Sparse Functional Relevance Learning in Generalized Learning Vector Quantization

被引：0
|
作者：
Villmann, Thomas [1 ]
Kaestner, Marika [1 ]
机构：
[1] Univ Appl Sci Mittweida, Dep Math Nat & Comp Sci, Tech Pl 17, D-09648 Mittweida, Germany
来源：
ADVANCES IN SELF-ORGANIZING MAPS, WSOM 2011 | 2011年 / 6731卷
关键词：
functional vector quantization; relevance learning; information theory; SELECTION;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We propose a functional relevance learning for learning vector quantization of functional data. The relevance profile is taken as a superposition of a set of basis functions depending on only a few parameters compared to standard relevance learning. Moreover, the sparsity of the superposition is achieved by an entropy based penalty function forcing sparsity.
引用
下载
收藏
页码：79 / 89
页数：11
相关论文
共 50 条
  • [31] Alternative learning vector quantization
    Wu, KL
    Yang, MS
    PATTERN RECOGNITION, 2006, 39 (03) : 351 - 362
  • [32] Learning Vector Quantization networks
    Matera, F
    SUBSTANCE USE & MISUSE, 1998, 33 (02) : 271 - 282
  • [33] Regression Learning Vector Quantization
    Grbovic, Mihajlo
    Vucetic, Slobodan
    2009 9TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, 2009, : 788 - 793
  • [34] Learning vector quantization: A review
    Karayiannis, Nicolaos B.
    International Journal of Smart Engineering System Design, 1997, 1 (01): : 33 - 58
  • [35] Soft learning vector quantization
    Seo, S
    Obermayer, K
    NEURAL COMPUTATION, 2003, 15 (07) : 1589 - 1604
  • [36] Generalized Learning Graph Quantization
    Jain, Brijnesh J.
    Obermayer, Klaus
    GRAPH-BASED REPRESENTATIONS IN PATTERN RECOGNITION, 2011, 6658 : 122 - 131
  • [37] Admire LVQ-Adaptive Distance Measures in Relevance Learning Vector Quantization
    Biehl, Michael
    KUNSTLICHE INTELLIGENZ, 2012, 26 (04): : 391 - 395
  • [38] Comparison of relevance learning vector quantization with other metric adaptive classification methods
    Villmann, Th.
    Schleif, F.
    Hammer, B.
    NEURAL NETWORKS, 2006, 19 (05) : 610 - 622
  • [39] Generalized Learning Vector Quantization for Classification in Randomized Neural Networks and Hyperdimensional Computing
    Diao, Cameron
    Kleyko, Denis
    Rabaey, Jan M.
    Olshausen, Bruno A.
    2021 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2021,
  • [40] Cyber-Physical Security with RF Fingerprint Classification through Distance Measure Extensions of Generalized Relevance Learning Vector Quantization
    Bihl, Trevor J.
    Paciencia, Todd J.
    Bauer, Kenneth W., Jr.
    Temple, Michael A.
    SECURITY AND COMMUNICATION NETWORKS, 2020, 2020
12345