J
Joydeep Ghosh
Researcher at University of Texas at Austin
Publications - 513
Citations - 29870
Joydeep Ghosh is an academic researcher from University of Texas at Austin. The author has contributed to research in topics: Cluster analysis & Artificial neural network. The author has an hindex of 60, co-authored 474 publications receiving 26979 citations. Previous affiliations of Joydeep Ghosh include Los Angeles Mission College & National University of Singapore.
Papers
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Proceedings Article
Learning to rank with Bregman divergences and monotone retargeting
TL;DR: This paper introduces a novel approach for learning to rank (LETOR) based on the notion of monotone retargeting that can outperform the state of the art NDCG consistent techniques.
Journal ArticleDOI
Effective supra-classifiers for knowledge base construction
Kurt D. Bollacker,Joydeep Ghosh +1 more
TL;DR: Here, it is described theoretically how the probability that the Hamming nearest neighbor supra-classifier will predict the true target class approaches certainty at an exponential rate as more classifiers are reused.
Proceedings ArticleDOI
Blind image quality assessment without training on human opinion scores
TL;DR: A family of image quality assessment models based on natural scene statistics (NSS) that can predict the subjective quality of a distorted image without reference to a corresponding distortionless image, and without any training results on human opinion scores of distorted images are proposed.
Proceedings ArticleDOI
Hierarchical Density Shaving: A clustering and visualization framework for large biological datasets
TL;DR: HDS is presented, a framework that consists of a fast, hierarchical, density-based clustering algorithm, and provides a simple yet powerful 2D visualization of the hierarchy of clusters that can be very useful for further exploration.
Book ChapterDOI
Classification of Spatiotemporal Patterns with Applications to Recognition of Sonar Sequences
Joydeep Ghosh,Larry Deuser +1 more
TL;DR: Many tasks performed by humans and animals involve decision-making and behavioral responses to spatiotemporally patterned stimuli, and the recognition and processing of time-varying signals is fundamental to a wide range of cognitive processes.