V
Vipin Kumar
Researcher at University of Minnesota
Publications - 678
Citations - 67181
Vipin Kumar is an academic researcher from University of Minnesota. The author has contributed to research in topics: Parallel algorithm & Computer science. The author has an hindex of 95, co-authored 614 publications receiving 59034 citations. Previous affiliations of Vipin Kumar include University of Maryland, College Park & United States Department of the Army.
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Journal Article
Similarity measures for categorical data: A comparative evaluation
TL;DR: This paper studies the performance of a variety of similarity measures in the context of a specific data mining task: outlier detection and shows that while no one measure dominates others for all types of problems, some measures are able to have consistently high performance.
Proceedings ArticleDOI
Identification of functional modules in protein complexes via hyperclique pattern discovery.
TL;DR: This paper presents a hyperclique pattern discovery approach for extracting functional modules (hyperclique patterns) from protein complexes and demonstrates that a hyperClique pattern can be involved in different complexes performing different higher-order biological functions, although the pattern corresponds to a specific elementary biological function.
Journal ArticleDOI
An Integrative Multi-Network and Multi-Classifier Approach to Predict Genetic Interactions
TL;DR: An integrative, multi-network approach for predicting synthetic lethal interactions that significantly improves upon the existing approaches and derived the first yeast transcription factor genetic interaction network, part of which was well supported by literature.
Proceedings ArticleDOI
Parallel search algorithms for robot motion planning
TL;DR: It is shown that parallel search techniques derived from their sequential counterparts can enable the solution of instances of the robot motion planning problem which are computationally infeasible on sequential machines.
Book ChapterDOI
Scalable parallel formulations of depth-first search
Vipin Kumar,V. Nageshwara Rao +1 more
TL;DR: The analysis shows that the parallel formulation of DFS can provide near linear speedup on very large parallel architectures, particularly on ring and shared-memory architectures.