Publications

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Deshpande A, Garofalakis MN, Jordan MI.  2001.  Efficient stepwise selection in decomposable models. Proc. UAI. :128-135.
Deshpande A.  2004.  An initial study of overheads of eddies. SIGMOD Rec.. 33(1):44-49.
Deshpande A, Khuller S, Malekian A, Toossi M.  2008.  Energy Efficient Monitoring in Sensor Networks. LATIN 2008: Theoretical InformaticsLATIN 2008: Theoretical Informatics. 4957:436-448.
Deshpande A, Hellerstein JM.  2004.  Lifting the burden of history from adaptive query processing. Proceedings of the Thirtieth international conference on Very large data bases - Volume 30. :948-959.
Deshpande A, Guestrin C, Madden SR.  2005.  Resource-aware wireless sensor-actuator networks. Data Engineering. 1001:40-40.
Deshpande A, Garofalakis M, Rastogi R.  2001.  Independence is good: dependency-based histogram synopses for high-dimensional data. SIGMOD Rec.. 30(2):199-210.
Deshpande A, Nath S, Gibbons PB, Seshan S.  2003.  Cache-and-query for wide area sensor databases. Proceedings of the 2003 ACM SIGMOD international conference on Management of data. :503-514.
Deshpande A, Khuller S, Malekian A, Toossi M.  2011.  Energy efficient monitoring in sensor networks. Algorithmica. 59(1):94-114.
Deshpande A, Hellerstein L.  2008.  Flow Algorithms for Parallel Query Optimization. IEEE 24th International Conference on Data Engineering, 2008. ICDE 2008. :754-763.
Deshpande A, Guestrin C, Madden S.  2005.  Using probabilistic models for data management in acquisitional environments. Proc. CIDR. :317-328.
Deshpande A, Ives Z, Raman V.  2007.  Adaptive query processing: why, how, when, what next? Proceedings of the 33rd international conference on Very large data bases. :1426-1427.
Deshpande A, Guestrin C, Madden SR, Hellerstein JM, Hong W.  2004.  Model-driven data acquisition in sensor networks. Proceedings of the Thirtieth international conference on Very large data bases - Volume 30. :588-599.
Deshpande A, Hellerstein JM.  2002.  Decoupled query optimization for federated database systems. 18th International Conference on Data Engineering, 2002. Proceedings. :716-727.
Deshpande A, Sarawagi S.  2007.  Probabilistic graphical models and their role in databases. Proceedings of the 33rd international conference on Very large data bases. :1435-1436.
Desimone R, Wilkins DE, Bienkowski M, desJardins M.  1993.  SOCAP: lessons learned in automating military operations planning. Proceedings of the 6th international conference on Industrial and engineering applications of artificial intelligence and expert systems. :384-393.
desJardins M.  1995.  How to succeed in graduate school: a guide for students and advisors: part II of II. Crossroads. 1(3):1-6.
desJardins M.  1993.  Workshop summary: AAAI-92 Workshop on Constraining Learning with Prior Knowledge. ACM SIGART Bulletin. 4(3):11-13.
desJardins M, Bulka B, Carr R, Hunt A, Rathod P, Rheingans P.  2006.  Heuristic search and information visualization methods for school redistricting. Proceedings of the 18th conference on Innovative applications of artificial intelligence - Volume 2. :1774-1781.
desJardins M.  2005.  DD-PREF: A language for expressing preferences over sets. In AAAI-05.
desJardins M.  1994.  Knowledge acquisition techniques for a military planning system. Tools with Artificial Intelligence, 1994. Proceedings., Sixth International Conference on. :454-460.
desJardins M, MacGlashan J, Wagstaff KL.  2010.  Confidence-based feature acquisition to minimize training and test costs. Proceedings of the SIAM Conference on Data Mining. 76(373):514-524.
desJardins M.  1994.  How to succeed in graduate school: a guide for students and advisors: part I of II. Crossroads. 1(2):3-9.
desJardins M, Rathod P, Getoor L.  2008.  LEARNING STRUCTURED BAYESIAN NETWORKS: COMBINING ABSTRACTION HIERARCHIES AND TREE‐STRUCTURED CONDITIONAL PROBABILITY TABLES. Computational Intelligence. 24(1):1-22.
desJardins M.  1993.  Pagoda: A Model for Autonomous Learning in Probabilistic Domains. AI Magazine. 14(1):75-75.
desJardins M.  1994.  Evaluation of learning biases using probabilistic domain knowledge. Proceedings of the workshop on Computational learning theory and natural learning systems (vol. 2) : intersections between theory and experiment: intersections between theory and experiment. :97-112.

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