Cooled and Relaxed Survey Propagation for MRFs (2008)
Chieu, Hai Leong, Lee, Wee Sun, Teh, Yee Whye
We describe a new algorithm, Relaxed Survey Propagation (RSP), for finding MAP configurations in Markov random fields. We compare its performance with state-of-the-art algorithms including the...
Finite Energy Survey Propagation for Constraint Satisfaction Problems (2007)
The Survey Propagation (SP) algorithm [1] has recently been shown to work well in the hard region for random K-SAT problems. SP has its origins in sophisticated arguments in statistical physics, and...
Finite Energy Survey Propagation for Constraint Satisfaction Problems (2007)
The Survey Propagation (SP) algorithm [1] has recently been shown to work well in the hard region for random K-SAT problems. SP has its origins in sophisticated arguments in statistical physics, and...
Activity Recognition from Physiological Data using Conditional Random Fields (2005)
Chieu, Hai Leong, Lee, Wee Sun, Kaelbling, Leslie P.
We describe the application of conditional random fields (CRF) to physiological data modeling for the application of activity recognition. We use the data provided by the Physiological Data Modeling...
Activity Recognition from Physiological Data using Conditional Random Fields (2005)
Chieu, Hai Leong, Lee, Wee Sun, Kaelbling, Leslie P.
We describe the application of conditional random fields (CRF) to physiological data modeling for the application of activity recognition. We use the data provided by the Physiological Data Modeling...
Named Entity Recognition: A Maximum Entropy Approach (2004)
This paper presents a maximum entropy-based named entity recognizer (NER). It differs from previous machine learning-based NERs in that it uses information from the whole document to classify each...
Named Entity Recognition with a Maximum Entropy Approach (2004)
This paper presents a maximum entropy approach to the NER task, where NER not only made use of local context within a sentence, but also made use of other occurrences of each word within the same...
Closing the Gap: Learning-Based Information Extraction Rivaling (2003)
Hai Leong Chieu, Hwee Tou Ng, Yoong Keok Lee
to the scenario template task of information extraction, where information filling one template could come from multiple sentences. When tested on the MUC4 task, our learning approach achieves...
Named Entity Recognition with a Maximum Entropy Approach (2003)
This paper presents a maximum entropy approach to the NER task, where NER not only made use of local context within a sentence, but also made use of other occurrences of each word within the same...
Closing the Gap: Learning-Based Information Extraction Rivaling (2003)
Hai Leong Chieu, Hwee Tou Ng, Yoong Keok Lee
to the scenario template task of information extraction, where information filling one template could come from multiple sentences. When tested on the MUC4 task, our learning approach achieves...
Closing the Gap: Learning-Based Information Extraction Rivaling (2003)
Hai Leong Chieu, Hwee Tou Ng, Yoong Keok Lee
to the scenario template task of information extraction, where information filling one template could come from multiple sentences. When tested on the MUC4 task, our learning approach achieves...
Named Entity Recognition with a Maximum Entropy Approach (2003)
This paper presents a maximum entropy approach to the NER task, where NER not only made use of local context within a sentence, but also made use of other occurrences of each word within the same...
Teaching a Weaker Classifier: (2002)
This paper describes how a machinelearning named entity recognizer (NER) on upper case text can be improved by using a mixed case NER and some unlabeled text. The mixed case NER can be used to tag...
Named Entity Recognition: A Maximum Entropy Approach Using Global Information (2002)
This paper presents a maximum entropy-based named entity recognizer (NER). It differs from previous machine learning-based NERs in that it uses information from the whole document to classify each...
Bayesian Online Classifiers for Text Classification and Filtering (2002)
Kian Ming, Adam Chai, Hwee Tou Ng, Hai Leong Chieu
This paper explores the use of Bayesian online classifiers to classify text documents. Empirical results indicate that these classifiers are comparable with the best text classification systems....
A Maximum Entropy Approach to Information Extraction from Semi-Structured and Free Text (2002)
In this paper, we present a classification-based approach towards single-slot as well as multi-slot information extraction (IE). For single-slot IE, we worked on the domain of Seminar Announcements,...
Teaching a Weaker Classifier: Named Entity Recognition on Upper Case Text (2002)
This paper describes how a machinelearning named entity recognizer (NER) on upper case text can be improved by using a mixed case NER and some unlabeled text. The mixed case NER can be used to tag...