Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
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...
This paper describes how heterogeneous data sources captured in the SignCom project may be used for the analysis and synthesis of French Sign Language (LSF) utterances. The captur...
Exponential algorithms, i.e. algorithms of complexity O(cn ) for some c > 1, seem to be unavoidable in the case of NP-complete problems (unless P=NP), especially if the problem ...
Virtually every commercial query optimizer chooses the best plan for a query using a cost model that relies heavily on accurate cardinality estimation. Cardinality estimation erro...
Volker Markl, Vijayshankar Raman, David E. Simmen,...