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» On learning with dissimilarity functions
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ECML
2006
Springer
14 years 27 days ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...
JMLR
2010
186views more  JMLR 2010»
13 years 4 months ago
Dimensionality Estimation, Manifold Learning and Function Approximation using Tensor Voting
We address instance-based learning from a perceptual organization standpoint and present methods for dimensionality estimation, manifold learning and function approximation. Under...
Philippos Mordohai, Gérard G. Medioni
BMCBI
2008
228views more  BMCBI 2008»
13 years 9 months ago
Adaptive diffusion kernel learning from biological networks for protein function prediction
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Liang Sun, Shuiwang Ji, Jieping Ye
ECML
2000
Springer
14 years 1 months ago
Metric-Based Inductive Learning Using Semantic Height Functions
In the present paper we propose a consistent way to integrate syntactical least general generalizations (lgg's) with semantic evaluation of the hypotheses. For this purpose we...
Zdravko Markov, Ivo Marinchev
AAAI
1992
13 years 10 months ago
Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning
It is often useful for a robot to construct a spatial representation of its environment from experiments and observations, in other words, to learn a map of its environment by exp...
Thomas Dean, Dana Angluin, Kenneth Basye, Sean P. ...