John Shawe‐Taylor

61.7k citations

312 papers · 36.7k indexed · 10 hit papers · h-index 52

Impact in

Artificial Intelligence top 0.01%
- Anomaly Detection Techniques and Applications
- Neural Networks and Applications
- Text and Document Classification Technologies
- Machine Learning and Algorithms
Computer Vision and Pattern Recognition top 0.05%
- Face and Expression Recognition
- Advanced Image and Video Retrieval Techniques
- Image Retrieval and Classification Techniques

Papers in

Artificial Intelligence 182
- Machine Learning and Algorithms 58
- Neural Networks and Applications 52
- Machine Learning and Data Classification 22
- Text and Document Classification Technologies 21
Computer Vision and Pattern Recognition 80
- Face and Expression Recognition 53
- Image Retrieval and Classification Techniques 20

Co-authors: Nello Cristianini John Platt Robert C. Williamson Bernhard Schölkopf Alex Smola David R. Hardoon Sándor Szedmák Theodore C. White
Journals: Journal of Machine Learning Research (9 papers)Machine Learning (7 papers)Discrete Applied Mathematics (7 papers)IEEE Transactions on Information Theory (7 papers)Neurocomputing (5 papers)
Partner nations: United Kingdom United States Australia

In The Last Decade

John Shawe‐Taylor

303 papers receiving 34.3k citations

Hit Papers

10 papers align trajectories log scale

Artificial Intelligence Alone Will Not Democratise Education: On Educational Inequality, Techno-Solutionism and Inclusive Tools 2024 · 73 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2024 Sustainability
2011 Proceedings of the 24th International Conference on Neural Information Processing Systems
2004 Cambridge University Press eBooks
2004 Neural Computation
2001 Neural Computation
2000 ePrints Soton (University of Southampton)
2000 Cambridge University Press eBooks
1999 UCL Discovery (University College London)
1999 Explore Bristol Research
1990 Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. PCR protocols: a guide to methods and applications

Peers

Countries citing papers authored by John Shawe‐Taylor

Since Specialization

Citations

This map shows the geographic impact of John Shawe‐Taylor's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by John Shawe‐Taylor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Shawe‐Taylor more than expected).

Fields of papers citing papers by John Shawe‐Taylor

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John Shawe‐Taylor. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by John Shawe‐Taylor. The network helps show where John Shawe‐Taylor may publish in the future.

Co-authorship network

The 25 scholars most cited alongside John Shawe‐Taylor, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with John Shawe‐Taylor Line = papers co-authored together John Shawe‐Taylor links everyone, so they are left out of the graph.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work
1	Artificial Intelligence Alone Will Not Democratise Education: On Educational Inequality, Techno-Solutionism and Inclusive Tools Sustainability ·Kenta Nakatani, María Pérez‐Ortiz, Catherine Holloway, Mutlu Cukurova, John Shawe‐Taylor Hit paper breakdown →	2024	73
2	Randomized learning and generalization of fair and private classifiers: From PAC-Bayes to stability and differential privacy Neurocomputing ·Luca Oneto, Michele Donini, Massimiliano Pontil, John Shawe‐Taylor	2020	8
3	Tracking global changes induced in the CD4 T-cell receptor repertoire by immunization with a complex antigen using short stretches of CDR3 protein sequence Bioinformatics ·Niclas Thomas, Katharine Best, Zhale Rajavi, Shlomit Reich-Zeliger, Hilah Gal, Eric Shifrut, Asaf Madi, Nir Friedman, John Shawe‐Taylor, Benny Chain	2014	70
4	GLM and SVM analyses of neural response to tonal and atonal stimuli: new techniques and a comparison Connection Science ·Simon Durrant, David R. Hardoon, (unknown), John Shawe‐Taylor, Eduardo Reck Miranda, Henning Scheich	2009	10
5	GLM and SVM analyses of neural response to tonal and atonal stimuli: new techniques and a comparison (vol 21, pg 161, 2009) UCL Discovery (University College London) ·Samantha Durrant, (unknown), (unknown), John Shawe‐Taylor, Ahad Yousef, Henning Scheich	2009	1
6	Learning Hierarchical Multi-Category Text Classification Models ePrints Soton (University of Southampton) ·Juho Rousu, Craig Saunders, Sándor Szedmák, John Shawe‐Taylor	2005	1
7	KCCA Feature Selection for fMRI Analysis ePrints Soton (University of Southampton) ·David R. Hardoon, John Shawe‐Taylor, Ola Friman	2004	2
8	PAC Bayes and Margins ePrints Soton (University of Southampton) ·John Langford, John Shawe‐Taylor	2003	35
9	Optimizing Kernel Alignment over Combinations of Kernel ePrints Soton (University of Southampton) ·Jaz Kandola, John Shawe‐Taylor, Nello Cristianini	2002	50
10	Inferring a Semantic Representation of Text via Cross-Language Correlation Analysis ePrints Soton (University of Southampton) ·V V Zuyenko, Nello Cristianini, John Shawe‐Taylor	2002	150
11	Review of "Anthony, Martin; Bartlett, Peter L., Neural Network Learning: Theoretical Foundations, Cambridge: Cambridge University Press" ePrints Soton (University of Southampton) ·John Shawe‐Taylor	2001	2
12	Composite Kernels for Hypertext Categorisation ePrints Soton (University of Southampton) ·Thorsten Joachims, Nello Cristianini, John Shawe‐Taylor	2001	96
13	Direct Bayes Point Machines ePrints Soton (University of Southampton) ·冷冬, John Shawe‐Taylor, Manfred Glesner	2000	2
14	A multiplicative updating algorithm for training support vector machine UCL Discovery (University College London) ·Nello Cristianini, Colin Campbell, John Shawe‐Taylor	1999	6
15	Large Margin Decision Trees for Induction and Transduction ePrints Soton (University of Southampton) ·Donghui Wu, Kristin P. Bennett, Nello Cristianini, John Shawe‐Taylor	1999	8
16	Multiplicative Updatings for Support Vector Learning ePrints Soton (University of Southampton) ·Nello Cristianini, Colin Campbell, John Shawe‐Taylor	1998	3
17	Robust Bounds on Generalization from the Margin Distribution ePrints Soton (University of Southampton) ·John Shawe‐Taylor, (unknown), (unknown)	1998	11
18	Frameworks For Fraud Detection In Mobile Telecommunications Networks ePrints Soton (University of Southampton) ·Peter Burge, John Shawe‐Taylor	1996	7
19	Fast Expected Two Dimensional Pattern Matching ePrints Soton (University of Southampton) ·Bharat R. Devhare, John Shawe‐Taylor	1993	2
20	BUILDING SYMMETRIES INTO FEEDFORWARD NETWORKS ePrints Soton (University of Southampton) ·John Shawe‐Taylor	1989	8

About John Shawe‐Taylor

John Shawe‐Taylor is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Discrete Mathematics and Combinatorics and Computational Mathematics, having authored 312 papers that have together received 36.7k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (58 papers), Face and Expression Recognition (53 papers), Neural Networks and Applications (52 papers), Sparse and Compressive Sensing Techniques (23 papers), Machine Learning and Data Classification (22 papers), Text and Document Classification Technologies (21 papers), Image Retrieval and Classification Techniques (20 papers) and Blind Source Separation Techniques (19 papers). The work is most often cited by research in Artificial Intelligence (16.3k citations), Computer Vision and Pattern Recognition (10.3k citations), Signal Processing (3.6k citations), Media Technology (1.8k citations) and Computational Mathematics (120 citations). John Shawe‐Taylor has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Nello Cristianini, John Platt, Robert C. Williamson, Bernhard Schölkopf, Alex Smola, David R. Hardoon, Sándor Szedmák, Theodore C. White, D. Lee Taylor and TJ White. Their work appears in journals such as Journal of Machine Learning Research, Machine Learning, Discrete Applied Mathematics, IEEE Transactions on Information Theory and Neurocomputing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact