Generalized belief propagation (GBP) has proven to be a promising technique for approximate inference tasks in AI and machine learning. However, the choice of a good set of cluste...
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...
We develop a normative theory of interaction-negotiation in particular--among self-interested computationally limited agents where computational actions are game-theoretically tre...
The CPS transformation dates back to the early 1970's, where it arose as a technique to represent the control flow of programs in -calculus based programming languages as -te...
We present an interactive technique for the registration of captured images of elastic and rigid body parts in which the user is given flexible control over material specific de...