Abstract. In preference learning, the algorithm observes pairwise relative judgments (preference) between items as training data for learning an ordering of all items. This is an i...
Interactively learning from a small sample of unlabeled examples is an enormously challenging task, one that often arises in vision applications. Relevance feedback and more recen...
ShyamSundar Rajaram, Charlie K. Dagli, Nemanja Pet...
We explore the utility of different types of topic models for retrieval purposes. Based on prior work, we describe several ways that topic models can be integrated into the retrie...
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,...
Most modern DBMS optimizers rely upon a cost model to choose the best query execution plan (QEP) for any given query. Cost estimates are heavily dependent upon the optimizer’s e...
Michael Stillger, Guy M. Lohman, Volker Markl, Mok...