publications
Stanislav Funiak, Carlos E. Guestrin, Mark A. Paskin, and Rahul Sukthankar (2006). Distributed Localization of Networked Cameras. To appear in Proceedings of the Fifth International Symposium on Information Processing in Sensor Networks 2005 (IPSN-06).
Mark A. Paskin and Sebastian Thrun (2005). Robotic Mapping with Polygonal Random Fields. To appear in Proceedings of the 21st Conference on Uncertainty in Artificial Intelligence (UAI-05).
Also see: http://paskin.org/prf
Mark A. Paskin, Carlos E. Guestrin, and Jim McFadden (2005). A Robust Architecture for Inference in Sensor Networks. In Proceedings of the Fourth International Symposium on Information Processing in Sensor Networks 2005 (IPSN-05). (This paper won a Best Paper Award.)
Also see: Mark A. Paskin and Carlos E. Guestrin (2004). A Robust Architecture for Distributed Inference in Sensor Networks. Technical Report IRB-TR-03-039, Intel Research.
Mark A. Paskin and Carlos E. Guestrin (2004). Robust Probabilistic Inference in Distributed Systems. In Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (UAI-04).
Carlos Guestrin, Romain Thibaux, Peter Bodik, Mark A. Paskin, and Samuel Madden (2004). Distributed Regression: an Efficient Framework for Modeling Sensor Network Data. In Proceedings of the Third International Symposium on Information Processing in Sensor Networks 2004 (IPSN-04).
Also see: Mark A. Paskin and Gregory D. Lawrence (2003). Junction Tree Algorithms for Solving Sparse Linear Systems. Technical Report UCB/CSD-03-1271, University of California, Berkeley.
Mark A. Paskin (2003). Sample Propagation. In S. Thrun, L. Saul, and B. Schoelkopf eds., Advances in Neural Information Processing Systems 16 (NIPS-03). Cambridge, MA: MIT Press.
Mark A. Paskin (2003). Thin Junction Tree Filters for Simultaneous Localization and Mapping. In G. Gottlob and T. Walsh eds., Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence (IJCAI-03), pp. 1157–1164. San Francisco, CA: Morgan Kaufmann. (This paper won a Distinguished Paper Award.)
Also see: Mark A. Paskin (2002). Thin Junction Tree Filters for Simultaneous Localization and Mapping. Technical Report UCB/CSD-02-1198, University of California, Berkeley. Revised February 4, 2003.
Also see: http://paskin.org/slam
Mark A. Paskin (2002). Maximum Entropy Probabilistic Logic. Technical Report UCB/CSD-01-1161, University of California, Berkeley.
Kevin P. Murphy and Mark A. Paskin (2001). Linear-time Inference in Hierarchical HMMs. In T. Dietterich, S. Becker, and Z. Gharahmani eds., Advances in Neural Information Processing Systems 14 (NIPS-01). Cambridge, MA: MIT Press.
Mark A. Paskin (2001). Grammatical Bigrams. In T. Dietterich, S. Becker, and Z. Gharahmani eds., Advances in Neural Information Processing Systems 14 (NIPS-01). Cambridge, MA: MIT Press.
Also see: Mark A. Paskin (2001). Cubic-time Parsing and Learning Algorithms for Grammatical Bigram Models. Technical Report UCB/CSD-01-1148, University of California, Berkeley.
thesis
Mark A. Paskin (2004). Exploiting Locality in Probabilistic Inference. Ph. D. thesis, University of California, Berkeley, September 2004.