Search Results for author: Jing Yang

Found 51 papers, 12 papers with code

The USTC-NELSLIP Offline Speech Translation Systems for IWSLT 2022

no code implementations IWSLT (ACL) 2022 Weitai Zhang, Zhongyi Ye, Haitao Tang, Xiaoxi Li, Xinyuan Zhou, Jing Yang, Jianwei Cui, Dan Liu, Junhua Liu, LiRong Dai

This paper describes USTC-NELSLIP’s submissions to the IWSLT 2022 Offline Speech Translation task, including speech translation of talks from English to German, English to Chinese and English to Japanese.


Safe Exploration Incurs Nearly No Additional Sample Complexity for Reward-free RL

no code implementations28 Jun 2022 Ruiquan Huang, Jing Yang, Yingbin Liang

We then particularize the SWEET framework to the tabular and the low-rank MDP settings, and develop algorithms coined Tabular-SWEET and Low-rank-SWEET, respectively.

Safe Exploration

Unified BERT for Few-shot Natural Language Understanding

no code implementations24 Jun 2022 Junyu Lu, Ping Yang, Ruyi Gan, Jing Yang, Jiaxing Zhang

Even as pre-trained language models share a semantic encoder, natural language understanding suffers from a diversity of output schemas.

Natural Language Understanding

Counting Varying Density Crowds Through Density Guided Adaptive Selection CNN and Transformer Estimation

no code implementations21 Jun 2022 Yuehai Chen, Jing Yang, Badong Chen, Shaoyi Du

Thus, CNN could locate and estimate crowd accurately in low-density regions, while it is hard to properly perceive density in high-density regions.

Crowd Counting

Provable Benefit of Multitask Representation Learning in Reinforcement Learning

no code implementations13 Jun 2022 Yuan Cheng, Songtao Feng, Jing Yang, Hong Zhang, Yingbin Liang

To the best of our knowledge, this is the first theoretical study that characterizes the benefit of representation learning in exploration-based reward-free multitask RL for both upstream and downstream tasks.

Offline RL reinforcement-learning +1

Knowledge Distillation Meets Open-Set Semi-Supervised Learning

1 code implementation13 May 2022 Jing Yang, Xiatian Zhu, Adrian Bulat, Brais Martinez, Georgios Tzimiropoulos

The key idea is that we leverage the teacher's classifier as a semantic critic for evaluating the representations of both teacher and student and distilling the semantic knowledge with high-order structured information over all feature dimensions.

Face Recognition Knowledge Distillation

Transformer-based Cross-Modal Recipe Embeddings with Large Batch Training

no code implementations10 May 2022 Jing Yang, Junwen Chen, Keiji Yanai

In this paper, we present a cross-modal recipe retrieval framework, Transformer-based Network for Large Batch Training (TNLBT), which is inspired by ACME~(Adversarial Cross-Modal Embedding) and H-T~(Hierarchical Transformer).

Contrastive Learning Image Generation +1

Killing Two Birds with One Stone:Efficient and Robust Training of Face Recognition CNNs by Partial FC

1 code implementation28 Mar 2022 Xiang An, Jiankang Deng, Jia Guo, Ziyong Feng, Xuhan Zhu, Jing Yang, Tongliang Liu

In each iteration, positive class centers and a random subset of negative class centers are selected to compute the margin-based softmax loss.

Face Recognition Face Verification

On Federated Learning with Energy Harvesting Clients

no code implementations12 Feb 2022 Cong Shen, Jing Yang, Jie Xu

Catering to the proliferation of Internet of Things devices and distributed machine learning at the edge, we propose an energy harvesting federated learning (EHFL) framework in this paper.

Federated Learning

Multi-channel Attentive Graph Convolutional Network With Sentiment Fusion For Multimodal Sentiment Analysis

no code implementations25 Jan 2022 Luwei Xiao, Xingjiao Wu, Wen Wu, Jing Yang, Liang He

This paper proposes a Multi-channel Attentive Graph Convolutional Network (MAGCN), consisting of two main components: cross-modality interactive learning and sentimental feature fusion.

Multimodal Sentiment Analysis

Killing Two Birds With One Stone: Efficient and Robust Training of Face Recognition CNNs by Partial FC

no code implementations CVPR 2022 Xiang An, Jiankang Deng, Jia Guo, Ziyong Feng, Xuhan Zhu, Jing Yang, Tongliang Liu

In each iteration, positive class centers and a random subset of negative class centers are selected to compute the margin-based softmax loss.

Face Recognition

Feature Generation and Hypothesis Verification for Reliable Face Anti-Spoofing

1 code implementation30 Dec 2021 Shice Liu, Shitao Lu, Hongyi Xu, Jing Yang, Shouhong Ding, Lizhuang Ma

However, the improvement is still limited by two issues: 1) It is difficult to perfectly map all faces to a shared feature space.

Disentanglement Domain Generalization +1

Duck swarm algorithm: a novel swarm intelligence algorithm

no code implementations27 Dec 2021 Mengjian Zhang, Guihua Wen, Jing Yang

A swarm intelligence-based optimization algorithm, named Duck Swarm Algorithm (DSA), is proposed in this paper.

Federated Linear Contextual Bandits

no code implementations NeurIPS 2021 Ruiquan Huang, Weiqiang Wu, Jing Yang, Cong Shen

This paper presents a novel federated linear contextual bandits model, where individual clients face different $K$-armed stochastic bandits coupled through common global parameters.

Multi-Armed Bandits

Scalable Fact-checking with Human-in-the-Loop

1 code implementation22 Sep 2021 Jing Yang, Didier Vega-Oliveros, Tais Seibt, Anderson Rocha

Researchers have been investigating automated solutions for fact-checking in a variety of fronts.

Fact Checking

Deep-learning-based Hyperspectral imaging through a RGB camera

no code implementations12 Jul 2021 Xinyu Gao, Tianlang Wang, Jing Yang, Jinchao Tao, Yanqing Qiu, Yanlong Meng, Banging Mao, Pengwei Zhou, Yi Li

Hyperspectral image (HSI) contains both spatial pattern and spectral information which has been widely used in food safety, remote sensing, and medical detection.

Region-Aware Network: Model Human's Top-Down Visual Perception Mechanism for Crowd Counting

no code implementations23 Jun 2021 Yuehai Chen, Jing Yang, Dong Zhang, Kun Zhang, Badong Chen, Shaoyi Du

More specifically, we scan the whole input images and its priority maps in the form of column vector to obtain a relevance matrix estimating their similarity.

Crowd Counting

Variational Prototype Learning for Deep Face Recognition

no code implementations CVPR 2021 Jiankang Deng, Jia Guo, Jing Yang, Alexandros Lattas, Stefanos Zafeiriou

Deep face recognition has achieved remarkable improvements due to the introduction of margin-based softmax loss, in which the prototype stored in the last linear layer represents the center of each class.

Face Recognition

Multi-Spectrally Constrained Transceiver Design against Signal-Dependent Interference

no code implementations10 May 2021 Jing Yang, Augusto Aubry, Antonio De Maio, Xianxiang Yu, Guolong Cui

This paper focuses on the joint synthesis of constant envelope transmit signal and receive filter aimed at optimizing radar performance in signal-dependent interference and spectrally contested-congested environments.

Document Layout Analysis via Dynamic Residual Feature Fusion

no code implementations7 Apr 2021 Xingjiao Wu, Ziling Hu, Xiangcheng Du, Jing Yang, Liang He

The document layout analysis (DLA) aims to split the document image into different interest regions and understand the role of each region, which has wide application such as optical character recognition (OCR) systems and document retrieval.

Document Layout Analysis Optical Character Recognition

Pre-training strategies and datasets for facial representation learning

2 code implementations30 Mar 2021 Adrian Bulat, Shiyang Cheng, Jing Yang, Andrew Garbett, Enrique Sanchez, Georgios Tzimiropoulos

Recent work on Deep Learning in the area of face analysis has focused on supervised learning for specific tasks of interest (e. g. face recognition, facial landmark localization etc.)

3D Face Reconstruction 3D Facial Landmark Localization +11

Robust Kalman filter-based dynamic state estimation of natural gas pipeline networks

no code implementations26 Feb 2021 Liang Chen, Peng Jin, Jing Yang, Yang Li, Yi Song

To obtain the accurate transient states of the big scale natural gas pipeline networks under the bad data and non-zero mean noises conditions, a robust Kalman filter-based dynamic state estimation method is proposed using the linearized gas pipeline transient flow equations in this paper.

Federated Multi-armed Bandits with Personalization

1 code implementation25 Feb 2021 Chengshuai Shi, Cong Shen, Jing Yang

A general framework of personalized federated multi-armed bandits (PF-MAB) is proposed, which is a new bandit paradigm analogous to the federated learning (FL) framework in supervised learning and enjoys the features of FL with personalization.

Federated Learning Multi-Armed Bandits

Magnetic field generation from bubble collisions during first-order phase transition

no code implementations2 Feb 2021 Jing Yang, Ligong Bian

We study the magnetic fields generation from the cosmological first-order electroweak phase transition.

Cosmology and Nongalactic Astrophysics High Energy Physics - Phenomenology High Energy Physics - Theory

Experimental demonstration of superresolution of partially coherent light sources using parity sorting

no code implementations2 Feb 2021 S. A. Wadood, Yiyu Zhou, Jing Yang, Kevin Liang, M. A. Alonso, X. -F. Qian, T. Malhotra, S. M. Hashemi Rafsanjani, Andrew N. Jordan, Robert W. Boyd, A. N. Vamivakas

Analyses based on quantum metrology have shown that the ability to localize the positions of two incoherent point sources can be significantly enhanced through the use of mode sorting.

Optics Quantum Physics

Knowledge distillation via softmax regression representation learning

no code implementations ICLR 2021 Jing Yang, Brais Martinez, Adrian Bulat, Georgios Tzimiropoulos

We advocate for a method that optimizes the output feature of the penultimate layer of the student network and hence is directly related to representation learning.

Knowledge Distillation Model Compression +1

OrgMining 2.0: A Novel Framework for Organizational Model Mining from Event Logs

no code implementations24 Nov 2020 Jing Yang, Chun Ouyang, Wil M. P. van der Aalst, Arthur H. M. ter Hofstede, Yang Yu

We demonstrate the feasibility of this framework by proposing an approach underpinned by the framework for organizational model discovery, and also conduct experiments on real-life event logs to discover and evaluate organizational models.

Model Discovery

DARE: AI-based Diver Action Recognition System using Multi-Channel CNNs for AUV Supervision

no code implementations16 Nov 2020 Jing Yang, James P. Wilson, Shalabh Gupta

With the growth of sensing, control and robotic technologies, autonomous underwater vehicles (AUVs) have become useful assistants to human divers for performing various underwater operations.

Action Recognition Autonomous Driving

Adaptive 3D Face Reconstruction from a Single Image

no code implementations8 Jul 2020 Kun Li, Jing Yang, Nianhong Jiao, Jinsong Zhang, Yu-Kun Lai

3D face reconstruction from a single image is a challenging problem, especially under partial occlusions and extreme poses.

3D Face Reconstruction Pose Estimation

Knowledge distillation via adaptive instance normalization

no code implementations9 Mar 2020 Jing Yang, Brais Martinez, Adrian Bulat, Georgios Tzimiropoulos

To this end, we propose a new knowledge distillation method based on transferring feature statistics, specifically the channel-wise mean and variance, from the teacher to the student.

Knowledge Distillation Model Compression

Stochastic Linear Contextual Bandits with Diverse Contexts

no code implementations5 Mar 2020 Weiqiang Wu, Jing Yang, Cong Shen

In this paper, we investigate the impact of context diversity on stochastic linear contextual bandits.

Multi-Armed Bandits

Decentralized Multi-player Multi-armed Bandits with No Collision Information

no code implementations29 Feb 2020 Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang

The decentralized stochastic multi-player multi-armed bandit (MP-MAB) problem, where the collision information is not available to the players, is studied in this paper.

Multi-Armed Bandits

MODMA dataset: a Multi-modal Open Dataset for Mental-disorder Analysis

no code implementations20 Feb 2020 Hanshu Cai, Yiwen Gao, Shuting Sun, Na Li, Fuze Tian, Han Xiao, Jianxiu Li, Zhengwu Yang, Xiaowei Li, Qinglin Zhao, Zhenyu Liu, Zhijun Yao, Minqiang Yang, Hong Peng, Jing Zhu, Xiaowei Zhang, Guoping Gao, Fang Zheng, Rui Li, Zhihua Guo, Rong Ma, Jing Yang, Lan Zhang, Xiping Hu, Yumin Li, Bin Hu

The EEG dataset includes not only data collected using traditional 128-electrodes mounted elastic cap, but also a novel wearable 3-electrode EEG collector for pervasive applications.


A Real-Time Deep Network for Crowd Counting

1 code implementation16 Feb 2020 Xiaowen Shi, Xin Li, Caili Wu, Shuchen Kong, Jing Yang, Liang He

Automatic analysis of highly crowded people has attracted extensive attention from computer vision research.

Crowd Counting

Cascaded Detail-Preserving Networks for Super-Resolution of Document Images

no code implementations25 Nov 2019 Zhichao Fu, Yu Kong, Yingbin Zheng, Hao Ye, Wenxin Hu, Jing Yang, Liang He

The accuracy of OCR is usually affected by the quality of the input document image and different kinds of marred document images hamper the OCR results.

Image Super-Resolution Optical Character Recognition

Meta-neural-network for Realtime and Passive Deep-learning-based Object Recognition

no code implementations16 Sep 2019 Jingkai Weng, Yujiang Ding, Chengbo Hu, Xue-Feng Zhu, Bin Liang, Jing Yang, Jianchun Cheng

Deep-learning recently show great success across disciplines yet conventionally require time-consuming computer processing or bulky-sized diffractive elements.

Handwritten Digit Recognition Object Recognition

Edge-Aware Deep Image Deblurring

no code implementations4 Jul 2019 Zhichao Fu, Tianlong Ma, Yingbin Zheng, Hao Ye, Jing Yang, Liang He

In this paper, we resort to human visual demands of sharp edges and propose a two-phase edge-aware deep network to improve deep image deblurring.

Deblurring Edge Detection +1

Fast Video Crowd Counting with a Temporal Aware Network

no code implementations4 Jul 2019 Xingjiao Wu, Baohan Xu, Yingbin Zheng, Hao Ye, Jing Yang, Liang He

Crowd counting aims to count the number of instantaneous people in a crowded space, and many promising solutions have been proposed for single image crowd counting.

Crowd Counting

Online Learning with Diverse User Preferences

no code implementations23 Jan 2019 Chao Gan, Jing Yang, Ruida Zhou, Cong Shen

We aim to show that when the user preferences are sufficiently diverse and each arm can be optimal for certain users, the O(log T) regret incurred by exploring the sub-optimal arms under the standard stochastic MAB setting can be reduced to a constant.

online learning

Adaptive Scenario Discovery for Crowd Counting

1 code implementation6 Dec 2018 Xingjiao Wu, Yingbin Zheng, Hao Ye, Wenxin Hu, Jing Yang, Liang He

Crowd counting, i. e., estimation number of the pedestrian in crowd images, is emerging as an important research problem with the public security applications.

Crowd Counting

Runtime Analysis for Self-adaptive Mutation Rates

no code implementations30 Nov 2018 Benjamin Doerr, Carsten Witt, Jing Yang

We propose and analyze a self-adaptive version of the $(1,\lambda)$ evolutionary algorithm in which the current mutation rate is part of the individual and thus also subject to mutation.

Otem&Utem: Over- and Under-Translation Evaluation Metric for NMT

1 code implementation24 Jul 2018 Jing Yang, Biao Zhang, Yue Qin, Xiangwen Zhang, Qian Lin, Jinsong Su

Although neural machine translation(NMT) yields promising translation performance, it unfortunately suffers from over- and under-translation is- sues [Tu et al., 2016], of which studies have become research hotspots in NMT.

Machine Translation Translation

Optimal Parameter Choices via Precise Black-Box Analysis

no code implementations9 Jul 2018 Benjamin Doerr, Carola Doerr, Jing Yang

It has been observed that some working principles of evolutionary algorithms, in particular, the influence of the parameters, cannot be understood from results on the asymptotic order of the runtime, but only from more precise results.

Cost-Aware Learning and Optimization for Opportunistic Spectrum Access

no code implementations11 Apr 2018 Chao Gan, Ruida Zhou, Jing Yang, Cong Shen

Our objective is to understand how the costs and reward of the actions would affect the optimal behavior of the user in both offline and online settings, and design the corresponding opportunistic spectrum access strategies to maximize the expected cumulative net reward (i. e., reward-minus-cost).

The (1+$λ$) Evolutionary Algorithm with Self-Adjusting Mutation Rate

no code implementations7 Apr 2017 Benjamin Doerr, Christian Gießen, Carsten Witt, Jing Yang

We propose a new way to self-adjust the mutation rate in population-based evolutionary algorithms in discrete search spaces.

Adaptive Compressive Tracking via Online Vector Boosting Feature Selection

no code implementations21 Apr 2015 Qingshan Liu, Jing Yang, Kaihua Zhang, Yi Wu

Recently, the compressive tracking (CT) method has attracted much attention due to its high efficiency, but it cannot well deal with the large scale target appearance variations due to its data-independent random projection matrix that results in less discriminative features.

feature selection

Cannot find the paper you are looking for? You can Submit a new open access paper.