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» Optimizing Local Probability Models for Statistical Parsing
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ACL
2006
13 years 9 months ago
Trimming CFG Parse Trees for Sentence Compression Using Machine Learning Approaches
Sentence compression is a task of creating a short grammatical sentence by removing extraneous words or phrases from an original sentence while preserving its meaning. Existing me...
Yuya Unno, Takashi Ninomiya, Yusuke Miyao, Jun-ich...
BMCBI
2007
130views more  BMCBI 2007»
13 years 7 months ago
HMM-ModE - Improved classification using profile hidden Markov models by optimising the discrimination threshold and modifying e
Background: Profile Hidden Markov Models (HMM) are statistical representations of protein families derived from patterns of sequence conservation in multiple alignments and have b...
Prashant K. Srivastava, Dhwani K. Desai, Soumyadee...
IJRR
2010
185views more  IJRR 2010»
13 years 6 months ago
FISST-SLAM: Finite Set Statistical Approach to Simultaneous Localization and Mapping
The solution to the problem of mapping an environment and at the same time using this map to localize (the simultaneous localization and mapping, SLAM, problem) is a key prerequis...
Bharath Kalyan, K. W. Lee, W. Sardha Wijesoma
TIT
2008
118views more  TIT 2008»
13 years 6 months ago
Discrete-Input Two-Dimensional Gaussian Channels With Memory: Estimation and Information Rates Via Graphical Models and Statisti
Abstract--Discrete-input two-dimensional (2-D) Gaussian channels with memory represent an important class of systems, which appears extensively in communications and storage. In sp...
Ori Shental, Noam Shental, Shlomo Shamai, Ido Kant...
CORR
2010
Springer
95views Education» more  CORR 2010»
13 years 7 months ago
Statistical Compressive Sensing of Gaussian Mixture Models
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...
Guoshen Yu, Guillermo Sapiro