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» The Foundations of Cost-Sensitive Learning
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ML
2010
ACM
193views Machine Learning» more  ML 2010»
13 years 2 months ago
On the eigenvectors of p-Laplacian
Spectral analysis approaches have been actively studied in machine learning and data mining areas, due to their generality, efficiency, and rich theoretical foundations. As a natur...
Dijun Luo, Heng Huang, Chris H. Q. Ding, Feiping N...
NIPS
1993
13 years 9 months ago
Convergence of Stochastic Iterative Dynamic Programming Algorithms
Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments. These algorithms,includ...
Tommi Jaakkola, Michael I. Jordan, Satinder P. Sin...
ICDE
2004
IEEE
117views Database» more  ICDE 2004»
14 years 9 months ago
Adapting a Generic Match Algorithm to Align Ontologies of Human Anatomy
The difficulty inherent in schema matching has led to the development of several generic match algorithms. This paper describes how we adapted general approaches to the specific t...
Peter Mork, Philip A. Bernstein
ICECCS
2009
IEEE
129views Hardware» more  ICECCS 2009»
14 years 2 months ago
CONNECT Challenges: Towards Emergent Connectors for Eternal Networked Systems
—The CONNECT European project that started in February 2009 aims at dropping the interoperability barrier faced by today’s distributed systems. It does so by adopting a revolut...
Valérie Issarny, Bernhard Steffen, Bengt Jo...
ICTIR
2009
Springer
14 years 2 months ago
Robust Word Similarity Estimation Using Perturbation Kernels
We introduce perturbation kernels, a new class of similarity measure for information retrieval that casts word similarity in terms of multi-task learning. Perturbation kernels mode...
Kevyn Collins-Thompson