D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 62 Citations 19,268 222 World Ranking 1355 National Ranking 33

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

Ivor W. Tsang focuses on Artificial intelligence, Pattern recognition, Support vector machine, Kernel method and Machine learning. His study in Neural coding, Contextual image classification, Feature, Training set and Kernel falls within the category of Artificial intelligence. His Pattern recognition study frequently draws connections between related disciplines such as Transfer of learning.

Within one scientific family, Ivor W. Tsang focuses on topics pertaining to Algorithm under Support vector machine, and may sometimes address concerns connected to Efficiency. His Kernel method study combines topics in areas such as Time complexity and Mathematical optimization. His work focuses on many connections between Machine learning and other disciplines, such as Classifier, that overlap with his field of interest in TRECVID.

His most cited work include:

  • Domain Adaptation via Transfer Component Analysis (1893 citations)
  • Core Vector Machines: Fast SVM Training on Very Large Data Sets (792 citations)
  • Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels (414 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in Artificial intelligence, Machine learning, Pattern recognition, Support vector machine and Algorithm. His study involves Classifier, Deep learning, Kernel method, Feature extraction and Multiple kernel learning, a branch of Artificial intelligence. His Kernel method research integrates issues from Quadratic programming and Mathematical optimization.

Many of his research projects under Machine learning are closely connected to Generalization with Generalization, tying the diverse disciplines of science together. His Pattern recognition research incorporates themes from Contextual image classification and Cluster analysis. The study incorporates disciplines such as Margin and Image retrieval in addition to Support vector machine.

He most often published in these fields:

  • Artificial intelligence (59.82%)
  • Machine learning (30.06%)
  • Pattern recognition (29.75%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (59.82%)
  • Machine learning (30.06%)
  • Deep learning (6.44%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Artificial intelligence, Machine learning, Deep learning, Theoretical computer science and Generalization. The various areas that Ivor W. Tsang examines in his Artificial intelligence study include Computer vision and Pattern recognition. Pattern recognition is represented through his Discriminative model and Support vector machine research.

His research investigates the connection with Machine learning and areas like Rate of convergence which intersect with concerns in Privacy preserving, Mathematical optimization, Proximal Gradient Methods and Multiple kernel learning. He interconnects Early stopping, Training set, Speech recognition, Multi label learning and Focus in the investigation of issues within Deep learning. His Theoretical computer science study which covers Benchmark that intersects with Search engine indexing, Multimedia database and Spectral clustering.

Between 2019 and 2021, his most popular works were:

  • Survey on Multi-Output Learning (33 citations)
  • Curriculum Loss: Robust Learning and Generalization against Label Corruption (24 citations)
  • VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning (22 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Statistics

His scientific interests lie mostly in Artificial intelligence, Feature learning, Machine learning, Pattern recognition and Deep learning. As a part of the same scientific family, Ivor W. Tsang mostly works in the field of Artificial intelligence, focusing on Computer vision and, on occasion, Hallucinating. His Feature learning study integrates concerns from other disciplines, such as Graph classification, Android malware, Malware and Upload.

His work on Artificial neural network as part of general Machine learning research is frequently linked to Rank, thereby connecting diverse disciplines of science. His Mutual information study, which is part of a larger body of work in Pattern recognition, is frequently linked to Infomax, bridging the gap between disciplines. Ivor W. Tsang has researched Deep learning in several fields, including Training set and Robustness.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Domain Adaptation via Transfer Component Analysis

Sinno Jialin Pan;Ivor W Tsang;James T Kwok;Qiang Yang.
IEEE Transactions on Neural Networks (2011)

1935 Citations

Core Vector Machines: Fast SVM Training on Very Large Data Sets

Ivor W. Tsang;James T. Kwok;Pak-Ming Cheung.
Journal of Machine Learning Research (2005)

1218 Citations

Visual event recognition in videos by learning from web data

Lixin Duan;Dong Xu;Ivor Wai-Hung Tsang;Jiebo Luo.
computer vision and pattern recognition (2010)

559 Citations

The pre-image problem in kernel methods

J.T.-Y. Kwok;I.W.-H. Tsang.
IEEE Transactions on Neural Networks (2004)

554 Citations

Local features are not lonely – Laplacian sparse coding for image classification

Shenghua Gao;Ivor Wai-Hung Tsang;Liang-Tien Chia;Peilin Zhao.
computer vision and pattern recognition (2010)

552 Citations

Domain Transfer Multiple Kernel Learning

Lixin Duan;I. W. Tsang;Dong Xu.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2012)

474 Citations

Kernel sparse representation for image classification and face recognition

Shenghua Gao;Ivor Wai-Hung Tsang;Liang-Tien Chia.
european conference on computer vision (2010)

431 Citations

Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels

Bo Han;Quanming Yao;Xingrui Yu;Gang Niu.
neural information processing systems (2018)

414 Citations

Improved Nyström low-rank approximation and error analysis

Kai Zhang;Ivor W. Tsang;James T. Kwok.
international conference on machine learning (2008)

390 Citations

Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction

Feiping Nie;Dong Xu;Ivor Wai-Hung Tsang;Changshui Zhang.
IEEE Transactions on Image Processing (2010)

384 Citations

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Best Scientists Citing Ivor W. Tsang

Feiping Nie

Feiping Nie

Northwestern Polytechnical University

Publications: 94

Dacheng Tao

Dacheng Tao

University of Sydney

Publications: 78

Shitong Wang

Shitong Wang

Jiangnan University

Publications: 72

Xuelong Li

Xuelong Li

Northwestern Polytechnical University

Publications: 68

Yi Yang

Yi Yang

Zhejiang University

Publications: 54

Yew-Soon Ong

Yew-Soon Ong

Nanyang Technological University

Publications: 53

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 52

David Zhang

David Zhang

Chinese University of Hong Kong, Shenzhen

Publications: 47

Zhi-Hua Zhou

Zhi-Hua Zhou

Nanjing University

Publications: 45

Fu-Lai Chung

Fu-Lai Chung

Hong Kong Polytechnic University

Publications: 42

Shuicheng Yan

Shuicheng Yan

National University of Singapore

Publications: 41

Dong Xu

Dong Xu

University of Sydney

Publications: 40

Meng Wang

Meng Wang

Hefei University of Technology

Publications: 39

Qingming Huang

Qingming Huang

Chinese Academy of Sciences

Publications: 38

Heng Tao Shen

Heng Tao Shen

University of Electronic Science and Technology of China

Publications: 36

Qiang Yang

Qiang Yang

Hong Kong University of Science and Technology

Publications: 35

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