SVM learning with the Schur-Hadamard inner product for graphs

Neurocomputing

Volumn 64, Issue 1-4 SPEC. ISS., 2005, Pages 93-105

  Jain, Brijnesh J ^a   Geibel, Peter ^a   Wysotzki, Fritz ^a  

^a TECHNISCHE UNIVERSITÄT BERLIN   (Germany)

Author keywords

Graph kernel; Hopfield network; Recurrent network; Schur Hadamard product; Support vector machine

Indexed keywords

APPROXIMATION THEORY; GRAPH THEORY; LEARNING SYSTEMS; MAPPING; MATRIX ALGEBRA; RECURRENT NEURAL NETWORKS;

KERNEL MATRICES; SCHUR-HADAMARD INNER PRODUCTS; SUPPORT VECTOR LEARNING; SUPPORT VECTOR MACHINES (SVM);

VECTORS;

AROMATIC NITRO COMPOUND;

ACCURACY; ALGORITHM; ANALYTICAL ERROR; ANALYTICAL PARAMETERS; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOTRANSFORMATION; CARCINOGENICITY; COMPUTER GRAPHICS; COMPUTER MODEL; COMPUTER SIMULATION; DATA BASE; GENETIC SIMILARITY; GEOMETRY; INFORMATION PROCESSING; LEARNING; MENTAL TASK; MUTAGENICITY; ONLINE SYSTEM; PRIORITY JOURNAL; STRUCTURAL BIOINFORMATICS; WORD RECOGNITION;

EID: 15844372451     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2004.11.011     Document Type: Article

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