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» On regularization algorithms in learning theory
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ICML
2008
IEEE
16 years 5 months ago
ManifoldBoost: stagewise function approximation for fully-, semi- and un-supervised learning
We introduce a boosting framework to solve a classification problem with added manifold and ambient regularization costs. It allows for a natural extension of boosting into both s...
Nicolas Loeff, David A. Forsyth, Deepak Ramachandr...
ICML
2004
IEEE
16 years 5 months ago
Communication complexity as a lower bound for learning in games
A fast-growing body of research in the AI and machine learning communities addresses learning in games, where there are multiple learners with different interests. This research a...
Vincent Conitzer, Tuomas Sandholm
146
Voted
EDBT
1990
ACM
108views Database» more  EDBT 1990»
15 years 9 months ago
Deductive Databases - Theory Meets Practice
Deductive Databases are coming of age with the emergence of efficient and easy to use systems that support queries, reasoning, and application development on databases through dec...
Carlo Zaniolo
STOC
2010
ACM
216views Algorithms» more  STOC 2010»
16 years 2 months ago
The HOM problem is decidable
We close affirmatively a question which has been open for long time: decidability of the HOM problem. The HOM problem consists in determining, given a tree homomorphism D and a re...
Guillem Godoy, Omer Giménez, Lander Ramos and Car...
NCA
2010
IEEE
15 years 3 months ago
Genetic algorithm-based training for semi-supervised SVM
The Support Vector Machine (SVM) is an interesting classifier with excellent power of generalization. In this paper, we consider applying the SVM to semi-supervised learning. We p...
Mathias M. Adankon, Mohamed Cheriet