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ICML
2010
IEEE
15 years 7 months ago
Online Learning for Group Lasso
We develop a novel online learning algorithm for the group lasso in order to efficiently find the important explanatory factors in a grouped manner. Different from traditional bat...
Haiqin Yang, Zenglin Xu, Irwin King, Michael R. Ly...
ICML
2010
IEEE
15 years 7 months ago
Learning Markov Logic Networks Using Structural Motifs
Markov logic networks (MLNs) use firstorder formulas to define features of Markov networks. Current MLN structure learners can only learn short clauses (4-5 literals) due to extre...
Stanley Kok, Pedro Domingos
ESEM
2010
ACM
15 years 6 months ago
A comprehensive characterization of NLP techniques for identifying equivalent requirements
Though very important in software engineering, linking artifacts of the same type (clone detection) or of different types (traceability recovery) is extremely tedious, error-prone...
Davide Falessi, Giovanni Cantone, Gerardo Canfora
SIGIR
2010
ACM
15 years 6 months ago
Learning to rank query reformulations
Query reformulation techniques based on query logs have recently proven to be effective for web queries. However, when initial queries have reasonably good quality, these techniqu...
Van Dang, Michael Bendersky, W. Bruce Croft
ICASSP
2010
IEEE
15 years 6 months ago
Summarization- and learning-based approaches to information distillation
Information distillation is the task that aims to extract relevant passages of text from massive volumes of textual and audio sources, given a query. In this paper, we investigate...
Boriska Toth, Dilek Hakkani-Tür, Sibel Yaman
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