http://apollonius.cs.utah.edu/web Thu, 12 Nov 2009 08:09:44 +0000 http://backend.userland.com/rss092 en [author]Sarang Joshi, Raj Varma Kommaraju, Jeff Phillips, and Suresh Venkatasubramanian[/author] 19th Fall Workshop on Computational Geometry, 2009 Links: PDF http://apollonius.cs.utah.edu/web/2009/10/10/matching-shapes-using-the-current-distance/ [author]P. Thomas Fletcher, John Moeller, Jeff Phillips and Suresh Venkatasubramanian[/author] 19th Fall Workshop on Computational Geometry Links: PDF This material is based upon work supported by the National Science Foundation under Grant No. 0841185 http://apollonius.cs.utah.edu/web/2009/10/10/computing-hulls-in-positive-definite-space/ [author]Divesh Srivastava and Suresh Venkatasubramanian[/author] 35th International Conference on Very Large Databases (VLDB) We are awash in data. The explosion in computing power and computing infrastructure allows us to generate multitudes of data, in differing formats, at different scales, and in inter-related areas. Data management is fundamentally about the harnessing of this ... http://apollonius.cs.utah.edu/web/2009/09/07/information-theory-for-data-management-tutorial/ [author]Piyush Rai, Hal Daume III, and Suresh Venkatasubramanian[/author] Twenty-First International Joint Conference on Artificial Intelligence (IJCAI-09) We present a streaming model for large scale classification (in the context of $\ell_2$-SVM) by leveraging connections between learning and computational geometry. The streaming model imposes the constraint that only a single pass over the data ... http://apollonius.cs.utah.edu/web/2009/04/08/streamed-learning-one-pass-svms/ [author]Shankar Krishnan and Suresh Venkatasubramanian[/author] SMI 2009: IEEE International Conference on Shape Modeling and Applications http://apollonius.cs.utah.edu/web/2009/02/23/approximate-shape-matching-and-symmetry-detection-for-3d-shapes-with-guaranteed-error-bounds/ [author]Amit Goyal, Hal Daume and Suresh Venkatasubramanian[/author] North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL HLT) 2009 (to appear) In this paper, we explore a streaming algorithm paradigm to handle large amounts of data for NLP problems. We present an efficient low-memory method for constructing high-order ... http://apollonius.cs.utah.edu/web/2009/01/19/streaming-for-large-scale-nlp-language-modelling/ [author]Babak Ahmadi, Marios Hadjieleftheriou, Thomas Seidl, Divesh Srivastava and Suresh Venkatasubramanian[/author] 12th International Conference on Extending Database Technology (EDBT 09) (to appear) In this work we concentrate on categorization of relational attributes based on their data type. Assuming that attribute type/characteristics are unknown or unidentifiable, we analyze and compare a variety of ... http://apollonius.cs.utah.edu/web/2008/11/15/type-based-categorization-of-relational-attributes/ [author]Nick Koudas, Avishek Saha, Divesh Srivastava and Suresh Venkatasubramanian[/author] 25th International Conference on Data Engineering, 2009 (to appear) When merging data from various sources, it is often the case that small variations in data format and interpretation cause traditional functional dependencies (FDs) to be violated, without there being an intrinsic violation of ... http://apollonius.cs.utah.edu/web/2008/06/28/metric-functional-dependencies/ [author]Suresh Venkatasubramanian[/author] In Privacy-Preserving Data Mining: Models and Algorithms (Springer). Ed. Charu Aggarwal, Philip S. Yu An excerpt from the introduction: In this chapter, we survey the various approaches that have been proposed to measure privacy (and the loss of privacy). Since most privacy concerns (especially those related to health-care information) are raised ... http://apollonius.cs.utah.edu/web/2008/03/30/on-measures-of-privacy/ Suresh Venkatasubramanian Springer Encyclopedia on Databases, to appear. An instance of a clustering problem (see clustering) consists of a collection of points in a distance space, a measure of the cost of a clustering, and a measure of the size of a clustering. The goal is to compute a partitioning of the ... http://apollonius.cs.utah.edu/web/2008/03/29/clustering-on-streams/