AUC-maximized deep convolutional neural fields for protein sequence labeling

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 9852 LNAI, Issue , 2016, Pages 1-16

  Wang, Sheng ^a,b   Sun, Siqi ^a   Xu, Jinbo ^a  

^a TOYOTA TECHNOLOGICAL INSTITUTE AT CHICAGO   (United States)

^b UNIVERSITY OF CHICAGO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CONVOLUTION; FORECASTING; LEARNING ALGORITHMS; MAXIMUM LIKELIHOOD; NEURAL NETWORKS; RANDOM PROCESSES;

AREA UNDER THE ROC CURVE; CONDITIONAL RANDOM FIELD; CONVOLUTIONAL NEURAL NETWORK; DISORDER PREDICTIONS; POLYNOMIAL FUNCTIONS; SECONDARY STRUCTURE PREDICTION; SOLVENT ACCESSIBILITY; TRAINING ALGORITHMS;

LEARNING SYSTEMS;

EID: 84988556622     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-46227-1_1     Document Type: Conference Paper

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