This paper uses Factored Latent Analysis (FLA) to learn a factorized, segmental representation for observations of tracked objects over time. Factored Latent Analysis is latent cl...
We propose a new semantics for modeling belief, mixing conncepts from qualitative probabilistic and classical possible world accounts. Our belief structures are coherent sets of q...
Latent class models (LCM) represent the high dimensional data in a smaller dimensional space in terms of latent variables. They are able to automatically discover the patterns from...
Semantic structures for belief revision are proposed. We start with one-stage revision structures that generalize the notion of choice function from rational choice theory. A corr...
Existing approaches to multi-view learning are particularly effective when the views are either independent (i.e, multi-kernel approaches) or fully dependent (i.e., shared latent ...
Mathieu Salzmann, Carl Henrik Ek, Raquel Urtasun, ...