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ECML
2007
Springer
15 years 10 months ago
Probabilistic Explanation Based Learning
Abstract. Explanation based learning produces generalized explanations from examples. These explanations are typically built in a deductive manner and they aim to capture the essen...
Angelika Kimmig, Luc De Raedt, Hannu Toivonen
NECO
2007
107views more  NECO 2007»
15 years 3 months ago
Training a Support Vector Machine in the Primal
Most literature on Support Vector Machines (SVMs) concentrate on the dual optimization problem. In this paper, we would like to point out that the primal problem can also be solve...
Olivier Chapelle
ILP
2007
Springer
15 years 10 months ago
Beyond Prediction: Directions for Probabilistic and Relational Learning
Research over the past several decades in learning logical and probabilistic models has greatly increased the range of phenomena that machine learning can address. Recent work has ...
David D. Jensen
VLSID
2007
IEEE
97views VLSI» more  VLSID 2007»
15 years 10 months ago
Embedded Support Vector Machine : Architectural Enhancements and Evaluation
In recent years, research and development in the field of machine learning and classification techniques have gained paramount importance. The future generation of intelligent e...
Soumyajit Dey, Monu Kedia, Niket Agarwal, Anupam B...
ML
2010
ACM
181views Machine Learning» more  ML 2010»
15 years 2 months ago
Decomposing the tensor kernel support vector machine for neuroscience data with structured labels
Abstract The tensor kernel has been used across the machine learning literature for a number of purposes and applications, due to its ability to incorporate samples from multiple s...
David R. Hardoon, John Shawe-Taylor