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» The Use of Classifiers in Sequential Inference
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IJCNN
2006
IEEE
14 years 1 months ago
Rao-Blackwellized Particle Filtering for Sequential Speech Enhancement
— In this paper we present a method of sequential speech enhancement, where we infer clean speech signal using a Rao-Blackwellized particle filter (RBPF), given a noisecontamina...
Sunho Park, Seungjin Choi
EMNLP
2007
13 years 9 months ago
LEDIR: An Unsupervised Algorithm for Learning Directionality of Inference Rules
Semantic inference is a core component of many natural language applications. In response, several researchers have developed algorithms for automatically learning inference rules...
Rahul Bhagat, Patrick Pantel, Eduard H. Hovy
CVPR
2008
IEEE
14 years 9 months ago
Semantic-based indexing of fetal anatomies from 3-D ultrasound data using global/semi-local context and sequential sampling
The use of 3-D ultrasound data has several advantages over 2-D ultrasound for fetal biometric measurements, such as considerable decrease in the examination time, possibility of p...
Gustavo Carneiro, Fernando Amat, Bogdan Georgescu,...
ICML
2007
IEEE
14 years 8 months ago
CarpeDiem: an algorithm for the fast evaluation of SSL classifiers
In this paper we present a novel algorithm, CarpeDiem. It significantly improves on the time complexity of Viterbi algorithm, preserving the optimality of the result. This fact ha...
Roberto Esposito, Daniele P. Radicioni
SDM
2008
SIAM
130views Data Mining» more  SDM 2008»
13 years 9 months ago
Mining Sequence Classifiers for Early Prediction
Supervised learning on sequence data, also known as sequence classification, has been well recognized as an important data mining task with many significant applications. Since te...
Zhengzheng Xing, Jian Pei, Guozhu Dong, Philip S. ...