PAPERS AND PUBLICATIONS

Warning: This is a list. I haven’t had a chance to link the actual papers. Please go to my co-author’s web pages for the actual papers (www.live.com is your friend).

  1. Moises Goldszmidt, "Making Life Better One Large System at a Time: Challenges for UAI Research", in Proceedings of the 23rd Conference on Uncertainty in Artificial Intelligence, UAI 2007, (Invited Paper)
  2. Yinglian Xie, Fang Yu, Kannan Achan, Eliot Gillum, Moises Goldszmidt, and Ted Wobber, "How Dynamic are IP Addresses", In Proceedings of ACM SIGCOMM 2007.
  3. Emre Kiciman, Dave Maltz, Moises Goldszmidt, and John Platt, “Mining web logs to debug distant connectivity problems”, ACM SIGCOMM Workshop on Mining Network Data (MineNet), 2006
  4. Ira Cohen, Moises Goldszmidt, Steve Zhang, Armando Fox, Julie Symons, and Terence Kelly, “Capturing, Indexing, Clustering, and Retrieving System History”, Symposium on Operating System Principles (SOSP), 2005
  5. Steve Zhang, Ira Cohen, Moises Goldszmidt, Julie Symons, and Armando Fox, "Ensembles of models for automated diagnosis of system performance problems", Dependable Systems and Networks (DSN), 2005
  6. Moises Goldszmidt, Ira Cohen, Armando Fox, and Steve Zhang, "Three research challenges at the intersection of machine learning, statistical induction, and systems", HotOS 2005
  7. Rob Powers, Ira Cohen, and Moises Goldszmidt, "Short term performance forecasting in enterprise systems", Knowledge Discovery and Datamining (KDD), 2005
  8. Ira Cohen, Moises Goldszmidt, Terence Kelly, Julie Symons, and Jeff Chase, "Correlating instrumentation data to system states: A building block for automated diagnosis and control", Operating Systems Design and Implementation (OSDI), 2004
  9. Ira Cohen and Moises Goldszmidt, "Properties and Benefits of Calibrated Classifiers", European Conference on Machine Learning/ European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD) 2004
  10. Moises Goldszmidt, Derek Palma, Bikash Sabata, “On the Quantification of e-Business Capacity”, In Proceedings of ACM Ecommerce 2001
  11. Craig Boutilier, Richard Dearden, and Moises Goldszmidt, “Stochastic Dynamic Programming with Factored Representations”. Artificial Intelligence, 2000
  12. Moises Goldszmidt “Learning Bayesian Networks from Data”, in the Italian Association of Artificial Intelligence Magazine, 2000.
  13. Craig Boutilier, Moises Goldszmidt, and Bikash Sabata, “Sequential Auctions for the Allocation of Resources with Complementarities.” In Proceedings of the International Joint Conference on Artificial Intelligence, IJCAI-1999
  14. Craig Boutilier, Moises Goldszmidt, and Bikash Sabata, “Continuous Value Function Approximation for Sequential Bidding Policies.” In Proceedings of the 15th Conference on Uncertainty in Artificial Intelligence, UAI-1999.
  15. Nir Friedman, Moises Goldszmidt, and Abraham Wyner, “Data Analysis with Bayesian Networks: A Bootstrap Approach.” In Proceedings of the 15th Conference on Uncertainty in Artificial Intelligence, UAI-1999.
  16. Nir Friedman, Moises Goldszmidt, and Abraham Wyner, “On the Application of the Bootstrap for Computing Confidence Features of Induced Bayesian Networks.” In Proceedings of Artificial Intelligence and Statistics, AI&S 1999.
  17. Bikash Sabata and Moises Goldszmidt, “Fusion of Multiple Cues for Video Segmentation.” In Proceedings of the Second International Conference on Information Fusion, 1999.
  18. Nir Friedman and Moises Goldszmidt, “Learning Bayesian Networks with Local Structure.” In Learning in Graphical Models, Michael Jordan editor, 1998.
  19. Nir Friedman, Moises Goldszmidt, and Thomas Lee, “Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Worlds.” In Proceedings of the International Conference on Machine Learning, ICML 1998.
  20. Nir Friedman, Dan Geiger, and Moises Goldszmidt, “Bayesian Network Classifiers.” Machine Learning, 1997
  21. Nir Friedman and Moises Goldszmidt, “Sequential Learning of Bayesian Networks Structure.” In Proceedings of the 13th Conference on Uncertainty in Artificial Intelligence, UAI-1997.
  22. Nir Friedman, Moises Goldszmidt, David Heckerman, and Stuart Russell, “Challenge: Where is the Impact of Learning Bayesian Networks.” In Proceedings of the International Joint Conference on Artificial Intelligence, IJCAI-1997.
  23. Moises Goldszmidt and Judea Pearl, “Qualitative Probabilities for Default Reasoning, Belief Revision, and Causal Modeling.” Artificial Intelligence, 1996
  24. Nir Friedman and Moises Goldszmidt, “Building Classifiers using Bayesian Networks.” In Proceedings of the National Conference on Artificial Intelligence, AAAI-1996.
  25. Nir Friedman and Moises Goldszmidt, “Learning Bayesian Networks with Local Structure.” In Proceedings of the 12th Conference on Uncertainty in Artificial Intelligence, CUAI-1996.
  26. Nir Friedman and Moises Goldszmidt, “Discretizing Continuous Attributes While Learning Bayesian Networks.” In Proceedings of the International Conference on Machine Learning, ICML-1996.
  27. Craig Boutilier, Nir Friedman, Moises Goldszmidt, and Daphne Koller, “Context-Specific Independence in Bayesian Networks.” In Proceedings of the 12th Conference on Uncertainty in Artificial Intelligence, UAI-1996.
  28. Craig Boutilier and Moises Goldszmidt, “The Frame Problem and Bayesian Network Action Representations.” In Proceedings of the Canadian Conference on Artificial Intelligence, CCAI-1996.
  29. Moises Goldszmidt and Judea Pearl, “Probabilistic Foundations of Qualitative Reasoning with Conditional Sentences.” In Foundations of Knowledge Representation and Reasoning, Gerd Brewka editor, CSLI Publications, USA, 1996.
  30. Moises Goldszmidt, “Fast Belief Update Using Order-of-Magnitude Probabilities.” In Proceedings of the 11th Conference on Uncertainty in Artificial Intelligence, UAI-1995.
  31. Craig Boutilier, Richard Dearden, and Moises Goldszmidt, “Exploiting Structure in Policy Construction.” In Proceedings of the International Joint Conference on Artificial Intelligence, IJCAI-1995.
  32. Craig Boutilier and Moises Goldszmidt, “On the Revision of Conditional Belief Sets.” In Conditionals: from Philosophy to Computer Science, Luis Farinas del Cerro et. al., editors, Oxford University Press, England, 1995.
  33. Moises Goldszmidt and Adnan Darwiche, “Plan Simulation Using Bayesian Networks.” In Proceedings of the 11th IEEE Conference on Artificial Intelligence Applications, CAIA-1995.
  34. Moises Goldszmidt, “Hedges, Background Knowledge, and Evidence: A Reply to Kyburg's Believing on the Basis of the Evidence.” Computational Intelligence, 10:1:53-56, 1994.
  35. Adnan Darwiche and Moises Goldszmidt, “Action Networks: A framework for reasoning about actions and change under uncertainty.” In Proceedings of the 10th Conference on Uncertainty in Artificial Intelligence, UAI-1994.
  36. Adnan Darwiche and Moises Goldszmidt, “On the Relation between Kappa Calculus and Probabilistic Reasoning.” In Proceedings of the 10th Conference on Uncertainty in Artificial Intelligence, UAI-1994.
  37. Max Henrion, Adnan Darwiche, Moises Goldszmidt, Gregory Provan, and Brendan del Favero, “An Experimental Comparison of Infinitesimal and Numerical Probabilities for Diagnostic Reasoning.” In Proceedings of the 5th International Workshop on Principles of Diagnosis, DX-1994.
  38. Moises Goldszmidt, Paul Morris, and Judea Pearl, “A Maximum Entropy Approach to Nonmonotonic Reasoning.” IEEE Pattern Analysis and Machine Intelligence, 15:3:220-232, 1993.
  39. Craig Boutilier and Moises Goldszmidt, “Revision by Conditional Beliefs.” In Proceedings of the 11th National Conference on Artificial Intelligence, AAAI-1993.
  40. Moises Goldszmidt and Judea Pearl, “Rank-Based Systems: A Simple Approach to Belief Revision, Belief Update, and Reasoning About Evidence and Actions.” In Proceedings of the 3rd International Conference on Principles o Knowledge Representation and Reasoning, KR-1992.
  41. Moises Goldszmidt and Judea Pearl, “Reasoning with Qualitative Probabilities Can Be Tractable.” In Proceedings of the 8th Conference on Uncertainty in Artificial, Intelligence, UAI-1992.
  42. Moises Goldszmidt and Judea Pearl, “Stratified Rankings for Causal Modeling.” In Proceedings of the Fourth International Workshop on Nonmonotonic Reasoning, 1992.
  43. Moises Goldszmidt and Judea Pearl, “On the Consistency of Defeasible Databases.” Artificial Intelligence, Vol. 52:2:121-149, 1991.
  44. Moises Goldszmidt and Judea Pearl, “System Z+: A Formalism for Reasoning with Variable Strength Defaults.” In Proceedings of American Association for Artificial Intelligence Conference, AAAI-1991.
  45. Moises Goldszmidt, Paul Morris, and Judea Pearl, “A Maximum Entropy Approach to Nonmonotonic Reasoning.” In Proceedings of American Association for Artificial Intelligence Conference, AAAI-1990.
  46. Moises Goldszmidt and Judea Pearl, “Deciding Consistency of Databases Containing Defeasible and Strict Information.” In Uncertainty in Artificial Intelligence (Vol. 5), M. Henrion et. al., editors, North Holland, Amsterdam, 1990. Also in the UCLA Annual Research Review 1990.
  47. Moises Goldszmidt and Judea Pearl, “On The Relation Between Rational Closure and System-Z.” In 3rd International Workshop on Nonmonotonic Reasoning, 1990.
  48. Moises Goldszmidt and Judea Pearl, “Deciding Consistency of Databases Containing Defeasible and Strict Information.” In Proceedings of the 5th Workshop on Uncertainty in Artificial Intelligence, UAI-1989.

EDITED VOLUMES:

  1. Craig Boutilier and Moises Goldszmidt “Proceedings of the 17th Conference on Uncertainty in AI”, Morgan Kaufman 2000.
  2. Craig Boutilier and Moises Goldszmidt “Extending Formal Theories of Action”, notes of the AAAI Spring Symposium Series, AAAI press, 1995.

OTHER:

  1. Thomas Lee and Moises Goldszmidt “Tree Augmented NaiveBayes, Bayesian Network Classifier – TAN Version 2.1 User Manual.” SRI International Technical Memorandum 1999.
  2. Moises Goldszmidt and Mehran Sahami, “A Probabilistic Based Approach to Full-Text Clustering.” SRI International Technical Memorandum 1998.
  3. Moises Goldszmidt and David Jensen (Eds.), “DARPA Recommendations Report on Knowledge Discovery, Data mining, and Machine Learning Research,” 1998.
  4. Moises Goldszmidt and Vladimir Lifschitz, “A Report on the International Workshop on Nonmonotonic Reasoning.” In AI Magazine, 1997.
  5. Moises Goldszmidt, “Research Issues in Qualitative and Abstract Probability: A Report on the 1993 San Francisco Workshop.” In AI Magazine, 15:4:63-66, 1994.

THESIS:

Title: Qualitative Probabilities: A Normative Framework for Common Sense Reasoning
Advisor: Prof. Judea Pearl
Committee: Prof. Sheila Greibach (Computer Science), Prof. Stot Parker (Computer Science), Prof. Yiannis Moschovakis (Mathematics), and Prof. Kit Fine (Philosophy).