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» Learning Classifiers from Semantically Heterogeneous Data
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ACL
2010
14 years 8 months ago
Experiments in Graph-Based Semi-Supervised Learning Methods for Class-Instance Acquisition
Graph-based semi-supervised learning (SSL) algorithms have been successfully used to extract class-instance pairs from large unstructured and structured text collections. However,...
Partha Pratim Talukdar, Fernando Pereira
CIRA
2007
IEEE
152views Robotics» more  CIRA 2007»
15 years 4 months ago
Probabilistic Semantic Mapping with a Virtual Sensor for Building/Nature detection
Abstract— In human-robot communication it is often important to relate robot sensor readings to concepts used by humans. We believe that access to semantic maps will make it poss...
Martin Persson, Tom Duckett, Christoffer Valgren, ...
ICASSP
2011
IEEE
14 years 1 months ago
A regularization framework for mobile social network analysis
Mobile phone data provides rich dynamic information on human activities in social network analysis. In this paper, we represent data from two different modalities as a graph and f...
Xiaowen Dong, Pascal Frossard, Pierre Vandergheyns...
AAAI
2006
14 years 11 months ago
Boosting Expert Ensembles for Rapid Concept Recall
Many learning tasks in adversarial domains tend to be highly dependent on the opponent. Predefined strategies optimized for play against a specific opponent are not likely to succ...
Achim Rettinger, Martin Zinkevich, Michael H. Bowl...
COLING
2008
14 years 11 months ago
A Uniform Approach to Analogies, Synonyms, Antonyms, and Associations
Recognizing analogies, synonyms, antonyms, and associations appear to be four distinct tasks, requiring distinct NLP algorithms. In the past, the four tasks have been treated inde...
Peter D. Turney