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BIBM
2010
IEEE
139views Bioinformatics» more  BIBM 2010»
14 years 7 months ago
Scalable, updatable predictive models for sequence data
The emergence of data rich domains has led to an exponential growth in the size and number of data repositories, offering exciting opportunities to learn from the data using machin...
Neeraj Koul, Ngot Bui, Vasant Honavar
CHI
2008
ACM
15 years 10 months ago
CueFlik: interactive concept learning in image search
Web image search is difficult in part because a handful of keywords are generally insufficient for characterizing the visual properties of an image. Popular engines have begun to ...
James Fogarty, Desney S. Tan, Ashish Kapoor, Simon...
ISPASS
2009
IEEE
15 years 4 months ago
Lonestar: A suite of parallel irregular programs
Until recently, parallel programming has largely focused on the exploitation of data-parallelism in dense matrix programs. However, many important application domains, including m...
Milind Kulkarni, Martin Burtscher, Calin Cascaval,...
ICML
1996
IEEE
15 years 10 months ago
Learning Evaluation Functions for Large Acyclic Domains
Some of the most successful recent applications of reinforcement learning have used neural networks and the TD algorithm to learn evaluation functions. In this paper, we examine t...
Justin A. Boyan, Andrew W. Moore
GECCO
2007
Springer
194views Optimization» more  GECCO 2007»
15 years 4 months ago
Hybrid coevolutionary algorithms vs. SVM algorithms
As a learning method support vector machine is regarded as one of the best classifiers with a strong mathematical foundation. On the other hand, evolutionary computational techniq...
Rui Li, Bir Bhanu, Krzysztof Krawiec