Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

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Costs Engineering & Materials Science
Regularization Mathematics
Learning systems Engineering & Materials Science
Profitability Engineering & Materials Science
Experiments Engineering & Materials Science
Convex optimization Engineering & Materials Science
Regret Mathematics
Prediction Mathematics

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Grants 2014 2020

Research Output 2006 2017

  • 592 Citations
  • 12 Scopus h-Index
  • 28 Conference contribution
  • 14 Article

A data science approach to understanding residential water contamination in flint

Chojnacki, A., Dai, C., Farahi, A., Shi, G., Webb, J., Zhang, D. T., Abernethy, J. & Schwartz, E. Aug 13 2017 KDD 2017 - Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, Vol. Part F129685, p. 1407-1416 10 p.

Research output: ResearchConference contribution

Contamination
Lead
Water
Testing
Water supply
1 Citations

Analysing ratemyprofessors evaluations across institutions, disciplines, and cultures: The tell-tale signs of a good professor

Azab, M., Mihalcea, R. & Abernethy, J. 2016 Social Informatics - 8th International Conference, SocInfo 2016, Proceedings. Springer Verlag, Vol. 10046 LNCS, p. 438-453 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10046 LNCS)

Research output: ResearchConference contribution

Evaluation
Culture
Narrative
Students
Qualitative Analysis

Faster convex optimization: Simulated annealing with an efficient universal barrier

Abernethy, J. & Hazan, E. 2016 33rd International Conference on Machine Learning, ICML 2016. International Machine Learning Society (IMLS), Vol. 6, p. 3734-3746 13 p.

Research output: ResearchConference contribution

Convex optimization
Simulated annealing
Tropics
Temperature

Threshold bandit, with and without censored feedback

Abernethy, J., Amin, K. & Zhu, R. 2016 In : Advances in Neural Information Processing Systems. p. 4896-4904 9 p.

Research output: Research - peer-reviewArticle

Feedback
1 Citations

Utilizing high-dimensional features for real-time robotic applications: Reducing the curse of dimensionality for recursive Bayesian estimation

Li, J., Ozog, P., Abernethy, J., Eustice, R. M. & Johnson-Roberson, M. Nov 28 2016 IROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems. Institute of Electrical and Electronics Engineers Inc., Vol. 2016-November, p. 1230-1237 8 p. 7759205

Research output: ResearchConference contribution

Sonar
State estimation
Kalman filters
Learning systems
Robotics