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.
Two-person interaction detection using body-pose features and multiple instance learning
2012346 citationsJean Honorio, Dimitris Samaras et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Jean Honorio'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 Jean Honorio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jean Honorio more than expected).
This network shows the impact of papers produced by Jean Honorio. 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 Jean Honorio. The network helps show where Jean Honorio may publish in the future.
Co-authorship network of co-authors of Jean Honorio
This figure shows the co-authorship network connecting the top 25 collaborators of Jean Honorio.
A scholar is included among the top collaborators of Jean Honorio 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 Jean Honorio. Jean Honorio is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Honorio, Jean, et al.. (2021). Novel Change of Measure Inequalities with Applications to PAC-Bayesian Bounds and Monte Carlo Estimation. International Conference on Artificial Intelligence and Statistics. 1711–1719.1 indexed citations
4.
Honorio, Jean, et al.. (2020). Minimax Bounds for Structured Prediction Based on Factor Graphs. 213–222.1 indexed citations
5.
Honorio, Jean, et al.. (2019). Exact inference in structured prediction. Neural Information Processing Systems. 32. 3698–3707.
6.
Honorio, Jean, et al.. (2017). Learning Sparse Polymatrix Games in Polynomial Time and Sample Complexity. International Conference on Artificial Intelligence and Statistics. 1486–1494.
Honorio, Jean, et al.. (2013). Two-Sided Exponential Concentration Bounds for Bayes Error Rate and Shannon Entropy. DSpace@MIT (Massachusetts Institute of Technology). 459–467.2 indexed citations
10.
Honorio, Jean, et al.. (2013). FMRI Analysis of Cocaine Addiction Using K-Support Sparsity. SPIRE - Sciences Po Institutional REpository.
11.
Honorio, Jean, Dimitris Samaras, Irina Rish, & Guillermo Cecchi. (2012). Variable Selection for Gaussian Graphical Models. International Conference on Artificial Intelligence and Statistics. 538–546.8 indexed citations
Honorio, Jean & Dimitris Samaras. (2010). Multi-Task Learning of Gaussian Graphical Models. International Conference on Machine Learning. 447–454.29 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.