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» On regularization algorithms in learning theory
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FUIN
2008
108views more  FUIN 2008»
15 years 3 months ago
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques
Causal relations are present in many application domains. Causal Probabilistic Logic (CP-logic) is a probabilistic modeling language that is especially designed to express such rel...
Wannes Meert, Jan Struyf, Hendrik Blockeel
SIGMOD
2008
ACM
123views Database» more  SIGMOD 2008»
16 years 4 months ago
SchemaScope: a system for inferring and cleaning XML schemas
We present SchemaScope, a system to derive Document Type Definitions and XML Schemas from corpora of sample XML documents. Tools are provided to visualize, clean, and refine exist...
Geert Jan Bex, Frank Neven, Stijn Vansummeren
FOCM
2008
140views more  FOCM 2008»
15 years 4 months ago
Online Gradient Descent Learning Algorithms
This paper considers the least-square online gradient descent algorithm in a reproducing kernel Hilbert space (RKHS) without explicit regularization. We present a novel capacity i...
Yiming Ying, Massimiliano Pontil
SIGIR
2011
ACM
14 years 7 months ago
Learning search tasks in queries and web pages via graph regularization
As the Internet grows explosively, search engines play a more and more important role for users in effectively accessing online information. Recently, it has been recognized that ...
Ming Ji, Jun Yan, Siyu Gu, Jiawei Han, Xiaofei He,...
GECCO
2000
Springer
114views Optimization» more  GECCO 2000»
15 years 8 months ago
Intelligent Recombination Using Individual Learning in a Collective Learning Genetic Algorithm
This paper introduces a new collective learning genetic algorithm (CLGA) which employs individual learning to do intelligent recombination based on a cooperative exchange of knowl...
Terry P. Riopka, Peter Bock