Search Results for author: Zheng Zhang

Found 132 papers, 58 papers with code

Region Graph Embedding Network for Zero-Shot Learning

no code implementations ECCV 2020 Guo-Sen Xie, Li Liu, Fan Zhu, Fang Zhao, Zheng Zhang, Yazhou Yao, Jie Qin, Ling Shao

To exploit the progressive interactions among these regions, we represent them as a region graph, on which the parts relation reasoning is performed with graph convolutions, thus leading to our PRR branch.

Graph Embedding Zero-Shot Learning

MovieChats: Chat like Humans in a Closed Domain

no code implementations EMNLP 2020 Hui Su, Xiaoyu Shen, Zhou Xiao, Zheng Zhang, Ernie Chang, Cheng Zhang, Cheng Niu, Jie zhou

In this work, we take a close look at the movie domain and present a large-scale high-quality corpus with fine-grained annotations in hope of pushing the limit of movie-domain chatbots.

Chatbot

Why Propagate Alone? Parallel Use of Labels and Features on Graphs

no code implementations14 Oct 2021 Yangkun Wang, Jiarui Jin, Weinan Zhang, Yongyi Yang, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf

In this regard, it has recently been proposed to use a randomly-selected portion of the training labels as GNN inputs, concatenated with the original node features for making predictions on the remaining labels.

Node Property Prediction

A Dual-Channel Framework for Sarcasm Recognition by Detecting Sentiment Conflict

no code implementations8 Sep 2021 Yiyi Liu, Yequan Wang, Aixin Sun, Zheng Zhang, Jiafeng Guo, Xuying Meng

In this paper, we show up the essence of sarcastic text is that the literal sentiment (expressed by the surface form of the text) is opposite to the deep sentiment (expressed by the actual meaning of the text).

Sentiment Analysis

Kinship Verification Based on Cross-Generation Feature Interaction Learning

no code implementations7 Sep 2021 Guan-Nan Dong, Chi-Man Pun, Zheng Zhang

Specifically, we take parents and children as a whole to extract the expressive local and non-local features.

Deep Collaborative Multi-Modal Learning for Unsupervised Kinship Estimation

no code implementations7 Sep 2021 Guan-Nan Dong, Chi-Man Pun, Zheng Zhang

To this end, we propose a novel deep collaborative multi-modal learning (DCML) to integrate the underlying information presented in facial properties in an adaptive manner to strengthen the facial details for effective unsupervised kinship verification.

Face Recognition

EVA: An Open-Domain Chinese Dialogue System with Large-Scale Generative Pre-Training

1 code implementation3 Aug 2021 Hao Zhou, Pei Ke, Zheng Zhang, Yuxian Gu, Yinhe Zheng, Chujie Zheng, Yida Wang, Chen Henry Wu, Hao Sun, Xiaocong Yang, Bosi Wen, Xiaoyan Zhu, Minlie Huang, Jie Tang

Although pre-trained language models have remarkably enhanced the generation ability of dialogue systems, open-domain Chinese dialogue systems are still limited by the dialogue data and the model size compared with English ones.

TransAttUnet: Multi-level Attention-guided U-Net with Transformer for Medical Image Segmentation

no code implementations12 Jul 2021 Bingzhi Chen, Yishu Liu, Zheng Zhang, Guangming Lu, David Zhang

With the development of deep encoder-decoder architectures and large-scale annotated medical datasets, great progress has been achieved in the development of automatic medical image segmentation.

Medical Image Segmentation

Learning Hierarchical Graph Neural Networks for Image Clustering

2 code implementations ICCV 2021 Yifan Xing, Tong He, Tianjun Xiao, Yongxin Wang, Yuanjun Xiong, Wei Xia, David Wipf, Zheng Zhang, Stefano Soatto

Our hierarchical GNN uses a novel approach to merge connected components predicted at each level of the hierarchy to form a new graph at the next level.

Face Clustering

Context-Aware Attention-Based Data Augmentation for POI Recommendation

no code implementations30 Jun 2021 Yang Li, Yadan Luo, Zheng Zhang, Shazia W. Sadiq, Peng Cui

It aims at suggesting the next POI to a user in spatial and temporal context, which is a practical yet challenging task in various applications.

Data Augmentation

Video Swin Transformer

5 code implementations24 Jun 2021 Ze Liu, Jia Ning, Yue Cao, Yixuan Wei, Zheng Zhang, Stephen Lin, Han Hu

The vision community is witnessing a modeling shift from CNNs to Transformers, where pure Transformer architectures have attained top accuracy on the major video recognition benchmarks.

 Ranked #1 on Action Recognition on Something-Something V2 (using extra training data)

Action Classification Action Recognition +3

End-to-End Semi-Supervised Object Detection with Soft Teacher

2 code implementations ICCV 2021 Mengde Xu, Zheng Zhang, Han Hu, JianFeng Wang, Lijuan Wang, Fangyun Wei, Xiang Bai, Zicheng Liu

This paper presents an end-to-end semi-supervised object detection approach, in contrast to previous more complex multi-stage methods.

 Ranked #1 on Instance Segmentation on COCO minival (using extra training data)

Instance Segmentation Object Detection +2

DS-TransUNet:Dual Swin Transformer U-Net for Medical Image Segmentation

no code implementations12 Jun 2021 Ailiang Lin, Bingzhi Chen, Jiayu Xu, Zheng Zhang, Guangming Lu

To alleviate these problems, we propose a novel deep medical image segmentation framework called Dual Swin Transformer U-Net (DS-TransUNet), which might be the first attempt to concurrently incorporate the advantages of hierarchical Swin Transformer into both encoder and decoder of the standard U-shaped architecture to enhance the semantic segmentation quality of varying medical images.

Medical Image Segmentation

A Unified Generative Framework for Various NER Subtasks

1 code implementation ACL 2021 Hang Yan, Tao Gui, Junqi Dai, Qipeng Guo, Zheng Zhang, Xipeng Qiu

To that end, we propose to formulate the NER subtasks as an entity span sequence generation task, which can be solved by a unified sequence-to-sequence (Seq2Seq) framework.

NER Nested Named Entity Recognition

Prototype-supervised Adversarial Network for Targeted Attack of Deep Hashing

1 code implementation CVPR 2021 Xunguang Wang, Zheng Zhang, Baoyuan Wu, Fumin Shen, Guangming Lu

However, deep hashing networks are vulnerable to adversarial examples, which is a practical secure problem but seldom studied in hashing-based retrieval field.

Image Retrieval Representation Learning

3U-EdgeAI: Ultra-Low Memory Training, Ultra-Low BitwidthQuantization, and Ultra-Low Latency Acceleration

no code implementations11 May 2021 Yao Chen, Cole Hawkins, Kaiqi Zhang, Zheng Zhang, Cong Hao

This paper emphasizes the importance and efficacy of training, quantization and accelerator design, and calls for more research breakthroughs in the area for AI on the edge.

Model Compression Quantization

Group-Free 3D Object Detection via Transformers

1 code implementation ICCV 2021 Ze Liu, Zheng Zhang, Yue Cao, Han Hu, Xin Tong

Instead of grouping local points to each object candidate, our method computes the feature of an object from all the points in the point cloud with the help of an attention mechanism in the Transformers \cite{vaswani2017attention}, where the contribution of each point is automatically learned in the network training.

3D Object Detection

High-Dimensional Uncertainty Quantification via Tensor Regression with Rank Determination and Adaptive Sampling

no code implementations31 Mar 2021 Zichang He, Zheng Zhang

Recently, low-rank tensor methods have been developed to mitigate this issue, but two fundamental challenges remain open: how to automatically determine the tensor rank and how to adaptively pick the informative simulation samples.

Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

29 code implementations ICCV 2021 Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, Baining Guo

This paper presents a new vision Transformer, called Swin Transformer, that capably serves as a general-purpose backbone for computer vision.

Ranked #3 on Semantic Segmentation on FoodSeg103 (using extra training data)

Image Classification Instance Segmentation +2

Bag of Tricks for Node Classification with Graph Neural Networks

1 code implementation24 Mar 2021 Yangkun Wang, Jiarui Jin, Weinan Zhang, Yong Yu, Zheng Zhang, David Wipf

Over the past few years, graph neural networks (GNN) and label propagation-based methods have made significant progress in addressing node classification tasks on graphs.

Classification General Classification +1

Graph Neural Networks Inspired by Classical Iterative Algorithms

1 code implementation10 Mar 2021 Yongyi Yang, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf

Despite the recent success of graph neural networks (GNN), common architectures often exhibit significant limitations, including sensitivity to oversmoothing, long-range dependencies, and spurious edges, e. g., as can occur as a result of graph heterophily or adversarial attacks.

Node Classification

A Unified Framework for Specification Tests of Continuous Treatment Effect Models

no code implementations16 Feb 2021 Wei Huang, Oliver Linton, Zheng Zhang

We propose a general framework for the specification testing of continuous treatment effect models.

Bayesian Inference with Certifiable Adversarial Robustness

no code implementations10 Feb 2021 Matthew Wicker, Luca Laurenti, Andrea Patane, Zhoutong Chen, Zheng Zhang, Marta Kwiatkowska

We consider adversarial training of deep neural networks through the lens of Bayesian learning, and present a principled framework for adversarial training of Bayesian Neural Networks (BNNs) with certifiable guarantees.

Bayesian Inference

Towards Robust Neural Networks via Close-loop Control

1 code implementation ICLR 2021 Zhuotong Chen, Qianxiao Li, Zheng Zhang

We connect the robustness of neural networks with optimal control using the geometrical information of underlying data to design the control objective.

Semantics Disentangling for Generalized Zero-Shot Learning

1 code implementation ICCV 2021 Zhi Chen, Yadan Luo, Ruihong Qiu, Sen Wang, Zi Huang, Jingjing Li, Zheng Zhang

Generalized zero-shot learning (GZSL) aims to classify samples under the assumption that some classes are not observable during training.

Generalized Zero-Shot Learning

Entropy-Based Uncertainty Calibration for Generalized Zero-Shot Learning

no code implementations9 Jan 2021 Zhi Chen, Zi Huang, Jingjing Li, Zheng Zhang

To address these issues, in this paper, we propose a novel framework that leverages dual variational autoencoders with a triplet loss to learn discriminative latent features and applies the entropy-based calibration to minimize the uncertainty in the overlapped area between the seen and unseen classes.

Generalized Zero-Shot Learning

Composite Adversarial Training for Multiple Adversarial Perturbations and Beyond

no code implementations1 Jan 2021 Xinyang Zhang, Zheng Zhang, Ting Wang

One intriguing property of deep neural networks (DNNs) is their vulnerability to adversarial perturbations.

Explore with Dynamic Map: Graph Structured Reinforcement Learning

no code implementations1 Jan 2021 Jiarui Jin, Sijin Zhou, Weinan Zhang, Rasool Fakoor, David Wipf, Tong He, Yong Yu, Zheng Zhang, Alex Smola

In reinforcement learning, a map with states and transitions built based on historical trajectories is often helpful in exploration and exploitation.

Active Sampling for Accelerated MRI with Low-Rank Tensors

no code implementations23 Dec 2020 Zichang He, Bo Zhao, Zheng Zhang

In this paper, we introduce an active low-rank tensor model for fast MR imaging.

Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings

1 code implementation14 Dec 2020 Qipeng Guo, Zhijing Jin, Ziyu Wang, Xipeng Qiu, Weinan Zhang, Jun Zhu, Zheng Zhang, David Wipf

Cycle-consistent training is widely used for jointly learning a forward and inverse mapping between two domains of interest without the cumbersome requirement of collecting matched pairs within each domain.

Knowledge Graphs Text Generation

Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning

5 code implementations CVPR 2021 Zhenda Xie, Yutong Lin, Zheng Zhang, Yue Cao, Stephen Lin, Han Hu

We argue that the power of contrastive learning has yet to be fully unleashed, as current methods are trained only on instance-level pretext tasks, leading to representations that may be sub-optimal for downstream tasks requiring dense pixel predictions.

Contrastive Learning Object Detection +2

DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs

1 code implementation11 Oct 2020 Da Zheng, Chao Ma, Minjie Wang, Jinjing Zhou, Qidong Su, Xiang Song, Quan Gan, Zheng Zhang, George Karypis

To minimize the overheads associated with distributed computations, DistDGL uses a high-quality and light-weight min-cut graph partitioning algorithm along with multiple balancing constraints.

Fraud Detection graph partitioning

CoLAKE: Contextualized Language and Knowledge Embedding

1 code implementation COLING 2020 Tianxiang Sun, Yunfan Shao, Xipeng Qiu, Qipeng Guo, Yaru Hu, Xuanjing Huang, Zheng Zhang

With the emerging branch of incorporating factual knowledge into pre-trained language models such as BERT, most existing models consider shallow, static, and separately pre-trained entity embeddings, which limits the performance gains of these models.

Entity Embeddings Knowledge Graph Completion

Efficient Estimation of General Treatment Effects using Neural Networks with A Diverging Number of Confounders

no code implementations15 Sep 2020 Xiaohong Chen, Ying Liu, Shujie Ma, Zheng Zhang

This paper proposes a new unified approach for efficient estimation of treatment effects using feedforward artificial neural networks when the number of covariates is allowed to increase with the sample size.

Dual-constrained Deep Semi-Supervised Coupled Factorization Network with Enriched Prior

no code implementations8 Sep 2020 Yan Zhang, Zhao Zhang, Yang Wang, Zheng Zhang, Li Zhang, Shuicheng Yan, Meng Wang

Nonnegative matrix factorization is usually powerful for learning the "shallow" parts-based representation, but it clearly fails to discover deep hierarchical information within both the basis and representation spaces.

Graph Learning Representation Learning

FeatGraph: A Flexible and Efficient Backend for Graph Neural Network Systems

no code implementations26 Aug 2020 Yuwei Hu, Zihao Ye, Minjie Wang, Jiali Yu, Da Zheng, Mu Li, Zheng Zhang, Zhiru Zhang, Yida Wang

FeatGraph provides a flexible programming interface to express diverse GNN models by composing coarse-grained sparse templates with fine-grained user-defined functions (UDFs) on each vertex/edge.

Trojaning Language Models for Fun and Profit

1 code implementation1 Aug 2020 Xinyang Zhang, Zheng Zhang, Shouling Ji, Ting Wang

Recent years have witnessed the emergence of a new paradigm of building natural language processing (NLP) systems: general-purpose, pre-trained language models (LMs) are composed with simple downstream models and fine-tuned for a variety of NLP tasks.

Question Answering Toxic Comment Classification

Adversarial Bipartite Graph Learning for Video Domain Adaptation

1 code implementation31 Jul 2020 Yadan Luo, Zi Huang, Zijian Wang, Zheng Zhang, Mahsa Baktashmotlagh

To further enhance the model capacity and testify the robustness of the proposed architecture on difficult transfer tasks, we extend our model to work in a semi-supervised setting using an additional video-level bipartite graph.

Domain Adaptation Graph Learning +1

RepPoints V2: Verification Meets Regression for Object Detection

1 code implementation NeurIPS 2020 Yihong Chen, Zheng Zhang, Yue Cao, Li-Wei Wang, Stephen Lin, Han Hu

Though RepPoints provides high performance, we find that its heavy reliance on regression for object localization leaves room for improvement.

Instance Segmentation Object Detection +2

A Closer Look at Local Aggregation Operators in Point Cloud Analysis

1 code implementation ECCV 2020 Ze Liu, Han Hu, Yue Cao, Zheng Zhang, Xin Tong

Our investigation reveals that despite the different designs of these operators, all of these operators make surprisingly similar contributions to the network performance under the same network input and feature numbers and result in the state-of-the-art accuracy on standard benchmarks.

3D Semantic Segmentation

An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph

1 code implementation1 Jul 2020 Jiarui Jin, Jiarui Qin, Yuchen Fang, Kounianhua Du, Wei-Nan Zhang, Yong Yu, Zheng Zhang, Alexander J. Smola

To the best of our knowledge, this is the first work providing an efficient neighborhood-based interaction model in the HIN-based recommendations.

Recommendation Systems

Disentangled Non-Local Neural Networks

4 code implementations ECCV 2020 Minghao Yin, Zhuliang Yao, Yue Cao, Xiu Li, Zheng Zhang, Stephen Lin, Han Hu

This paper first studies the non-local block in depth, where we find that its attention computation can be split into two terms, a whitened pairwise term accounting for the relationship between two pixels and a unary term representing the saliency of every pixel.

Action Recognition Object Detection +1

Dual-level Semantic Transfer Deep Hashing for Efficient Social Image Retrieval

1 code implementation10 Jun 2020 Lei Zhu, Hui Cui, Zhiyong Cheng, Jingjing Li, Zheng Zhang

Specifically, we design a complementary dual-level semantic transfer mechanism to efficiently discover the potential semantics of tags and seamlessly transfer them into binary hash codes.

Image Retrieval Representation Learning

CycleGT: Unsupervised Graph-to-Text and Text-to-Graph Generation via Cycle Training

2 code implementations8 Jun 2020 Qipeng Guo, Zhijing Jin, Xipeng Qiu, Wei-Nan Zhang, David Wipf, Zheng Zhang

Due to the difficulty and high cost of data collection, the supervised data available in the two fields are usually on the magnitude of tens of thousands, for example, 18K in the WebNLG~2017 dataset after preprocessing, which is far fewer than the millions of data for other tasks such as machine translation.

Graph Generation Knowledge Graphs +2

Repurpose Open Data to Discover Therapeutics for COVID-19 using Deep Learning

no code implementations21 May 2020 Xiangxiang Zeng, Xiang Song, Tengfei Ma, Xiaoqin Pan, Yadi Zhou, Yuan Hou, Zheng Zhang, George Karypis, Feixiong Cheng

While this study, by no means recommends specific drugs, it demonstrates a powerful deep learning methodology to prioritize existing drugs for further investigation, which holds the potential of accelerating therapeutic development for COVID-19.

Learning Goal-oriented Dialogue Policy with Opposite Agent Awareness

no code implementations Asian Chapter of the Association for Computational Linguistics 2020 Zheng Zhang, Lizi Liao, Xiaoyan Zhu, Tat-Seng Chua, Zitao Liu, Yan Huang, Minlie Huang

Most existing approaches for goal-oriented dialogue policy learning used reinforcement learning, which focuses on the target agent policy and simply treat the opposite agent policy as part of the environment.

Decision Making

DGL-KE: Training Knowledge Graph Embeddings at Scale

1 code implementation18 Apr 2020 Da Zheng, Xiang Song, Chao Ma, Zeyuan Tan, Zihao Ye, Jin Dong, Hao Xiong, Zheng Zhang, George Karypis

Experiments on knowledge graphs consisting of over 86M nodes and 338M edges show that DGL-KE can compute embeddings in 100 minutes on an EC2 instance with 8 GPUs and 30 minutes on an EC2 cluster with 4 machines with 48 cores/machine.

Distributed, Parallel, and Cluster Computing

Spatially Adaptive Inference with Stochastic Feature Sampling and Interpolation

1 code implementation ECCV 2020 Zhenda Xie, Zheng Zhang, Xizhou Zhu, Gao Huang, Stephen Lin

In the feature maps of CNNs, there commonly exists considerable spatial redundancy that leads to much repetitive processing.

Recent Advances and Challenges in Task-oriented Dialog System

no code implementations17 Mar 2020 Zheng Zhang, Ryuichi Takanobu, Qi Zhu, Minlie Huang, Xiaoyan Zhu

Due to the significance and value in human-computer interaction and natural language processing, task-oriented dialog systems are attracting more and more attention in both academic and industrial communities.

CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset

2 code implementations TACL 2020 Qi Zhu, Kaili Huang, Zheng Zhang, Xiaoyan Zhu, Minlie Huang

To advance multi-domain (cross-domain) dialogue modeling as well as alleviate the shortage of Chinese task-oriented datasets, we propose CrossWOZ, the first large-scale Chinese Cross-Domain Wizard-of-Oz task-oriented dataset.

Dialogue State Tracking Task-Oriented Dialogue Systems

Transformer on a Diet

1 code implementation14 Feb 2020 Chenguang Wang, Zihao Ye, Aston Zhang, Zheng Zhang, Alexander J. Smola

Transformer has been widely used thanks to its ability to capture sequence information in an efficient way.

Language Modelling

ConvLab-2: An Open-Source Toolkit for Building, Evaluating, and Diagnosing Dialogue Systems

1 code implementation ACL 2020 Qi Zhu, Zheng Zhang, Yan Fang, Xiang Li, Ryuichi Takanobu, Jinchao Li, Baolin Peng, Jianfeng Gao, Xiaoyan Zhu, Minlie Huang

We present ConvLab-2, an open-source toolkit that enables researchers to build task-oriented dialogue systems with state-of-the-art models, perform an end-to-end evaluation, and diagnose the weakness of systems.

Task-Oriented Dialogue Systems

Dense Residual Network: Enhancing Global Dense Feature Flow for Character Recognition

no code implementations23 Jan 2020 Zhao Zhang, Zemin Tang, Yang Wang, Zheng Zhang, Choujun Zhan, ZhengJun Zha, Meng Wang

To construct FDRN, we propose a new fast residual dense block (f-RDB) to retain the ability of local feature fusion and local residual learning of original RDB, which can reduce the computing efforts at the same time.

Dense RepPoints: Representing Visual Objects with Dense Point Sets

2 code implementations ECCV 2020 Ze Yang, Yinghao Xu, Han Xue, Zheng Zhang, Raquel Urtasun, Li-Wei Wang, Stephen Lin, Han Hu

We present a new object representation, called Dense RepPoints, that utilizes a large set of points to describe an object at multiple levels, including both box level and pixel level.

Object Detection

Fully-Convolutional Intensive Feature Flow Neural Network for Text Recognition

no code implementations13 Dec 2019 Zhao Zhang, Zemin Tang, Zheng Zhang, Yang Wang, Jie Qin, Meng Wang

But existing CNNs based frameworks still have several drawbacks: 1) the traditaional pooling operation may lose important feature information and is unlearnable; 2) the tradi-tional convolution operation optimizes slowly and the hierar-chical features from different layers are not fully utilized.

Deep Self-representative Concept Factorization Network for Representation Learning

no code implementations13 Dec 2019 Yan Zhang, Zhao Zhang, Zheng Zhang, Mingbo Zhao, Li Zhang, Zheng-Jun Zha, Meng Wang

In this paper, we investigate the unsupervised deep representation learning issue and technically propose a novel framework called Deep Self-representative Concept Factorization Network (DSCF-Net), for clustering deep features.

Representation Learning

Quantum-Inspired Hamiltonian Monte Carlo for Bayesian Sampling

1 code implementation4 Dec 2019 Ziming Liu, Zheng Zhang

Hamiltonian Monte Carlo (HMC) is an efficient Bayesian sampling method that can make distant proposals in the parameter space by simulating a Hamiltonian dynamical system.

Image Denoising Network Pruning

Multi-Scale Self-Attention for Text Classification

no code implementations2 Dec 2019 Qipeng Guo, Xipeng Qiu, PengFei Liu, xiangyang xue, Zheng Zhang

In this paper, we introduce the prior knowledge, multi-scale structure, into self-attention modules.

Classification General Classification +1

Discriminative Local Sparse Representation by Robust Adaptive Dictionary Pair Learning

no code implementations20 Nov 2019 Yulin Sun, Zhao Zhang, Weiming Jiang, Zheng Zhang, Li Zhang, Shuicheng Yan, Meng Wang

In this paper, we propose a structured Robust Adaptive Dic-tionary Pair Learning (RA-DPL) framework for the discrim-inative sparse representation learning.

Representation Learning

Transductive Zero-Shot Hashing for Multilabel Image Retrieval

1 code implementation17 Nov 2019 Qin Zou, Zheng Zhang, Ling Cao, Long Chen, Song Wang

Given semantic annotations such as class labels and pairwise similarities of the training data, hashing methods can learn and generate effective and compact binary codes.

Multi-Label Image Retrieval Quantization

Learning from the Past: Continual Meta-Learning via Bayesian Graph Modeling

no code implementations12 Nov 2019 Yadan Luo, Zi Huang, Zheng Zhang, Ziwei Wang, Mahsa Baktashmotlagh, Yang Yang

Meta-learning for few-shot learning allows a machine to leverage previously acquired knowledge as a prior, thus improving the performance on novel tasks with only small amounts of data.

Continual Learning Few-Shot Learning

Deep Collaborative Discrete Hashing with Semantic-Invariant Structure

no code implementations5 Nov 2019 Zijian Wang, Zheng Zhang, Yadan Luo, Zi Huang

Existing deep hashing approaches fail to fully explore semantic correlations and neglect the effect of linguistic context on visual attention learning, leading to inferior performance.

Active Subspace of Neural Networks: Structural Analysis and Universal Attacks

1 code implementation29 Oct 2019 Chunfeng Cui, Kaiqi Zhang, Talgat Daulbaev, Julia Gusak, Ivan Oseledets, Zheng Zhang

Secondly, we propose analyzing the vulnerability of a neural network using active subspace and finding an additive universal adversarial attack vector that can misclassify a dataset with a high probability.

Adversarial Attack

A Deep Learning Framework for Pricing Financial Instruments

no code implementations7 Sep 2019 Qiong Wu, Zheng Zhang, Andrea Pizzoferrato, Mihai Cucuringu, Zhenming Liu

Meanwhile, the results from different trading simulators demonstrate that we can effectively monetize the signals.

Learning Structured Twin-Incoherent Twin-Projective Latent Dictionary Pairs for Classification

no code implementations21 Aug 2019 Zhao Zhang, Yulin Sun, Zheng Zhang, Yang Wang, Guangcan Liu, Meng Wang

In this setting, our TP-DPL integrates the twin-incoherence based latent flexible DPL and the joint embedding of codes as well as salient features by twin-projection into a unified model in an adaptive neighborhood-preserving manner.

Classification General Classification

Adaptive Structure-constrained Robust Latent Low-Rank Coding for Image Recovery

no code implementations21 Aug 2019 Zhao Zhang, Lei Wang, Sheng Li, Yang Wang, Zheng Zhang, Zheng-Jun Zha, Meng Wang

Specifically, AS-LRC performs the latent decomposition of given data into a low-rank reconstruction by a block-diagonal codes matrix, a group sparse locality-adaptive salient feature part and a sparse error part.

Representation Learning

Curiosity-driven Reinforcement Learning for Diverse Visual Paragraph Generation

no code implementations1 Aug 2019 Yadan Luo, Zi Huang, Zheng Zhang, Ziwei Wang, Jingjing Li, Yang Yang

Visual paragraph generation aims to automatically describe a given image from different perspectives and organize sentences in a coherent way.

Decision Making Imitation Learning

Tucker Tensor Decomposition on FPGA

no code implementations28 Jun 2019 Kaiqi Zhang, Xiyuan Zhang, Zheng Zhang

This paper presents an hardware accelerator for a classical tensor computation framework, Tucker decomposition.

Signal Processing Hardware Architecture

Joint Subspace Recovery and Enhanced Locality Driven Robust Flexible Discriminative Dictionary Learning

no code implementations11 Jun 2019 Zhao Zhang, Jiahuan Ren, Weiming Jiang, Zheng Zhang, Richang Hong, Shuicheng Yan, Meng Wang

We propose a joint subspace recovery and enhanced locality based robust flexible label consistent dictionary learning method called Robust Flexible Discriminative Dictionary Learning (RFDDL).

Dictionary Learning

Scalable Block-Diagonal Locality-Constrained Projective Dictionary Learning

no code implementations25 May 2019 Zhao Zhang, Weiming Jiang, Zheng Zhang, Sheng Li, Guangcan Liu, Jie Qin

More importantly, LC-PDL avoids using the complementary data matrix to learn the sub-dictionary over each class.

Dictionary Learning

Bayesian Tensorized Neural Networks with Automatic Rank Selection

1 code implementation24 May 2019 Cole Hawkins, Zheng Zhang

Tensor decomposition is an effective approach to compress over-parameterized neural networks and to enable their deployment on resource-constrained hardware platforms.

Model Compression Tensor Decomposition

Gradient-based learning for F-measure and other performance metrics

no code implementations ICLR 2019 Yu Gai, Zheng Zhang, Kyunghyun Cho

Many important classification performance metrics, e. g. $F$-measure, are non-differentiable and non-decomposable, and are thus unfriendly to gradient descent algorithm.

General Classification

Spatial-Temporal Relation Networks for Multi-Object Tracking

no code implementations ICCV 2019 Jiarui Xu, Yue Cao, Zheng Zhang, Han Hu

Recent progress in multiple object tracking (MOT) has shown that a robust similarity score is key to the success of trackers.

Multi-Object Tracking Multiple Object Tracking

ConvLab: Multi-Domain End-to-End Dialog System Platform

1 code implementation ACL 2019 Sungjin Lee, Qi Zhu, Ryuichi Takanobu, Xiang Li, Yaoqin Zhang, Zheng Zhang, Jinchao Li, Baolin Peng, Xiujun Li, Minlie Huang, Jianfeng Gao

We present ConvLab, an open-source multi-domain end-to-end dialog system platform, that enables researchers to quickly set up experiments with reusable components and compare a large set of different approaches, ranging from conventional pipeline systems to end-to-end neural models, in common environments.

An Empirical Study of Spatial Attention Mechanisms in Deep Networks

1 code implementation ICCV 2019 Xizhou Zhu, Dazhi Cheng, Zheng Zhang, Stephen Lin, Jifeng Dai

Attention mechanisms have become a popular component in deep neural networks, yet there has been little examination of how different influencing factors and methods for computing attention from these factors affect performance.

SADIH: Semantic-Aware DIscrete Hashing

no code implementations3 Apr 2019 Zheng Zhang, Guo-Sen Xie, Yang Li, Sheng Li, Zi Huang

Due to its low storage cost and fast query speed, hashing has been recognized to accomplish similarity search in large-scale multimedia retrieval applications.

Star-Transformer

1 code implementation NAACL 2019 Qipeng Guo, Xipeng Qiu, PengFei Liu, Yunfan Shao, xiangyang xue, Zheng Zhang

Although Transformer has achieved great successes on many NLP tasks, its heavy structure with fully-connected attention connections leads to dependencies on large training data.

Named Entity Recognition Natural Language Inference +2

Bilinear Supervised Hashing Based on 2D Image Features

no code implementations5 Jan 2019 Yujuan Ding, Wai Kueng Wong, Zhihui Lai, Zheng Zhang

Hashing has been recognized as an efficient representation learning method to effectively handle big data due to its low computational complexity and memory cost.

Representation Learning

Prediction of multi-dimensional spatial variation data via Bayesian tensor completion

no code implementations3 Jan 2019 Jiali Luan, Zheng Zhang

This paper presents a multi-dimensional computational method to predict the spatial variation data inside and across multiple dies of a wafer.

Adaptive Locality Preserving Regression

no code implementations3 Jan 2019 Jie Wen, Zuofeng Zhong, Zheng Zhang, Lunke Fei, Zhihui Lai, Runze Chen

This paper proposes a novel discriminative regression method, called adaptive locality preserving regression (ALPR) for classification.

Feature Selection

Melodic Phrase Segmentation By Deep Neural Networks

no code implementations14 Nov 2018 Yixing Guan, Jinyu Zhao, Yiqin Qiu, Zheng Zhang, Gus Xia

Automated melodic phrase detection and segmentation is a classical task in content-based music information retrieval and also the key towards automated music structure analysis.

Information Retrieval Music Information Retrieval

Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion

no code implementations6 Sep 2018 Cole Hawkins, Zheng Zhang

Streaming tensor factorization is a powerful tool for processing high-volume and multi-way temporal data in Internet networks, recommender systems and image/video data analysis.

Bayesian Inference Recommendation Systems

Top-Down Tree Structured Text Generation

no code implementations14 Aug 2018 Qipeng Guo, Xipeng Qiu, xiangyang xue, Zheng Zhang

Text generation is a fundamental building block in natural language processing tasks.

Text Generation

Effective Occlusion Handling for Fast Correlation Filter-based Trackers

no code implementations13 Jul 2018 Zheng Zhang, T. T. Wong

Correlation filter-based trackers heavily suffer from the problem of multiple peaks in their response maps incurred by occlusions.

Occlusion Handling

Efficient Generation and Processing of Word Co-occurrence Networks Using corpus2graph

1 code implementation WS 2018 Zheng Zhang, Pierre Zweigenbaum, Ruiqing Yin

Corpus2graph is an open-source NLP-application-oriented tool that generates a word co-occurrence network from a large corpus.

Keyword Extraction

Memory-augmented Dialogue Management for Task-oriented Dialogue Systems

no code implementations1 May 2018 Zheng Zhang, Minlie Huang, Zhongzhou Zhao, Feng Ji, Haiqing Chen, Xiaoyan Zhu

Dialogue management (DM) decides the next action of a dialogue system according to the current dialogue state, and thus plays a central role in task-oriented dialogue systems.

Dialogue Management Task-Oriented Dialogue Systems

Improved Deep Hashing with Soft Pairwise Similarity for Multi-label Image Retrieval

1 code implementation8 Mar 2018 Zheng Zhang, Qin Zou, Yuewei Lin, Long Chen, Song Wang

In this paper, a new deep hashing method is proposed for multi-label image retrieval by re-defining the pairwise similarity into an instance similarity, where the instance similarity is quantified into a percentage based on the normalized semantic labels.

Multi-Label Image Retrieval

Relation Networks for Object Detection

5 code implementations CVPR 2018 Han Hu, Jiayuan Gu, Zheng Zhang, Jifeng Dai, Yichen Wei

Although it is well believed for years that modeling relations between objects would help object recognition, there has not been evidence that the idea is working in the deep learning era.

Object Detection Object Recognition

Loss Functions for Multiset Prediction

no code implementations ICLR 2018 Sean Welleck, Zixin Yao, Yu Gai, Jialin Mao, Zheng Zhang, Kyunghyun Cho

In this paper, we propose a novel multiset loss function by viewing this problem from the perspective of sequential decision making.

Decision Making

Discriminative Block-Diagonal Representation Learning for Image Recognition

no code implementations12 Jul 2017 Zheng Zhang, Yong Xu, Ling Shao, Jian Yang

In particular, the elaborate BDLRR is formulated as a joint optimization problem of shrinking the unfavorable representation from off-block-diagonal elements and strengthening the compact block-diagonal representation under the semi-supervised framework of low-rank representation.

Representation Learning

Tractable Clustering of Data on the Curve Manifold

1 code implementation13 Apr 2017 Stephen Tierney, Junbin Gao, Yi Guo, Zheng Zhang

However the data may actually be functional i. e.\ each data point is a function of some variable such as time and the function is discretely sampled.

Who Leads the Clothing Fashion: Style, Color, or Texture? A Computational Study

no code implementations26 Aug 2016 Qin Zou, Zheng Zhang, Qian Wang, Qingquan Li, Long Chen, Song Wang

Specifically, a classification-based model is proposed to quantify the influence of different visual stimuli, in which each visual stimulus's influence is quantified by its corresponding accuracy in fashion classification.

Classification General Classification

Learning Word Embeddings from Intrinsic and Extrinsic Views

no code implementations20 Aug 2016 Jifan Chen, Kan Chen, Xipeng Qiu, Qi Zhang, Xuanjing Huang, Zheng Zhang

To prove the effectiveness of our model, we evaluate it on four tasks, including word similarity, reverse dictionaries, Wiki link prediction, and document classification.

Document Classification General Classification +3

Local Multiple Directional Pattern of Palmprint Image

no code implementations21 Jul 2016 Lunke Fei, Jie Wen, Zheng Zhang, Ke Yan, Zuofeng Zhong

Conventional methods usually capture the only one of the most dominant direction of palmprint images.

Natural Scene Character Recognition Using Robust PCA and Sparse Representation

no code implementations15 Jun 2016 Zheng Zhang, Yong Xu, Cheng-Lin Liu

Natural scene character recognition is challenging due to the cluttered background, which is hard to separate from text.

A survey of sparse representation: algorithms and applications

no code implementations23 Feb 2016 Zheng Zhang, Yong Xu, Jian Yang, Xuelong. Li, David Zhang

The main purpose of this article is to provide a comprehensive study and an updated review on sparse representation and to supply a guidance for researchers.

Learning to Point and Count

no code implementations8 Dec 2015 Jie Shao, Dequan Wang, xiangyang xue, Zheng Zhang

This paper proposes the problem of point-and-count as a test case to break the what-and-where deadlock.

General Classification

MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems

2 code implementations3 Dec 2015 Tianqi Chen, Mu Li, Yutian Li, Min Lin, Naiyan Wang, Minjie Wang, Tianjun Xiao, Bing Xu, Chiyuan Zhang, Zheng Zhang

This paper describes both the API design and the system implementation of MXNet, and explains how embedding of both symbolic expression and tensor operation is handled in a unified fashion.

Dimensionality Reduction General Classification

Multiple Granularity Descriptors for Fine-Grained Categorization

no code implementations ICCV 2015 Dequan Wang, Zhiqiang Shen, Jie Shao, Wei zhang, xiangyang xue, Zheng Zhang

Fine-grained categorization, which aims to distinguish subordinate-level categories such as bird species or dog breeds, is an extremely challenging task.

First Step toward Model-Free, Anonymous Object Tracking with Recurrent Neural Networks

no code implementations19 Nov 2015 Quan Gan, Qipeng Guo, Zheng Zhang, Kyunghyun Cho

In this paper, we propose and study a novel visual object tracking approach based on convolutional networks and recurrent networks.

Visual Object Tracking Visual Tracking

Symmetry-Based Text Line Detection in Natural Scenes

no code implementations CVPR 2015 Zheng Zhang, Wei Shen, Cong Yao, Xiang Bai

Recently, a variety of real-world applications have triggered huge demand for techniques that can extract textual information from natural scenes.

Line Detection Scene Text +1

The Application of Two-level Attention Models in Deep Convolutional Neural Network for Fine-grained Image Classification

no code implementations CVPR 2015 Tianjun Xiao, Yichong Xu, Kuiyuan Yang, Jiaxing Zhang, Yuxin Peng, Zheng Zhang

Our pipeline integrates three types of attention: the bottom-up attention that propose candidate patches, the object-level top-down attention that selects relevant patches to a certain object, and the part-level top-down attention that localizes discriminative parts.

Classification Fine-Grained Image Classification +1

Scale-Invariant Convolutional Neural Networks

no code implementations24 Nov 2014 Yichong Xu, Tianjun Xiao, Jiaxing Zhang, Kuiyuan Yang, Zheng Zhang

Even though convolutional neural networks (CNN) has achieved near-human performance in various computer vision tasks, its ability to tolerate scale variations is limited.

Classification Data Augmentation +1

Attentional Neural Network: Feature Selection Using Cognitive Feedback

1 code implementation NeurIPS 2014 Qian Wang, Jiaxing Zhang, Sen Song, Zheng Zhang

Attentional Neural Network is a new framework that integrates top-down cognitive bias and bottom-up feature extraction in one coherent architecture.

Feature Selection General Classification

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