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PAMI
2010
249views more  PAMI 2010»
13 years 2 months ago
Object Detection with Discriminatively Trained Part-Based Models
—We describe an object detection system based on mixtures of multiscale deformable part models. Our system is able to represent highly variable object classes and achieves state-...
Pedro F. Felzenszwalb, Ross B. Girshick, David A. ...
CI
2006
69views more  CI 2006»
13 years 4 months ago
The Importance of Neutral Examples for Learning Sentiment
Most research on learning to identify sentiment ignores "neutral" examples, learning only from examples of significant (positive or negative) polarity. We show that it i...
Moshe Koppel, Jonathan Schler
CATS
2006
13 years 5 months ago
Learnability of Term Rewrite Systems from Positive Examples
Learning from examples is an important characteristic feature of intelligence in both natural and artificial intelligent agents. In this paper, we study learnability of term rewri...
M. R. K. Krishna Rao
CIA
2006
Springer
13 years 8 months ago
Improving Example Selection for Agents Teaching Ontology Concepts
Abstract. We present a method to improve the positive examples selection by teaching agents in a multi-agent system in which a team of agent peers teach concepts to a learning agen...
Mohsen Afsharchi, Behrouz H. Far
ECML
1998
Springer
13 years 8 months ago
Predicate Invention and Learning from Positive Examples Only
Previous bias shift approaches to predicate invention are not applicable to learning from positive examples only, if a complete hypothesis can be found in the given language, as ne...
Henrik Boström
ALT
1998
Springer
13 years 8 months ago
PAC Learning from Positive Statistical Queries
Learning from positive examples occurs very frequently in natural learning. The PAC learning model of Valiant takes many features of natural learning into account, but in most case...
François Denis
ILP
2001
Springer
13 years 8 months ago
Learning Functions from Imperfect Positive Data
The Bayesian framework of learning from positive noise-free examples derived by Muggleton [12] is extended to learning functional hypotheses from positive examples containing norma...
Filip Zelezný
ECML
2003
Springer
13 years 9 months ago
Leveraging Lexical Semantics to Infer Context-Free Grammars
Context-free grammars cannot be identified in the limit from positive examples (Gold, 1967), yet natural language grammars are more powerful than context-free grammars and humans ...
Tim Oates, Tom Armstrong, Justin Harris, Mark Nejm...
CIVR
2003
Springer
126views Image Analysis» more  CIVR 2003»
13 years 9 months ago
Learning in Region-Based Image Retrieval
In this paper, several effective learning algorithms using global image representations are adjusted and introduced to region-based image retrieval (RBIR). First, the query point m...
Feng Jing, Mingjing Li, Lei Zhang, HongJiang Zhang...
ECML
2005
Springer
13 years 9 months ago
Learning from Positive and Unlabeled Examples with Different Data Distributions
Abstract. We study the problem of learning from positive and unlabeled examples. Although several techniques exist for dealing with this problem, they all assume that positive exam...
Xiaoli Li, Bing Liu