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» Efficient Learning of Semi-structured Data from Queries
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PKDD
2010
Springer
164views Data Mining» more  PKDD 2010»
15 years 3 months ago
Complexity Bounds for Batch Active Learning in Classification
Active learning [1] is a branch of Machine Learning in which the learning algorithm, instead of being directly provided with pairs of problem instances and their solutions (their l...
Philippe Rolet, Olivier Teytaud
ALT
2009
Springer
16 years 2 months ago
Average-Case Active Learning with Costs
Abstract. We analyze the expected cost of a greedy active learning algorithm. Our analysis extends previous work to a more general setting in which different queries have differe...
Andrew Guillory, Jeff A. Bilmes
236
Voted

Publication
244views
17 years 4 months ago
Phenomenon-aware Stream Query Processing
Spatio-temporal data streams that are generated from mobile stream sources (e.g., mobile sensors) experience similar environmental conditions that result in distinct phenomena. Sev...
M. H. Ali, Mohamed F. Mokbel, Walid G. Aref
IJAR
2006
89views more  IJAR 2006»
15 years 5 months ago
Learning probabilistic decision graphs
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Manfred Jaeger, Jens D. Nielsen, Tomi Silander
VLDB
2001
ACM
190views Database» more  VLDB 2001»
15 years 9 months ago
LEO - DB2's LEarning Optimizer
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...