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Graduate student interns & co-authors

Yiwen Wan, 2012
Omar Zia Khan, 2010
Carlos Diuk-Wasser, 2008
Jing Xu, 2007
Senthilkumar G. Cheetancheri, 2006
Alex Newman, 2004
Gert Lanckriet, 2003
Adam Zagorecki, 2003


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Bayesian Modeling Applications Workshop Proceedings

11th UAI Bayesian Modeling Applications Workshop, (BAW 2014), Quebec City, Quebec, Canada

10th UAI Bayesian Modelling Applications Workshop, (BAW 2013), Bellvue, WA, USA

9th UAI Bayesian Modelling Applications Workshop, (BAW 2012), Catalina Island, CA, USA

8th UAI Bayesian Modelling Applications Workshop, (BAW 2011), Barcelona, Spain.

Proceedings of the Seventh UAI Bayesian Modeling Application Workshop (BMAW 2009), Cambridge, MA, USA, July 13, 2009.

6th UAI Bayesian Modelling Applications Workshop (BMAW 2008), Helsinki, Finland.

5th UAI Bayesian Modeling Applications Workshop (UAI-AW 2007), Vancouver, BC, Canada.

4th UAI Bayesian Modeling Applications Workshop (BMAW 2006), Cambridge, MA, USA.

AUTOMOTIVE, USER EXPERIENCE

 J. M. Agosta, J. Edson, Binta Ayofemi, et al. The Connected Car 2025 A collaboration between Toyota-ITC and Lunar Design,2013. Vimeo

CONTENT SEARCH

Rob Ennals, Beth Trushkowsky, J. M. Agosta, Tye Rattenbury, Tad Hirsch Highlighting Disputed Claims on the Web 4th Workshop on Information Credibility on the Web (WICOW 2010) Raleigh, NC, USA on April 2010, PDF.

Rob Ennals, Dan Byler, J. M. Agosta, Barbara Rosario What is Disputed on the Web? 19th International World Wide Web Conference (WWW 2010) Raleigh, NC, USA on April 2010, PDF.

DISTRIBUTED INFERENCE AND NETWORKS

 J. M. Agosta, Daniel Ting, Jaideep Chadrashekar, Mark Crovella, Nina Taft, Mixture Models of Endhost Network Traffic IEEE INFOCOM 2013, Torino, IT. April 2013. Published version: PDF. Presentation: SLIDES. Arxiv full version: PDF.

Senthilkumar G. Cheetancheri, J. M. Agosta, Karl N. Levitt, Felix Wu, and Jeff Rowe, Optimal Cost, Collaborative, and Distributed Response to Zero-Day Worms-- A Control Theoretic Approach in R. Lippmann, E. Kirda, and A. Trachtenberg (Eds.): Recent Advances in Intrusion Detection (RAID) Symposium (RAID-08), Boston, MA. pp. 231-250 Springer-Verlag Berlin Heidelberg 2008. PDF
See the article about this paper in Science Daily, dated 14 Jan 2009.

J. M. Agosta, Jaideep Chandrashekar, Frédéric Giroire, Carl Livadas & Jing Xu, Abstract: Approaches to Anomaly Detection using Host Network-Traffic Traces, NIPS workshop, Machine Learning for Systems Problems (MLSys07) Whistler, BC, Canada. December 7, 2007. PDF Abstract, PDF Poster

J. M. Agosta, Carlos Diuk, Jaideep Chandrashekar and Carl Livadas An Adaptive Anomaly Detector For Worm Detection Workshop on Tackling Computer Systems Problems with Machine Learning Techniques (sysML-07) 2007. PDF

Senthilkumar G. Cheetancheri, J. M. Agosta, Denver H. Dash, Karl N. Levitt, Jeff Rowe, and Eve M. Schooler. A distributed host-based worm detection system In Proceedings of the 2006 SIGCOMM Workshop on Large-Scale Attack Defense (Pisa, Italy, September 11 - 15, 2006). LSAD'06. ACM Press, New York, NY, 107-113.

J. M. Agosta, Jaideep Chandrashekar Anti-worm Dynamics in Distributed Detection Adaptive and Resilient Computing Security Workshop (ARCS06), August 2006. PDF

Denver Dash, Branislav Kveton, J. M. Agosta, Eve Schooler, Jaideep Chandrashekar, Abraham Bachrach and Alex Newman, ”When gossip is good:” Distributed Probabilistic Inference For Detection Of Slow Network Intrusions. In Proceedings of the Twenty-First National Conference on Artificial Intelligence, AAAI Press, Menlo Park, California, 2006.

J. M. Agosta, Distributed decision agents for managability and security Business Network Fellowship Statement of Purpose, Santa Fe Institute, March 2006. PDF

Denver Dash, J. M. Agosta, Jaideep Chandrashekar, Eve Schooler, A Distributed Host-based Worm Detection System. Proceedings of the ACM SIGCOMM Workshop on Large Scale Attack Defense (LSAD06), September, 2006.

Denver Dash, J. M. Agosta, Abraham Bachrach, Branislav Kveton, Alex Newman, Eve Schooler, Learning robust generative models for distributed anomaly detection. Intelligence Beyond the Desktop, In conjunction with the Nineteenth annual conference on Neural Information Processing Systems (NIPS), 2005.

J. M. Agosta, Abraham Bachrach, Denver Dash, Branislav Kveton, Alex Newman, Eve Schooler, Distributed inference to detect a network attack. Adaptive and Resilient Computing Security Workshop (ARCS05), 2005. PDF

J. M. Agosta, S. Crosby, Network Integrity by Inference in Distributed Systems NIPS workshop, Robust Communication Dynamics in Complex Networks Abstract Whistler, BC, Canada. December 12-13, 2003.

Patents

J. M. Agosta, Hormuzd Khosravi, Authenticated Distributed Detection And Inference
US Patent 7,921,453. Filed 12/2006, issued 4/2011.

Alex P Newman, Toby Kohlenberg, J. M. Agosta. Inappropriate Access Detector Based On System Segmentation Faults, Filed 7/2006 Pending.

Simon Crosby, J. M. Agosta and Denver Dash, A Method For Distributed Sequential Hypothesis Testing In Autonomic Computing Systems.
US Patent 7,603,461 B2. Filed 12/2004, Issued 10/2009.

Simon Crosby, J. M. Agosta and Denver Dash. A Method for Collaborative Attack Detection in Networked Computer Systems. Filed 11/2004 Pending.

DIAGNOSIS AND RECOGNITION

  J. M. Agosta, P. Pillai, A Lightweight Inference Method for Image Classi cation, Accepted at MSTND-13, workshop at UAI-13, July 15, 2013. PDF

  Omar Zia Khan, Pascal Poupart and J. M. Agosta, Iterative Model Refinement of Recommender MDPs based on Expert Feedback European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2013, (ECMLPKDD13), Prague, Czechoslovakia, September 23-27, 2013. PDF

Omar Zia Khan, Pascal Poupart and J. M. Agosta, Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints Neural Information Processing Systems 2011 (NIPS 11), Granada, Spain, December 12-15, 2011. PDF

Agosta, J. M., Omar Zia Khan and Pascal Poupart, Evaluation Results for a Query-Based Diagnostics Application The Fifth European Workshop on Probabilistic Graphical Models (PGM 10) Helsinki, Finland, September 13-15, 2010. PDF

Agosta, J. M., Thomas Gardos and Marek J. Druzdel, Query-based Diagnostics The Fourth European Workshop on Probabilistic Graphical Models (PGM 08) Hirtshals, Denmark, September 17-19, 2008. PDF

Agosta, J. M. and Thomas Gardos, Bayes Network “Smart Diagnostics” in Intel Technology Journal “Toward The Proactive Enterprise”, Vol 8, Issue 4 (November 17, 2004) pp.361-372. PDF

Agosta, J. M. and Jonathan S. Katz, The use of Evidence Conflict to extend Diagnostic Models in Kai Goebel and Piero Bonissone, Cochairs Information Refinement and Revision for Decision Making: Modeling for Diagnostics, Prognostics, and Prediction, Papers from the 2002 AAAI Spring Symposium, AAAI Technical Report SS-02-03, p.9

Agosta, J.M. and Jonathan Weiss, Active Fusion for Diagnosis, Guided by Mutual Information Measures, Proceedings of the 2nd International Conference on Information Fusion, (Sunnyvale, CA, July 1999), pp. 337-344

Millán, E., Agosta, J.M., Perez de la Cruz, J.-L.: Bayesian Student Modelling and the Problem of Parameter Specification. British Journal of Educational Technology 32, 2 (2001) 171-181

Agosta, J. M, “ Approximating the Noisy-Or Model by Naive Bayes” in Peter Haddawy and Steve Hanks, cochairs, Interactive and Mixed-Initiative Decision-Theoretic Systems, Papers from the 1998 AAAI Spring Symposium AAAI Technical Report SS-98-03, p.1

Agosta, J. M. Constraining Influence Diagram Structure by Generative Planning: An Application to the Optimization of Oil Spill Response. Proceedings of the Twelfth Conference on Uncertainty in Artificial Intelligence, (San Mateo: Morgan Kaufmann, 1996) pp. 11-19.

Agosta, J. M. Diagramming Influences: The use of Influence Diagrams and Data Flow diagrams in organizational decision-making (DRAFT, October 1994)

Agosta, J. M. and John S. Breese Causal Probability Networks in the process of product support IEEE CAIA '92 Workshop on Artificial Intelligence for Customer Service and Support (Monterey, CA 1992)

Agosta, J. M., 'Conditionally Inter-Causally Independent' node distributions, a property of 'noisy-or' models in B. D'Ambrosio, editor, Proceedings of the Seventh Conference on Uncertainty in Artificial Intelligence, (San Mateo: Morgan Kaufmann, 1991), pp 9-16

Agosta, J. M., An example of a Bayes network of relations among visual features, in Su-Shing Chen, editor, Stochastic and neural methods in signal processing, image processing and computer vision, (Bellingham, WA: SPIE proceeding series, vol. 1569, 1991)

Agosta, J. M., The structure of Bayes networks for visual recognition, in T.S. Levitt L. N. Kanal and J. F. Lemmer editors, Uncertainty in Artificial Intelligence 4,(New York: Elsevier Science Publishers, 1990) p.397-405

T.S. Levitt, J. M. Agosta and T. O. Binford, Model-Based Influence Diagrams for Machine Vision, in M.  Henrion and R. Shachter, editors, Proceedings of the Fifth Workshop on Uncertainty in Artificial Intelligence, (Windsor, Ontario, 18-20 August, 1989) pp. 233-244

DECISION THEORETIC PLANNING

Agosta, J. M.Constraining Influence Diagram Structure by Generative Planning: An Application to the Optimization of Oil Spill Response in Eric Horvitz and Finn Jensen, editors, Proceedings of the Twelfth conference on Uncertainty in Artificial Intelligence, (Portland OR, Reed College, 1996)

Agosta, J. M., Representation of Deliberation and Execution Time in Influence Diagrams in Craig Boutilier & Moises Goldszmidt, cochairs, Extending Theories of Action: Formal Theory & Practical Applications, Papers from the 1995 AAAI Symposium AAAI Technical Report SS-95-07, p.1

Agosta, J. M. and Roberto Desimone, Some Questions about Interpreting Plans as Multi-Stage Influence Diagrams in Steve Hanks, Program chair , Decision-Theoretic Planning, Papers from the 1994 Spring AAAI Symposium, AAAI Technical Report SS-94-06, p. 279

AUTOMATED EMERGENCY PLANNING

Agosta, J. M. and David Wilkins Emergency Planning for Marine Oil Spill Incidents, IEEE Expert, (December 1996) pp. 6-8

Agosta, J. M., Formulation and Implementation of an Equipment Configuration Problem with the SIPE2 Generative Planner in Adele Howe, chair, Integrated Planning Applications, Papers from the 1995 AAAI Symposium, AAAI Technical Report SS-95-04, p.1

Desimone, R.V. and J. M. Agosta. Oil Spill Response Simulation: The Application of AI Planning Technology, Proceedings of the 1994 Simulation MultiConference, Simulation for Emergency Management track,  (La Jolla, CA, April 1994)

MISCELLANEOUS

Agosta, J. M., Norman R. Nielsen and Gerry Andeen, Fast Training of Neural Networks for Load Forecasting, Proceedings of the American Power Conference, (Chicago, IL: 9-11 April 1996 )

Agosta, J. M. Soft Logic and Flexible Reasoning: The Real World Computing Project in Japan (Menlo Park, CA: SRI International Business Intelligence Program, Datalog D94-1812, 1994)