camera Localization +3

Weighted Encoding Optimization for Dynamic Single-pixel Imaging and Sensing

no code implementations8 Jan 2022 Xinrui Zhan, Liheng Bian, Chunli Zhu, Jun Zhang

While the network is training at a high sampling rate, the modulation patterns and corresponding weights are updated iteratively, which produces optimal ranked encoding series when converged.

Node-Aligned Graph Convolutional Network for Whole-Slide Image Representation and Classification

1 code implementation CVPR 2022 Yonghang Guan, Jun Zhang, Kuan Tian, Sen yang, Pei Dong, Jinxi Xiang, Wei Yang, Junzhou Huang, Yuyao Zhang, Xiao Han

In this paper, we propose a hierarchical global-to-local clustering strategy to build a Node-Aligned GCN (NAGCN) to represent WSI with rich local structural information as well as global distribution.

Clustering graph construction +2

Semi-Decentralized Federated Edge Learning with Data and Device Heterogeneity

no code implementations20 Dec 2021 Yuchang Sun, Jiawei Shao, Yuyi Mao, Jessie Hui Wang, Jun Zhang

By exploiting the low-latency communication among edge servers for efficient model sharing, SD-FEEL can incorporate more training data, while enjoying much lower latency compared with conventional federated learning.

Federated Learning Privacy Preserving

Asynchronous Semi-Decentralized Federated Edge Learning for Heterogeneous Clients

no code implementations9 Dec 2021 Yuchang Sun, Jiawei Shao, Yuyi Mao, Jun Zhang

Federated edge learning (FEEL) has drawn much attention as a privacy-preserving distributed learning framework for mobile edge networks.

Privacy Preserving

Learn to Communicate with Neural Calibration: Scalability and Generalization

no code implementations1 Oct 2021 Yifan Ma, Yifei Shen, Xianghao Yu, Jun Zhang, S. H. Song, Khaled B. Letaief

Furthermore, such networks will vary dynamically in a significant way, which makes it intractable to develop comprehensive analytical models.


Sk-Unet Model with Fourier Domain for Mitosis Detection

no code implementations1 Sep 2021 Sen yang, Feng Luo, Jun Zhang, Xiyue Wang

Mitotic count is the most important morphological feature of breast cancer grading.

Mitosis Detection

Task-Oriented Communication for Multi-Device Cooperative Edge Inference

2 code implementations1 Sep 2021 Jiawei Shao, Yuyi Mao, Jun Zhang

To enable low-latency cooperative inference, we propose a learning-based communication scheme that optimizes local feature extraction and distributed feature encoding in a task-oriented manner, i. e., to remove data redundancy and transmit information that is essential for the downstream inference task rather than reconstructing the data samples at the edge server.

Communication-Computation Efficient Device-Edge Co-Inference via AutoML

no code implementations30 Aug 2021 Xinjie Zhang, Jiawei Shao, Yuyi Mao, Jun Zhang

Device-edge co-inference, which partitions a deep neural network between a resource-constrained mobile device and an edge server, recently emerges as a promising paradigm to support intelligent mobile applications.

AutoML Feature Compression +1

$k$Folden: $k$-Fold Ensemble for Out-Of-Distribution Detection

1 code implementation29 Aug 2021 Xiaoya Li, Jiwei Li, Xiaofei Sun, Chun Fan, Tianwei Zhang, Fei Wu, Yuxian Meng, Jun Zhang

For a task with $k$ training labels, $k$Folden induces $k$ sub-models, each of which is trained on a subset with $k-1$ categories with the left category masked unknown to the sub-model.

Out-of-Distribution Detection Out of Distribution (OOD) Detection +2

Image-free single-pixel segmentation

no code implementations24 Aug 2021 Haiyan Liu, Liheng Bian, Jun Zhang

We envision that this image-free segmentation technique can be widely applied in various resource-limited platforms such as UAV and unmanned vehicle that require real-time sensing.

Semantic Segmentation

Semantic Reinforced Attention Learning for Visual Place Recognition

no code implementations19 Aug 2021 Guohao Peng, Yufeng Yue, Jun Zhang, Zhenyu Wu, Xiaoyu Tang, Danwei Wang

(2) By exploiting the interpretability of the local weighting scheme, a semantic constrained initialization is proposed so that the local attention can be reinforced by semantic priors.

Visual Place Recognition

How Powerful is Graph Convolution for Recommendation?

1 code implementation17 Aug 2021 Yifei Shen, Yongji Wu, Yao Zhang, Caihua Shan, Jun Zhang, Khaled B. Letaief, Dongsheng Li

In this paper, we endeavor to obtain a better understanding of GCN-based CF methods via the lens of graph signal processing.

Collaborative Filtering

Neural Calibration for Scalable Beamforming in FDD Massive MIMO with Implicit Channel Estimation

no code implementations3 Aug 2021 Yifan Ma, Yifei Shen, Xianghao Yu, Jun Zhang, S. H. Song, Khaled B. Letaief

Channel estimation and beamforming play critical roles in frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems.

Primary-Auxiliary Model Scheduling Based Estimation of the Vertical Wheel Force in a Full Vehicle System

no code implementations24 Jul 2021 Xueke Zheng, Runze Cai, Shuixin Xiao, Yu Qiu, Jun Zhang, Mian Li

A real-world application to the estimation of the vertical wheel force in a full vehicle system are, respectively, conducted to demonstrate the effectiveness of the proposed method.

Management Scheduling

Deep Adaptive Arbitrary Polynomial Chaos Expansion: A Mini-data-driven Semi-supervised Method for Uncertainty Quantification

1 code implementation22 Jul 2021 Wen Yao, Xiaohu Zheng, Jun Zhang, Ning Wang, Guijian Tang

Based on the adaptive aPC, a semi-supervised deep adaptive arbitrary polynomial chaos expansion (Deep aPCE) method is proposed to reduce the training data cost and improve the surrogate model accuracy.

Dimensionality Reduction

RBUE: A ReLU-Based Uncertainty Estimation Method of Deep Neural Networks

no code implementations15 Jul 2021 Yufeng Xia, Jun Zhang, Zhiqiang Gong, Tingsong Jiang, Wen Yao

Deep Ensemble is widely considered the state-of-the-art method which can estimate the uncertainty with higher quality, but it is very expensive to train and test.

Joint Activity Detection, Channel Estimation, and Data Decoding for Grant-free Massive Random Access

no code implementations12 Jul 2021 Xinyu Bian, Yuyi Mao, Jun Zhang

In particular, the common sparsity pattern in the received pilot and data signal has been ignored in most existing studies, and auxiliary information of channel decoding has not been utilized for user activity detection.

Action Detection Activity Detection

IDRLnet: A Physics-Informed Neural Network Library

1 code implementation9 Jul 2021 Wei Peng, Jun Zhang, Weien Zhou, Xiaoyu Zhao, Wen Yao, Xiaoqian Chen

Physics Informed Neural Network (PINN) is a scientific computing framework used to solve both forward and inverse problems modeled by Partial Differential Equations (PDEs).

Joint Deep Reversible Regression Model and Physics-Informed Unsupervised Learning for Temperature Field Reconstruction

1 code implementation22 Jun 2021 Zhiqiang Gong, Weien Zhou, Jun Zhang, Wei Peng, Wen Yao

To solve this problem, this work develops a novel physics-informed deep reversible regression models for temperature field reconstruction of heat-source systems (TFR-HSS), which can better reconstruct the temperature field with limited monitoring points unsupervisedly.


Learning 3D Shape Feature for Texture-Insensitive Person Re-Identification

1 code implementation CVPR 2021 Jiaxing Chen, Xinyang Jiang, Fudong Wang, Jun Zhang, Feng Zheng, Xing Sun, Wei-Shi Zheng

In this paper, rather than relying on texture based information, we propose to improve the robustness of person ReID against clothing texture by exploiting the information of a person's 3D shape.

3D Reconstruction Person Re-Identification

Pyramidal Dense Attention Networks for Lightweight Image Super-Resolution

no code implementations13 Jun 2021 Huapeng Wu, Jie Gui, Jun Zhang, James T. Kwok, Zhihui Wei

Recently, deep convolutional neural network methods have achieved an excellent performance in image superresolution (SR), but they can not be easily applied to embedded devices due to large memory cost.

Image Super-Resolution

Feedback Pyramid Attention Networks for Single Image Super-Resolution

no code implementations13 Jun 2021 Huapeng Wu, Jie Gui, Jun Zhang, James T. Kwok, Zhihui Wei

Recently, convolutional neural network (CNN) based image super-resolution (SR) methods have achieved significant performance improvement.

Image Super-Resolution

Invariant Information Bottleneck for Domain Generalization

no code implementations11 Jun 2021 Bo Li, Yifei Shen, Yezhen Wang, Wenzhen Zhu, Colorado J. Reed, Jun Zhang, Dongsheng Li, Kurt Keutzer, Han Zhao

IIB significantly outperforms IRM on synthetic datasets, where the pseudo-invariant features and geometric skews occur, showing the effectiveness of proposed formulation in overcoming failure modes of IRM.

Domain Generalization

Agile wide-field imaging with selective high resolution

no code implementations9 Jun 2021 Lintao Peng, Liheng Bian, Tiexin Liu, Jun Zhang

In this work, we report an agile wide-field imaging framework with selective high resolution that requires only two detectors.

Vocal Bursts Intensity Prediction

A Comprehensive Survey and Taxonomy on Single Image Dehazing Based on Deep Learning

1 code implementation7 Jun 2021 Jie Gui, Xiaofeng Cong, Yuan Cao, Wenqi Ren, Jun Zhang, Jing Zhang, Jiuxin Cao, DaCheng Tao

With the development of convolutional neural networks, hundreds of deep learning based dehazing methods have been proposed.

Image Dehazing Single Image Dehazing

Privacy Inference Attacks and Defenses in Cloud-based Deep Neural Network: A Survey

no code implementations13 May 2021 XiaoYu Zhang, Chao Chen, Yi Xie, Xiaofeng Chen, Jun Zhang, Yang Xiang

This survey presents the most recent findings of privacy attacks and defenses appeared in cloud-based neural network services.

Cloud Computing

Communication-Efficient Federated Learning with Dual-Side Low-Rank Compression

no code implementations26 Apr 2021 Zhefeng Qiao, Xianghao Yu, Jun Zhang, Khaled B. Letaief

Federated learning (FL) is a promising and powerful approach for training deep learning models without sharing the raw data of clients.

Federated Learning Low-rank compression

Joint Activity Detection and Data Decoding in Massive Random Access via a Turbo Receiver

no code implementations26 Apr 2021 Xinyu Bian, Yuyi Mao, Jun Zhang

In this paper, we propose a turbo receiver for joint activity detection and data decoding in grant-free massive random access, which iterates between a detector and a belief propagation (BP)-based channel decoder.

Action Detection Activity Detection

Semi-Decentralized Federated Edge Learning for Fast Convergence on Non-IID Data

no code implementations26 Apr 2021 Yuchang Sun, Jiawei Shao, Yuyi Mao, Jessie Hui Wang, Jun Zhang

Federated edge learning (FEEL) has emerged as an effective approach to reduce the large communication latency in Cloud-based machine learning solutions, while preserving data privacy.

Federated Learning

Affine-modeled video extraction from a single motion blurred image

no code implementations8 Apr 2021 Daoyu Li, Liheng Bian, Jun Zhang

Recovering these sharp video frames from a single blurred image is nontrivial, due to not only its strong ill-posedness, but also various types of complex motion in reality such as rotation and motion in depth.


Large-scale phase retrieval

no code implementations6 Apr 2021 Xuyang Chang, Liheng Bian, Jun Zhang

In computational phase imaging, phase retrieval (PR) is required to reconstruct both amplitude and phase in complex space from intensity-only measurements.


Decentralized Statistical Inference with Unrolled Graph Neural Networks

1 code implementation4 Apr 2021 He Wang, Yifei Shen, Ziyuan Wang, Dongsheng Li, Jun Zhang, Khaled B. Letaief, Jie Lu

In this paper, we investigate the decentralized statistical inference problem, where a network of agents cooperatively recover a (structured) vector from private noisy samples without centralized coordination.

HMM-Free Encoder Pre-Training for Streaming RNN Transducer

no code implementations2 Apr 2021 Lu Huang, Jingyu Sun, Yufeng Tang, JunFeng Hou, Jinkun Chen, Jun Zhang, Zejun Ma

This work describes an encoder pre-training procedure using frame-wise label to improve the training of streaming recurrent neural network transducer (RNN-T) model.

Speech Recognition

Hierarchical Federated Learning with Quantization: Convergence Analysis and System Design

no code implementations26 Mar 2021 Lumin Liu, Jun Zhang, Shenghui Song, Khaled B. Letaief

Hierarchical FL, with a client-edge-cloud aggregation hierarchy, can effectively leverage both the cloud server's access to many clients' data and the edge servers' closeness to the clients to achieve a high communication efficiency.

Federated Learning Quantization

A Deep Neural Network Surrogate Modeling Benchmark for Temperature Field Prediction of Heat Source Layout

1 code implementation20 Mar 2021 Xianqi Chen, Xiaoyu Zhao, Zhiqiang Gong, Jun Zhang, Weien Zhou, Xiaoqian Chen, Wen Yao

Thermal issue is of great importance during layout design of heat source components in systems engineering, especially for high functional-density products.

Layout Design Model Selection +1

Single-photon imaging over 200 km

no code implementations10 Mar 2021 Zheng-Ping Li, Jun-Tian Ye, Xin Huang, Peng-Yu Jiang, Yuan Cao, Yu Hong, Chao Yu, Jun Zhang, Qiang Zhang, Cheng-Zhi Peng, Feihu Xu, Jian-Wei Pan

Long-range active imaging has widespread applications in remote sensing and target recognition.

Ask&Confirm: Active Detail Enriching for Cross-Modal Retrieval with Partial Query

1 code implementation ICCV 2021 Guanyu Cai, Jun Zhang, Xinyang Jiang, Yifei Gong, Lianghua He, Fufu Yu, Pai Peng, Xiaowei Guo, Feiyue Huang, Xing Sun

However, the performance of existing methods suffers in real life since the user is likely to provide an incomplete description of an image, which often leads to results filled with false positives that fit the incomplete description.

Cross-Modal Retrieval Image Retrieval +1

Supporting More Active Users for Massive Access via Data-assisted Activity Detection

no code implementations17 Feb 2021 Xinyu Bian, Yuyi Mao, Jun Zhang

Massive machine-type communication (mMTC) has been regarded as one of the most important use scenarios in the fifth generation (5G) and beyond wireless networks, which demands scalable access for a large number of devices.

Action Detection Activity Detection

Machine Learning Based Cyber Attacks Targeting on Controlled Information: A Survey

2 code implementations16 Feb 2021 Yuantian Miao, Chao Chen, Lei Pan, Qing-Long Han, Jun Zhang, Yang Xiang

Stealing attack against controlled information, along with the increasing number of information leakage incidents, has become an emerging cyber security threat in recent years.

BIG-bench Machine Learning

Learning Task-Oriented Communication for Edge Inference: An Information Bottleneck Approach

1 code implementation8 Feb 2021 Jiawei Shao, Yuyi Mao, Jun Zhang

Extensive experiments evidence that the proposed task-oriented communication system achieves a better rate-distortion tradeoff than baseline methods and significantly reduces the feature transmission latency in dynamic channel conditions.


Attentional Pyramid Pooling of Salient Visual Residuals for Place Recognition

no code implementations ICCV 2021 Guohao Peng, Jun Zhang, Heshan Li, Danwei Wang

The core of visual place recognition (VPR) lies in how to identify task-relevant visual cues and embed them into discriminative representations.

Visual Place Recognition

Molecular CT: Unifying Geometry and Representation Learning for Molecules at Different Scales

no code implementations22 Dec 2020 Jun Zhang, Yaqiang Zhou, Yao-Kun Lei, Yi Isaac Yang, Yi Qin Gao

Deep learning is changing many areas in molecular physics, and it has shown great potential to deliver new solutions to challenging molecular modeling problems.

Representation Learning

Hawking radiation from nonrotating singularity-free black holes in conformal gravity

no code implementations2 Dec 2020 Jun Zhang, Yuan Sun

Besides, we investigate the dependence of the greybody factor and the sparsity of Hawking radiation on the conformal parameters.

General Relativity and Quantum Cosmology

Deep Reinforcement Learning of Transition States

no code implementations13 Nov 2020 Jun Zhang, Yao-Kun Lei, Zhen Zhang, Xu Han, Maodong Li, Lijiang Yang, Yi Isaac Yang, Yi Qin Gao

Combining reinforcement learning (RL) and molecular dynamics (MD) simulations, we propose a machine-learning approach (RL$^\ddag$) to automatically unravel chemical reaction mechanisms.

reinforcement-learning Reinforcement Learning (RL)

Improving RNN transducer with normalized jointer network

no code implementations3 Nov 2020 Mingkun Huang, Jun Zhang, Meng Cai, Yang Zhang, Jiali Yao, Yongbin You, Yi He, Zejun Ma

In this work, we analyze the cause of the huge gradient variance in RNN-T training and proposed a new \textit{normalized jointer network} to overcome it.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Dynamic latency speech recognition with asynchronous revision

no code implementations3 Nov 2020 Mingkun Huang, Meng Cai, Jun Zhang, Yang Zhang, Yongbin You, Yi He, Zejun Ma

In this work we propose an inference technique, asynchronous revision, to unify streaming and non-streaming speech recognition models.

speech-recognition Speech Recognition

Branchy-GNN: a Device-Edge Co-Inference Framework for Efficient Point Cloud Processing

1 code implementation27 Oct 2020 Jiawei Shao, Haowei Zhang, Yuyi Mao, Jun Zhang

The recent advancements of three-dimensional (3D) data acquisition devices have spurred a new breed of applications that rely on point cloud data processing.

Distributed, Parallel, and Cluster Computing

DeFuzz: Deep Learning Guided Directed Fuzzing

no code implementations23 Oct 2020 Xiaogang Zhu, Shigang Liu, Xian Li, Sheng Wen, Jun Zhang, Camtepe Seyit, Yang Xiang

Fuzzing is one of the most effective technique to identify potential software vulnerabilities.

Vulnerability Detection

From em-Projections to Variational Auto-Encoder

no code implementations NeurIPS Workshop DL-IG 2020 Tian Han, Jun Zhang, Ying Nian Wu

This paper reviews the em-projections in information geometry and the recent understanding of variational auto-encoder, and explains that they share a common formulation as joint minimization of the Kullback-Leibler divergence between two manifolds of probability distributions, and the joint minimization can be implemented by alternating projections or alternating gradient descent.

Group-Buying Recommendation for Social E-Commerce

1 code implementation14 Oct 2020 Jun Zhang, Chen Gao, Depeng Jin, Yong Li

Group-buying recommendation for social e-commerce, which recommends an item list when users want to launch a group, plays an important role in the group success ratio and sales.

Microscope Based HER2 Scoring System

no code implementations15 Sep 2020 Jun Zhang, Kuan Tian, Pei Dong, Haocheng Shen, Kezhou Yan, Jianhua Yao, Junzhou Huang, Xiao Han

Recently, artificial intelligence (AI) has been used in various disease diagnosis to improve diagnostic accuracy and reliability, but the interpretation of diagnosis results is still an open problem.

Flow Field Reconstructions with GANs based on Radial Basis Functions

no code implementations11 Aug 2020 Liwei Hu, Wenyong Wang, Yu Xiang, Jun Zhang

Motivated by the problems of existing approaches and inspired by the success of the generative adversarial networks (GANs) in the field of computer vision, we prove an optimal discriminator theorem that the optimal discriminator of a GAN is a radial basis function neural network (RBFNN) while dealing with nonlinear sparse FFD regression and generation.


Robust Ego and Object 6-DoF Motion Estimation and Tracking

2 code implementations28 Jul 2020 Jun Zhang, Mina Henein, Robert Mahony, Viorela Ila

The problem of tracking self-motion as well as motion of objects in the scene using information from a camera is known as multi-body visual odometry and is a challenging task.

Autonomous Driving Motion Estimation +2

Graph Neural Networks for Scalable Radio Resource Management: Architecture Design and Theoretical Analysis

1 code implementation15 Jul 2020 Yifei Shen, Yuanming Shi, Jun Zhang, Khaled B. Letaief

In this paper, we propose to apply graph neural networks (GNNs) to solve large-scale radio resource management problems, supported by effective neural network architecture design and theoretical analysis.

Distributed Optimization Management

EPI-based Oriented Relation Networks for Light Field Depth Estimation

1 code implementation9 Jul 2020 Kunyuan Li, Jun Zhang, Rui Sun, Xu-Dong Zhang, Jun Gao

Based on the observation that an oriented line and its neighboring pixels in an EPI share a similar linear structure, we propose an end-to-end fully convolutional network (FCN) to estimate the depth value of the intersection point on the horizontal and vertical EPIs.

Data Augmentation Depth Estimation

Communication-Computation Trade-Off in Resource-Constrained Edge Inference

1 code implementation3 Jun 2020 Jiawei Shao, Jun Zhang

The recent breakthrough in artificial intelligence (AI), especially deep neural networks (DNNs), has affected every branch of science and technology.

Edge-computing Model Compression

Deep Denoising Neural Network Assisted Compressive Channel Estimation for mmWave Intelligent Reflecting Surfaces

1 code implementation3 Jun 2020 Shicong Liu, Zhen Gao, Jun Zhang, Marco Di Renzo, Mohamed-Slim Alouini

Integrating large intelligent reflecting surfaces (IRS) into millimeter-wave (mmWave) massive multi-input-multi-ouput (MIMO) has been a promising approach for improved coverage and throughput.

Compressive Sensing Denoising

VDO-SLAM: A Visual Dynamic Object-aware SLAM System

1 code implementation22 May 2020 Jun Zhang, Mina Henein, Robert Mahony, Viorela Ila

Combining Simultaneous Localisation and Mapping (SLAM) estimation and dynamic scene modelling can highly benefit robot autonomy in dynamic environments.


Cores in discrete exchange economies with complex endowments

no code implementations19 May 2020 Jun Zhang

The core is a traditional and useful solution concept in economic theory.


Efficient and fair trading algorithms in market design environments

no code implementations14 May 2020 Jingsheng Yu, Jun Zhang

We propose a new method to define trading algorithms in market design environments.


Target-based Sentiment Annotation in Chinese Financial News

no code implementations LREC 2020 Chaofa Yuan, Yu-Han Liu, Rongdi Yin, Jun Zhang, Qinling Zhu, Ruibin Mao, Ruifeng Xu

Based on high quality annotation guideline and effective quality control strategy, a corpus with 8, 314 target-level sentiment annotation is constructed on 6, 336 paragraphs from Chinese financial news text.

Sentiment Analysis

The Design and Construction of a Chinese Sarcasm Dataset

no code implementations LREC 2020 Xiaochang Gong, Qin Zhao, Jun Zhang, Ruibin Mao, Ruifeng Xu

Thus, the detection and processing of sarcasm is important to social media analysis. However, most existing sarcasm dataset are in English and there is still a lack of authoritative Chinese sarcasm dataset.

Blind Data Detection in Massive MIMO via $\ell_3$-norm Maximization over the Stiefel Manifold

no code implementations26 Apr 2020 Ye Xue, Yifei Shen, Vincent Lau, Jun Zhang, Khaled B. Letaief

Specifically, we propose a novel $\ell_3$-norm-based formulation to recover the data without channel estimation.

A Perspective on Deep Learning for Molecular Modeling and Simulations

no code implementations25 Apr 2020 Jun Zhang, Yao-Kun Lei, Zhen Zhang, Junhan Chang, Maodong Li, Xu Han, Lijiang Yang, Yi Isaac Yang, Yi Qin Gao

Deep learning is transforming many areas in science, and it has great potential in modeling molecular systems.

Accelerating Physics-Informed Neural Network Training with Prior Dictionaries

1 code implementation17 Apr 2020 Wei Peng, Weien Zhou, Jun Zhang, Wen Yao

Physics-Informed Neural Networks (PINNs) can be regarded as general-purpose PDE solvers, but it might be slow to train PINNs on particular problems, and there is no theoretical guarantee of corresponding error bounds.

Scene Text Recognition via Transformer

no code implementations18 Mar 2020 Xinjie Feng, Hongxun Yao, Yuankai Qi, Jun Zhang, Shengping Zhang

Different from previous transformer based models [56, 34], which just use the decoder of the transformer to decode the convolutional attention, the proposed method use a convolutional feature maps as word embedding input into transformer.

Scene Text Recognition

GATCluster: Self-Supervised Gaussian-Attention Network for Image Clustering

1 code implementation ECCV 2020 Chuang Niu, Jun Zhang, Ge Wang, Jimin Liang

To train the GATCluster in a completely unsupervised manner, we design four self-learning tasks with the constraints of transformation invariance, separability maximization, entropy analysis, and attention mapping.

Clustering Image Clustering +2