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» On Kernel Methods for Relational Learning
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CVPR
2011
IEEE
14 years 10 months ago
What You Saw is Not What You Get: Domain Adaptation Using Asymmetric Kernel Transforms
In real-world applications, “what you saw” during training is often not “what you get” during deployment: the distribution and even the type and dimensionality of features...
Brian Kulis, Kate Saenko, Trevor Darrell
151
Voted
JMLR
2012
13 years 5 months ago
Sparse Additive Machine
We develop a high dimensional nonparametric classification method named sparse additive machine (SAM), which can be viewed as a functional version of support vector machine (SVM)...
Tuo Zhao, Han Liu
CVPR
2004
IEEE
15 years 6 months ago
Learning in Region-Based Image Retrieval with Generalized Support Vector Machines
Relevance feedback approaches based on support vector machine (SVM) learning have been applied to significantly improve retrieval performance in content-based image retrieval (CBI...
Iker Gondra, Douglas R. Heisterkamp
ICASSP
2011
IEEE
14 years 6 months ago
Probabilistic distance SVM with Hellinger-Exponential Kernel for sound event classification
This paper presents a novel method for sound event classification based on probabilistic distance SVM. The basic idea is to embed probabilistic distances into classical SVM to cl...
Tran Huy Dat, Haizhou Li
ECAI
2000
Springer
15 years 7 months ago
Lazy Propositionalisation for Relational Learning
A number of Inductive Logic Programming (ILP) systems have addressed the problem of learning First Order Logic (FOL) discriminant definitions by first reformulating the FOL lear...
Érick Alphonse, Céline Rouveirol