Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
A training algorithm for optimal margin classifiers
19927.6k citationsBernhard E. Boser, Isabelle Guyon et al.profile →
Gene Selection for Cancer Classification using Support Vector Machines
20026.9k citationsIsabelle Guyon, Vladimir Vapnik et al.profile →
SIGNATURE VERIFICATION USING A “SIAMESE” TIME DELAY NEURAL NETWORK
19931.4k citationsLéon Bottou, Isabelle Guyon et al.profile →
Feature extraction : foundations and applications
20061.1k citationsIsabelle Guyon, S.R. Gunn et al.Springer eBooksprofile →
Comparison of classifier methods: a case study in handwritten digit recognition
2002408 citationsLéon Bottou, Corinna Cortes et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by Isabelle Guyon
Since
Specialization
Citations
This map shows the geographic impact of Isabelle Guyon'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 Isabelle Guyon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Isabelle Guyon more than expected).
This network shows the impact of papers produced by Isabelle Guyon. 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 Isabelle Guyon. The network helps show where Isabelle Guyon may publish in the future.
Co-authorship network of co-authors of Isabelle Guyon
This figure shows the co-authorship network connecting the top 25 collaborators of Isabelle Guyon.
A scholar is included among the top collaborators of Isabelle Guyon based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Isabelle Guyon. Isabelle Guyon is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Guyon, Isabelle, et al.. (2022). CodaLab Competitions An Open Source Platform to Organize Scientific Challenges. SPIRE - Sciences Po Institutional REpository.26 indexed citations
2.
Palmero, Cristina, Julio C. S. Jacques, Albert Clapés, et al.. (2021). ChaLearn LAP Challenges on Self-Reported Personality Recognition and Non-Verbal Behavior Forecasting During Social Dyadic Interactions:Dataset, Design, and Results. VBN Forskningsportal (Aalborg Universitet).
Seijo-Pardo, Borja, Amparo Alonso‐Betanzos, Kristin P. Bennett, et al.. (2018). Analysis of imputation bias for feature selection with missing data.. The European Symposium on Artificial Neural Networks.1 indexed citations
7.
Escalera, Sérgio, Xavier Baró, Hugo Jair Escalante, & Isabelle Guyon. (2017). ChaLearn Looking at People - Events and Resources.. arXiv (Cornell University).2 indexed citations
8.
Hutter, Frank, Balázs Kégl, Rich Caruana, et al.. (2015). Automatic Machine Learning (AutoML). SPIRE - Sciences Po Institutional REpository.4 indexed citations
9.
Guyon, Isabelle, Amir Saffari, Gideon Dror, & Gavin C. Cawley. (2010). Model Selection: Beyond the Bayesian/Frequentist Divide. Journal of Machine Learning Research. 11(3). 61–87.93 indexed citations
10.
Guyon, Isabelle, Alexander Statnikov, & Constantin Aliferis. (2009). Time series analysis with the causality workbench. Neural Information Processing Systems. 119–143.4 indexed citations
11.
Guyon, Isabelle, et al.. (2006). Feature extraction : foundations and applications. Springer eBooks.1105 indexed citations breakdown →
12.
Guyon, Isabelle, Steve Gunn, Masoud Nikravesh, & Lotfi A. Zadeh. (2006). Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing). Springer eBooks.300 indexed citations
13.
Guyon, Isabelle, Steve Gunn, Asa Ben‐Hur, & Gideon Dror. (2004). Result Analysis of the NIPS 2003 Feature Selection Challenge. ePrints Soton (University of Southampton). 17. 545–552.293 indexed citations
14.
Guyon, Isabelle, et al.. (1997). Handwriting as computer interface. Cambridge University Press eBooks. 78–83.3 indexed citations
15.
Guyon, Isabelle, et al.. (1996). Discovering informative patterns and data cleaning. Knowledge Discovery and Data Mining. 181–203.138 indexed citations
Schenkel, M., et al.. (1992). Recognition-based Segmentation of On-Line Hand-printed Words. Neural Information Processing Systems. 5. 723–730.13 indexed citations
18.
Guyon, Isabelle, Bernhard E. Boser, & Vladimir Vapnik. (1992). Automatic Capacity Tuning of Very Large VC-Dimension Classifiers. Neural Information Processing Systems. 5. 147–155.123 indexed citations
19.
Guyon, Isabelle, Vladimir Vapnik, Bernhard E. Boser, Léon Bottou, & Sara A. Solla. (1991). Structural Risk Minimization for Character Recognition. Neural Information Processing Systems. 4. 471–479.59 indexed citations
20.
Denker, John S., W.R. Gardner, Hans Peter Graf, et al.. (1988). Neural Network Recognizer for Hand-Written Zip Code Digits. Neural Information Processing Systems. 1. 323–331.89 indexed citations
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.