We describe the results of large-scale experiments with algorithms for unsupervised improvement of recognition of book-images using fully automatic mutual-entropy-based model adap...
This paper extends the framework of dynamic influence diagrams (DIDs) to the multi-agent setting. DIDs are computational representations of the Partially Observable Markov Decisio...
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
The reflection of light from surfaces is a fundamental problem in computer graphics. Although many reflection models have been proposed, few take into account the wave nature of...
This paper presents a non-parallel training algorithm for voice conversion based on feature transform Gaussian mixture model (FTGMM), which is a mixture model of joint density spa...