Deciding what to sense is a crucial task, made harder by dependencies and by a nonadditive utility function. We develop approximation algorithms for selecting an optimal set of me...
We consider the iterated belief change that occurs following an alternating sequence of actions and observations. At each instant, an agent has some beliefs about the action that ...
Abstract. We present experimental results about learning function values (i.e. Bellman values) in stochastic dynamic programming (SDP). All results come from openDP (opendp.sourcef...
The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
Francis R. Bach, Romain Thibaux, Michael I. Jordan
Depth reconstruction or acquisition with a 3-D camera results in a video sequence where each pixel of a frame is annotated with a depth value. We propose an approach to combine th...
Fabian Ernst, Cornelius W. A. M. van Overveld, Pio...