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OOPSLA
2004
Springer
14 years 2 months ago
Event-driven programming facilitates learning standard programming concepts
We have designed a CS 1 course that integrates event-driven programming from the very start. In [2] we argued that event-driven programming is simple enough for CS 1 when introduc...
Kim B. Bruce, Andrea Pohoreckyj Danyluk
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
14 years 9 months ago
Machine learning for online query relaxation
In this paper we provide a fast, data-driven solution to the failing query problem: given a query that returns an empty answer, how can one relax the query's constraints so t...
Ion Muslea
JMLR
2010
192views more  JMLR 2010»
13 years 4 months ago
Efficient Learning of Deep Boltzmann Machines
We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
Ruslan Salakhutdinov, Hugo Larochelle
JMLR
2010
165views more  JMLR 2010»
13 years 4 months ago
Learning with Blocks: Composite Likelihood and Contrastive Divergence
Composite likelihood methods provide a wide spectrum of computationally efficient techniques for statistical tasks such as parameter estimation and model selection. In this paper,...
Arthur Asuncion, Qiang Liu, Alexander T. Ihler, Pa...
BMCBI
2007
113views more  BMCBI 2007»
13 years 9 months ago
Learning biophysically-motivated parameters for alpha helix prediction
Background: Our goal is to develop a state-of-the-art protein secondary structure predictor, with an intuitive and biophysically-motivated energy model. We treat structure predict...
Blaise Gassend, Charles W. O'Donnell, William Thie...