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AAAI
2000
13 years 9 months ago
Deliberation in Equilibrium: Bargaining in Computationally Complex Problems
We develop a normative theory of interaction-negotiation in particular--among self-interested computationally limited agents where computational actions are game-theoretically tre...
Kate Larson, Tuomas Sandholm
HYBRID
2000
Springer
14 years 2 days ago
A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models
Abstract. Switching linear dynamic systems (SLDS) attempt to describe a complex nonlinear dynamic system with a succession of linear models indexed by a switching variable. Unfortu...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham
PSB
2004
13 years 9 months ago
Modeling Cellular Processes with Variational Bayesian Cooperative Vector Quantizer
Gene expression of a cell is controlled by sophisticated cellular processes. The capability of inferring the states of these cellular processes would provide insight into the mech...
Xinghua Lu, Milos Hauskrecht, Roger S. Day
AAAI
2011
12 years 8 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
NECO
2007
127views more  NECO 2007»
13 years 8 months ago
Visual Recognition and Inference Using Dynamic Overcomplete Sparse Learning
We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and e...
Joseph F. Murray, Kenneth Kreutz-Delgado