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» Learning on the Test Data: Leveraging Unseen Features
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ICMCS
2007
IEEE
133views Multimedia» more  ICMCS 2007»
14 years 3 months ago
Data Modeling Strategies for Imbalanced Learning in Visual Search
In this paper we examine a novel approach to the difficult problem of querying video databases using visual topics with few examples. Typically with visual topics, the examples a...
Jelena Tesic, Apostol Natsev, Lexing Xie, John R. ...
MLCW
2005
Springer
14 years 2 months ago
Learning Textual Entailment on a Distance Feature Space
Textual Entailment recognition is a very difficult task as it is one of the fundamental problems in any semantic theory of natural language. As in many other NLP tasks, Machine Lea...
Maria Teresa Pazienza, Marco Pennacchiotti, Fabio ...
CVPR
2010
IEEE
14 years 5 months ago
Unsupervised Learning of Invariant Features Using Video
We present an algorithm that learns invariant features from real data in an entirely unsupervised fashion. The principal benefit of our method is that it can be applied without hu...
David Stavens, Sebastian Thrun
HIS
2007
13 years 10 months ago
Pareto-based Multi-Objective Machine Learning
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...
Yaochu Jin
GPEM
2002
104views more  GPEM 2002»
13 years 9 months ago
Genetic Programming-based Construction of Features for Machine Learning and Knowledge Discovery Tasks
In this paper we use genetic programming for changing the representation of the input data for machine learners. In particular, the topic of interest here is feature construction i...
Krzysztof Krawiec