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AIL
2005
104views more  AIL 2005»
13 years 7 months ago
Argument Based Machine Learning Applied to Law
In this paper we discuss the application of a new machine learning approach - Argument Based Machine Learning - to the legal domain. An experiment using a dataset which has also be...
Martin Mozina, Jure Zabkar, Trevor J. M. Bench-Cap...
EUROGP
2009
Springer
132views Optimization» more  EUROGP 2009»
14 years 2 months ago
A Statistical Learning Perspective of Genetic Programming
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in GP from the perspec...
Nur Merve Amil, Nicolas Bredeche, Christian Gagn&e...
DMIN
2009
132views Data Mining» more  DMIN 2009»
13 years 5 months ago
Understanding Support Vector Machine Classifications via a Recommender System-Like Approach
Support vector machines are a valuable tool for making classifications, but their black-box nature means that they lack the natural explanatory value that many other classifiers po...
David Barbella, Sami Benzaid, Janara M. Christense...
JMLR
2012
11 years 9 months ago
Learning Low-order Models for Enforcing High-order Statistics
Models such as pairwise conditional random fields (CRFs) are extremely popular in computer vision and various other machine learning disciplines. However, they have limited expre...
Patrick Pletscher, Pushmeet Kohli
UAI
1996
13 years 8 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon