We cast model-free reinforcement learning as the problem of maximizing the likelihood of a probabilistic mixture model via sampling, addressing both the infinite and finite horizo...
Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, i.e. a database of available user preferences. In this ...
Combining the output from multiple retrieval sources over the same document collection is of great importance to a number of retrieval tasks such as multimedia retrieval, web retr...
—This paper addresses the issue of matching rigid and articulated shapes through probabilistic point registration. The problem is recast into a missing data framework where unkno...
Radu Horaud, Florence Forbes, Manuel Yguel, Guilla...
The ability to deal with uncertain information is becoming increasingly important for modern database applications. Whereas a conventional (certain) object is usually represented ...