Publications

Publications in Refereed Journals, Collections, and Conference Proceedings

Alessandro Epasto, Andrés Muñoz Medina, Steven Avery, Yijian Bai, Robert Busa-Fekete, CJ Carey, Ya Gao, David Guthrie, Subham Ghosh, James Ioannidis, Junyi Jiao, Jakub Lacki, Jason Lee, Arne Mauser, Brian Milch, Vahab Mirrokni, Deepak Ravichandran, Wei Shi, Max Spero, Yunting Sun, Umar Syed, Sergei Vassilvitskii, and Shuo Wang (2021). "Clustering for Private Interest-based Advertising". Proc. 27th ACM SIGKDD Conf. on Knowledge Discovery & Data Mining (KDD): 2802-2810.
Luke S. Zettlemoyer, Brian Milch, and Leslie Pack Kaelbling (2009). "Multi-Agent Filtering with Infinitely Nested Beliefs". In Neural Information Processing Systems 21 (NeurIPS 2008): 1905-1912.
Brian Milch, Luke S. Zettlemoyer, Kristian Kersting, Michael Haimes, and Leslie Pack Kaelbling (2008). "Lifted Probabilistic Inference with Counting Formulas". Proc. 23rd AAAI Conference on Artificial Intelligence: 1062-1068.
Ashwin Deshpande, Brian Milch, Luke S. Zettlemoyer, and Leslie Pack Kaelbling (2007). "Learning Probabilistic Relational Dynamics for Multiple Tasks". Proc. 23rd Conference on Uncertainty in Artificial Intelligence (UAI): 83-92.
Brian Milch, Bhaskara Marthi, Stuart Russell, David Sontag, Daniel L. Ong, and Andrey Kolobov (2007). "BLOG: Probabilistic Models with Unknown Objects". In Lise Getoor and Ben Taskar, eds. Introduction to Statistical Relational Learning. MIT Press, Cambridge, MA.
Brian Milch and Stuart Russell (2006). "General-Purpose MCMC Inference over Relational Structures". Proc. 22nd Conference on Uncertainty in Artificial Intelligence (UAI): 349-358.
Brian Milch, Bhaskara Marthi, Stuart Russell, David Sontag, Daniel L. Ong, and Andrey Kolobov (2005). "BLOG: Probabilistic Models with Unknown Objects". Proc. 19th International Joint Conference on Artificial Intelligence (IJCAI): 1352-1359.
Brian Milch, Bhaskara Marthi, David Sontag, Stuart Russell, Daniel L. Ong, and Andrey Kolobov (2005). "Approximate Inference for Infinite Contingent Bayesian Networks". 10th International Workshop on Artificial Intelligence and Statistics (AISTATS).
Monika Henzinger, Bay-Wei Chang, Brian Milch, and Sergey Brin (2005). "Query-Free News Search". World Wide Web: Internet and Web Information Systems 8(2):101-126. [Official version]
Monika Henzinger, Bay-Wei Chang, Brian Milch, and Sergey Brin (2003). "Query-Free News Search". Proc. 12th International World Wide Web Conference.
Daphne Koller and Brian Milch (2003). "Multi-Agent Influence Diagrams for Representing and Solving Games". Games and Economic Behavior 45(1): 181-221. [Official version]
Hanna Pasula, Bhaskara Marthi, Brian Milch, Stuart Russell, and Ilya Shpitser (2003). "Identity Uncertainty and Citation Matching". In Advances in Neural Information Processing Systems 15 (NeurIPS 2002). Cambridge, MA: MIT Press, pages 1401-1408.
Alex Franz and Brian Milch (2002). "Searching the Web by Voice". Proc. 19th International Conference on Computational Linguistics (COLING): 1213-1217.
Daphne Koller and Brian Milch (2001). "Multi-Agent Influence Diagrams for Representing and Solving Games". Proc. 17th International Joint Conference on Artificial Intelligence (IJCAI): 1027-1034.
Brian Milch and Daphne Koller (2000). "Probabilistic Models for Agents' Beliefs and Decisions". Proc. 16th Conference on Uncertainty in Artificial Intelligence (UAI): 389-396. Runner-up for Best Student Paper award.
Avi Pfeffer, Daphne Koller, Brian Milch, and Ken T. Takusagawa (1999). "SPOOK: A System for Probabilistic Object-Oriented Knowledge". Proc. 15th Conference on Uncertainty in Artificial Intelligence (UAI): 541-550.

Patents

Alexander Franz and Brian Milch. "System and method for identifying compounds through iterative analysis". US Patent 7,555,428, issued June 30, 2009. Assigned to Google Inc.
Alexander Franz, Brian Milch, Eric Jackson, Jenny Zhou, and Benjamin Diament. "Identifying language attributes through probabilistic analysis". US Patent 7,386,438, issued June 10, 2008. Assigned to Google Inc.
Alexander Mark Franz, Monika H. Henzinger, Sergey Brin, and Brian Christopher Milch. "Voice interface for a search engine". US Patent 7,027,987, issued April 11, 2006. Assigned to Google Inc.

Thesis

Brian Milch (2006). Probabilistic Models with Unknown Objects. Ph.D. Thesis, Computer Science Division, University of California, Berkeley, December 2006.

Other Publications

Brian Milch and Stuart Russell (2010). "Extending Bayesian Networks to the Open-Universe Case". In R. Dechter, H. Geffner, and J. Y. Halpern, eds. Heuristics, Probability and Causality: A Tribute to Judea Pearl. College Publications.
Brian Milch and Daphne Koller (2008). "Ignorable Information in Multi-Agent Scenarios". Technical report MIT-CSAIL-TR-2008-029, Massachusetts Institute of Technology, Cambridge, MA.
David McAllester, Brian Milch, and Noah D. Goodman (2008). "Random-World Semantics and Syntactic Independence for Expressive Languages". Technical report MIT-CSAIL-TR-2008-025, Massachusetts Institute of Technology, Cambridge, MA.
Brian Milch (2008). "Artificial General Intelligence through Large-Scale, Multimodal Bayesian Learning". Proc. 1st Conference on Artificial General Intelligence, Memphis, TN, March 2008.
Kristian Kersting, Brian Milch, Luke S. Zettlemoyer, Michael Haimes, and Leslie Pack Kaelbling (2007). "Reasoning about Large Populations with Lifted Probabilistic Inference" (extended abstract). NeurIPS 2007 Workshop on Statistical Network Models, Vancouver, BC. [Poster]
Brian Milch and Stuart Russell (2007). "First-Order Probabilistic Languages: Into the Unknown". In Stephen Muggleton, Ramon Otero, and Alireza Tamaddoni-Nezhad, eds. Inductive Logic Programming: 16th International Conference (ILP-2006). Lecture Notes in AI 4455. Berlin: Springer, pages 10-24. Written version of invited talk.
Brian Milch, Bhaskara Marthi, and Stuart Russell (2004). "BLOG: Relational Modeling with Unknown Objects". ICML 2004 Workshop on Statistical Relational Learning and Its Connections to Other Fields.
Bhaskara Marthi, Brian Milch, and Stuart Russell (2003). "First-Order Probabilistic Models for Information Extraction". IJCAI 2003 Workshop on Learning Statistical Models from Relational Data.