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ORCIDMichael C. Horsch
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2010 – 2019
- 2013
[i5]Michael C. Horsch, William S. Havens:
Probabilistic Arc Consistency: A Connection between Constraint Reasoning and Probabilistic Reasoning. CoRR abs/1301.3864 (2013)- [i4]Michael C. Horsch, David L. Poole:
Estimating the Value of Computation in Flexible Information Refinement. CoRR abs/1301.6706 (2013) - [i3]Michael C. Horsch, David L. Poole:
An Anytime Algorithm for Decision Making under Uncertainty. CoRR abs/1301.7384 (2013) - [i2]Michael C. Horsch, David L. Poole:
Flexible Policy Construction by Information Refinement. CoRR abs/1302.3583 (2013) - [i1]Michael C. Horsch, David L. Poole:
A Dynamic Approach to Probabilistic Inference. CoRR abs/1304.1100 (2013) - 2012
- [c17]Craig D. S. Thompson, Michael C. Horsch:
Predicting Good Propagation Methods for Constraint Satisfaction. Canadian AI 2012: 218-229 - 2011
- [c16]Michael Janzen, Michael C. Horsch, Eric Neufeld:
A Method of Virtual Camera Selection Using Soft Constraints. FLAIRS 2011
2000 – 2009
- 2009
- [j2]Kevin Grant, Michael C. Horsch:
Methods for constructing balanced elimination trees and other recursive decompositions. Int. J. Approx. Reason. 50(9): 1416-1424 (2009) - 2008
- [c15]Michael Janzen, Michael C. Horsch, Eric Neufeld:
Camera selection using SCSPs. Future Play 2008: 252-253 - [p1]Eric Neufeld, Michael C. Horsch:
Bayesian Belief Networks. Wiley Encyclopedia of Computer Science and Engineering 2008 - 2007
- [c14]Kevin Grant, Michael C. Horsch:
Efficient Caching in Elimination Trees. FLAIRS 2007: 98-103 - 2006
- [c13]Kevin Grant, Michael C. Horsch:
Exploiting Dynamic Independence in a Static Conditioning Graph. Canadian AI 2006: 206-217 - [c12]Kevin Grant, Michael C. Horsch:
Methods for Constructing Balanced Elimination Trees and Other Recursive Decompositions. FLAIRS 2006: 812-817 - 2005
- [c11]Jingfang Zheng, Michael C. Horsch:
A Decision Theoretic Meta-reasoner for Constraint Optimization. Canadian AI 2005: 53-65 - [c10]Jeff Long, Michael C. Horsch:
A Bayesian Model to Smooth Telepointer Jitter. Canadian AI 2005: 108-119 - [c9]Kevin Grant, Michael C. Horsch:
Conditioning Graphs: Practical Structures for Inference in Bayesian Networks. Australian Conference on Artificial Intelligence 2005: 49-59 - 2004
- [c8]David Mould, Michael C. Horsch:
An Hierarchical Terrain Representation for Approximately Shortest Paths. PRICAI 2004: 104-113 - 2003
- [c7]Jingfang Zheng, Michael C. Horsch:
A Comparison of Consistency Propagation Algorithms in Constraint Optimization. AI 2003: 160-174 - 2002
- [j1]Julita Vassileva, Silvia Breban, Michael C. Horsch:
Agent Reasoning Mechanism for Long-Term Coalitions Based on Decision Making and Trust. Comput. Intell. 18(4): 583-595 (2002) - [c6]Michael C. Horsch, William S. Havens, Aditya Ghose:
Generalized Arc Consistency with Application to MaxCSP. AI 2002: 104-118 - 2000
- [c5]Michael C. Horsch, William S. Havens:
An Empirical Study of Probabilistic Arc Consistency. CP 2000: 525-530 - [c4]Michael C. Horsch, William S. Havens:
Probabilistic Arc Consistency: A Connection between Constraint Reasoning and Probabilistic Reasoning. UAI 2000: 282-290
1990 – 1999
- 1999
- [c3]Michael C. Horsch, David L. Poole:
Estimating the Value of Computation in Flexible Information Refinement. UAI 1999: 297-304 - 1998
- [c2]Michael C. Horsch, David L. Poole:
An Anytime Algorithm for Decision Making under Uncertainty. UAI 1998: 246-255 - 1996
- [c1]Michael C. Horsch, David L. Poole:
Flexible Policy Construction by Information Refinement. UAI 1996: 315-324
Coauthor Index
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