Moises Goldszmidt, Marc Najork, and Stelios Paparizos, “Boot-strapping Language Identifiers for Short Colloquial Postings, in Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases  -- ECMLPKDD 2013

Edith Cohen, Daniel Delling, Fabian Fuchs, Andrew Goldberg, Moises Goldszmidt, and Renato Werneck, “Scalable Similarity Estimation in Social Networks: Closeness, Node Labels, and Random Edge Lengths”, in Proceedings of the ACM Conference on Online Social Networks - COSN 2013.

Anna Leontjeva, Moises Goldszmidt, Yniglian Xie, Fang Yu, and Martin Abadi, “Early Security Classification of Skype Users via Machine Learning, ACM AI and Security workshop AISec 2013.

Moises Goldszmidt, “Finding Soon-to-fail Disks in a Haystack”, Proceedings of the 4th Usenix Conference on Hot Topics in Storate and File Systems, HotStorage 2012.

John Davis, Suzanne Rivoire, Moises Goldszmidt, and Ehsan Ardestani, CHAOS: Composable Highly Accurate OS-Based Power Models, in IEEE International Symposium on Workload Characterization 2012

Dawn Woodard and Moises Goldszmidt, “Online Model-Based Clustering for Crisis Identification in Distributed Computing”, in Journal of the American Statistical Association, 2011.

John Davis, Suzanne Rivoire, Moises Goldszmidt, and Ehsan Ardestani, “Including Variability in Large-Scale Cluster Power Models, in Computer Architecture Letters, IEEE Computer Society, 2011.

Peter Bodik, Moises Goldszmidt, Armando Fox, Dawn Woodard, and Hans Andersen, “Fingerprinting the datacenter: Automated classification of performance crises”, ACM SIGOPS - Eurosys -2010.

Mark Gabel, Junfeng Yang, Yuan Yu, Moises Goldszmidt, and Zhedong Su, “Scalable and Systematic Detection of Buggy Inconsistencies”, in ACM International Conference on Systems, Programming, Languages, and Applications, OOPSLA Research Papers Track, 2010.

Moises Godlszmidt, “On Computers Diagnosing Computers”, in Heuristics, Probability, and Causality, A Tribute to Judea Pearl, Editors: Rina Dechter, Hector Geffner, and Joseph Halpern, 2010.

Moises Goldszmidt, Mihai Budiu, Yue Zhang, and Michael Pechuk, “Toward Automatic Policy Refinement in Repair Services for Large Distributed Systems”, in The 3rd ACM SIGOPS International Workshop on Large Scale Distributed Systems and Middleware, 2009. 

Peter Bodik, Moises Goldszmidt, and Armando Fox, “HiLighter: Automatically building robust signatures of performance behavior for small-and large-scale systems”, Solving systems problems with machine learning techniques (sysML), 2008.

Gabriela Cretu, Mihai Budiu, and Moises Goldszmidt, “Hunting for problems with Artemis”, Analysis of System Logs WASL) 2008.

Aleksander Simma, Moises Goldszmidt, John MacCormick, Paul Barham, Richard Black, Rebecca Isaacs, Richard Mortier, “CT-NOR: Representing and reasoning about events in continuous time”, International Conference on Uncertainty in Artificial Intelligence (UAI), 2008.

Moises Goldszmidt, “Making life better one large system at a time: Challenges for UAI research”, International Conference on Uncertainty in Artificial Intelligence (UAI), 2007.

Yinglian, Xie, Fang Yu, Kannan Achan, Eliot Gillum, Moises Goldszmidt, and Ted Wobber, “How dynamic are IP addresses”, ACM SIGCOMM 2007.

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.

Ira Cohen, Steve Zhang, Moises Goldszmidt, Julie Symons, Terence Kelly, and Armando Fox, “Capturing, Indexing, Clustering, and Retrieving System History”, Symposium on Operating System Principles (SOSP), 2005

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

Moises Goldszmidt, Ira Cohen, Armando Fox, and Steve Zhang, "Three research challenges at the intersection of machine learning, statistical induction, and systems", HotOS 2005

Rob Powers, Ira Cohen, and Moises Goldszmidt, "Short term performance forecasting in enterprise systems", Knowledge Discovery and Datamining (KDD), 2005

 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

 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

 Moises Goldszmidt, Derek Palma, Bikash Sabata, “On the Quantification of e-Business Capacity”, In Proceedings of ACM Ecommerce 2001

 Craig Boutilier, Richard Dearden, and Moises Goldszmidt, “Stochastic Dynamic Programming with Factored Representations”. Artificial Intelligence, 2000.

 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

 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.

 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. 

 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. 

 Bikash Sabata and Moises Goldszmidt, “Fusion of Multiple Cues for Video Segmentation.” In Proceedings of the Second International Conference on Information Fusion, 1999.

 Nir Friedman and Moises Goldszmidt, “Learning Bayesian Networks with Local Structure.” In Learning in Graphical Models, Michael Jordan editor, 1998.

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. 

Nir Friedman, Dan Geiger, and Moises Goldszmidt, “Bayesian Network Classifiers.” Machine Learning, 1997.

Nir Friedman and Moises Goldszmidt, “Sequential Learning of Bayesian Networks Structure.” In Proceedings of the 13th Conference on Uncertainty in Artificial Intelligence, UAI-1997.

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.

Moises Goldszmidt and Judea Pearl, “Qualitative Probabilities for Default Reasoning, Belief Revision, and Causal Modeling.”  Artificial  Intelligence, 1996

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.

Nir Friedman and Moises Goldszmidt, “Building Classifiers using Bayesian Networks.” In Proceedings of the National Conference on Artificial Intelligence, AAAI-1996.

Nir Friedman and Moises Goldszmidt, “Learning Bayesian Networks with Local Structure.” In Proceedings of the 12th Conference on Uncertainty in Artificial Intelligence, CUAI-1996.

Nir Friedman and Moises Goldszmidt, “Discretizing Continuous Attributes While Learning Bayesian Networks.”  In Proceedings of the International Conference on Machine Learning, ICML-1996.

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.

Craig Boutilier and Moises Goldszmidt, “The Frame Problem and Bayesian Network Action Representations.”  In Proceedings of the Canadian Conference on Artificial Intelligence, CCAI-1996.

Moises Goldszmidt, “Fast Belief Update Using Order-of-Magnitude Probabilities.” In Proceedings of the 11th Conference on Uncertainty in Artificial Intelligence, UAI-1995.

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.

Craig Boutilier, Richard Dearden, and Moises Goldszmidt, “Exploiting Structure in Policy Construction.”  In Proceedings of  the International Joint Conference on Artificial Intelligence, IJCAI-1995.

Moises Goldszmidt and Adnan Darwiche, “Plan Simulation Using Bayesian Networks.” In Proceedings of the 11th IEEE Conference on Artificial Intelligence Applications, CAIA-1995.

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.

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.

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.

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.

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.

Craig Boutilier and Moises Goldszmidt, “Revision by Conditional Beliefs.”  In Proceedings of the 11th National Conference on Artificial Intelligence, AAAI-1993.

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.

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.

Moises Goldszmidt and Judea Pearl, “Stratified Rankings for Causal Modeling.”  In Proceedings of the Fourth International Workshop on Nonmonotonic Reasoning, 1992.

Moises Goldszmidt and Judea Pearl, “On the Consistency of Defeasible Databases.” Artificial Intelligence, Vol. 52:2:121-149, 1991.

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.

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.

Moises Goldszmidt and Judea Pearl, “On The Relation Between Rational Closure and System-Z.”  In 3rd International Workshop on Nonmonotonic Reasoning, 1990.

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.

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 

Craig Boutilier and Moises Goldszmidt (Editors) “Proceedings of the 17th Conference on Uncertainty in AI”, Morgan Kaufman 2000.

Craig Boutilier and Moises Goldszmidt (Editors) “Extending Formal Theories of Action”, notes of the AAAI Spring Symposium Series, AAAI press, 1995.

OTHER 

Paul Barham, Richard Black, Moises Goldszmidt, Rebecca Isaacs, John MacCormick, Richard Mortier, Aleksandr Simma, “Constellation: automated discovery of service and host dependencies in networked systems”, no. MSR-TR-2008-67, pp. 14, Microsoft Research, Apr. 2008

Moises Goldszmidt “Learning Bayesian Networks from Data”, in the Italian Association of Artificial Intelligence Magazine, 2000.

Thomas Lee and Moises Goldszmidt “Tree Augmented NaiveBayes, Bayesian Network Classifier – TAN Version 2.1 User Manual.” SRI International Technical Memorandum 1999.

Moises Goldszmidt and Mehran Sahami, “A Probabilistic Based Approach to Full-Text Clustering.” SRI International Technical Memorandum 1998.

Moises Goldszmidt and David Jensen (Eds.), “DARPA Recommendations Report on Knowledge Discovery, Data mining, and Machine Learning Research,” 1998.

Moises Goldszmidt and Vladimir Lifschitz, “A Report on the International Workshop on Nonmonotonic Reasoning.” In AI Magazine, 1997.

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.

PATENTS (GRANTED)

Repair-policy refinement in distributed systems (8,504,874)

Data allocation and replication across distributed storage system (8,380,960)

Automated identification of performance crisis (8,078,913)

Adding prototype information into probabilistic models (8,010,341)

Automated health model generation and refinement (7,962,797)

Time modulated generative probabilistic models for automated causal discovery using a continuous time noisy-or (CT-NOR) models (7,958,069)

Dynamic activity model of network services (7,949,745)

Time modulated generative probabilistic models for automated causal discovery that monitors times of packets (7,895,146)

Automated discovery of service/host dependencies in computer networks (7,821,947)

Method of predicting response time for storage request (7,721,061)

Automated diagnosis and forecasting of service level objective states (7,693,982)

Determining a recurrent problem of a computer resource using signatures (7,502,971)

Method for grouping content requests by behaviors that relate to an information system’s ability to deliver specific quality of service objectives (7,451,226)

Method of defining a required information system capacity as a function of a user’s quality of service objective (7,441,028)

Method for determining behavior of an information system to control its ability to deliver a user’s quality of service (7,370,108)

Calibrated classifiers with threshold comparisons (7,266,536)

Determining and annotating a signature of a computer resource (7,184,935)

System and method for modeling information system capacity and accepting sessions in an information system (7,114,986)

PATENTS (PUBLISHED)

Identifying Subgraphs in Transformed Social Network Graphs (20140214936)

Estimating and Managing Power Consumption of Computing Devices Using Power Models (20130124885)

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).