Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
We consider the task of reinforcement learning with linear value function approximation. Temporal difference algorithms, and in particular the Least-Squares Temporal Difference (L...
There are well known algorithms for learning the structure of directed and undirected graphical models from data, but nearly all assume that the data consists of a single i.i.d. s...
We consider the problem of learning a similarity function from a set of positive equivalence constraints, i.e. 'similar' point pairs. We define the similarity in informa...
Capturing the context of a user's query from the previous queries and clicks in the same session may help understand the user's information need. A context-aware approac...