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AAAI
2008
15 years 8 months ago
Zero-data Learning of New Tasks
We introduce the problem of zero-data learning, where a model must generalize to classes or tasks for which no training data are available and only a description of the classes or...
Hugo Larochelle, Dumitru Erhan, Yoshua Bengio
AIPS
2010
15 years 6 months ago
Iterative Learning of Weighted Rule Sets for Greedy Search
Greedy search is commonly used in an attempt to generate solutions quickly at the expense of completeness and optimality. In this work, we consider learning sets of weighted actio...
Yuehua Xu, Alan Fern, Sung Wook Yoon
KDD
2012
ACM
187views Data Mining» more  KDD 2012»
13 years 9 months ago
Online learning to diversify from implicit feedback
In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
Karthik Raman, Pannaga Shivaswamy, Thorsten Joachi...
BMCBI
2004
190views more  BMCBI 2004»
15 years 6 months ago
RAG: RNA-As-Graphs web resource
Background: The proliferation of structural and functional studies of RNA has revealed an increasing range of RNA's structural repertoire. Toward the objective of systematic ...
Daniela Fera, Namhee Kim, Nahum Shiffeldrim, Julie...
ICML
2004
IEEE
16 years 7 months ago
Semi-supervised learning using randomized mincuts
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
Avrim Blum, John D. Lafferty, Mugizi Robert Rweban...