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COLING
1992
13 years 8 months ago
Syntactic Ambiguity Resolution Using A Discrimination and Robustness Oriented Adaptive Learning Algorithm
In this paper, a discrimination and robusmess oriented adaptive learning procedure is proposed to deal with the task of syntactic ambiguity resolution. Owing to the problem of ins...
Tung-Hui Chiang, Yi-Chung Lin, Keh-Yih Su
ACL
2007
13 years 9 months ago
Sparse Information Extraction: Unsupervised Language Models to the Rescue
Even in a massive corpus such as the Web, a substantial fraction of extractions appear infrequently. This paper shows how to assess the correctness of sparse extractions by utiliz...
Doug Downey, Stefan Schoenmackers, Oren Etzioni
ICDM
2007
IEEE
122views Data Mining» more  ICDM 2007»
14 years 1 months ago
Noise Modeling with Associative Corruption Rules
This paper presents an active learning approach to the problem of systematic noise inference and noise elimination, specifically the inference of Associated Corruption (AC) rules...
Yan Zhang, Xindong Wu
EMNLP
2008
13 years 9 months ago
Latent-Variable Modeling of String Transductions with Finite-State Methods
String-to-string transduction is a central problem in computational linguistics and natural language processing. It occurs in tasks as diverse as name transliteration, spelling co...
Markus Dreyer, Jason Smith, Jason Eisner
ICRA
2010
IEEE
137views Robotics» more  ICRA 2010»
13 years 6 months ago
Robot reinforcement learning using EEG-based reward signals
Abstract— Reinforcement learning algorithms have been successfully applied in robotics to learn how to solve tasks based on reward signals obtained during task execution. These r...
Iñaki Iturrate, Luis Montesano, Javier Ming...