• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 22 matches

• 2020
• 
  Xinjie Lan, Kenneth E. Barner:
  A Probabilistic Representation of Deep Learning for Improving The Information Theoretic Interpretability. CoRR abs/2010.14054 (2020)
• 2011
• 
  Huajin Tang, Haizhou Li:
  Information Theoretic Learning: Reny's Entropy and Kernel Perspectives (Principe, J.; 2010) [Book Review]. IEEE Comput. Intell. Mag. 6(3): 60-62 (2011)
• 
  Pascual Pérez-Paredes:
  Book review: Second Language Distance Learning and Teaching. Theoretical Perspectives and Didactic Ergonomics, BertinJean-Claude, GravéPatrick and Narcy-CombesJean-Paule. Hershey, PA: Information Science Reference, 2010. 258 pages. ISBN: 978-1-61520-707-7. Price: $180 US// €158.00. ReCALL 23(3): 311-315 (2011)
• 2010
• 
  Deisy Chelliah, S. Baskar, N. Ramaraj, J. Saravanan Koori, P. Jeevanandam:
  A novel information theoretic-interact algorithm (IT-IN) for feature selection using three machine learning algorithms. Expert Syst. Appl. 37(12): 7589-7597 (2010)
• 
  Ryotaro Kamimura:
  Information-theoretic enhancement learning and its application to visualization of self-organizing maps. Neurocomputing 73(13-15): 2642-2664 (2010)
• 
  Karthik Kuber, Chilukuri K. Mohan:
  Information theoretic fitness measures for learning classifier systems. GECCO (Companion) 2010: 1885-1892
• 
  Pablo A. Vera, Pablo A. Estévez, José Carlos Príncipe:
  Linear Projection Method Based on Information Theoretic Learning. ICANN (3) 2010: 178-187
• 
  Ryotaro Kamimura:
  Information-Theoretic Competitive and Cooperative Learning for Self-Organizing Maps. ICONIP (2) 2010: 423-430
• 
  Ricardo J. Bessa, Vladimiro Miranda, José C. Príncipe, Audun Botterud, Jun Wang:
  Information theoretic learning applied to wind power modeling. IJCNN 2010: 1-8
• 
  Ryotaro Kamimura:
  Explicit class structure produced by information-theoretic competitive and cooperative learning. NaBIC 2010: 628-633
• 
  Deniz Erdogmus, Seungju Han, Abhishek Singh:
  Algorithms for Entropy and Correntropy Adaptation with Applications to Linear Systems. Information Theoretic Learning 2010: 141-179
• 
  Deniz Erdogmus, Weifeng Liu:
  Adaptive Information Filtering with Error Entropy and Error Correntropy Criteria. Information Theoretic Learning 2010: 103-140
• 
  Deniz Erdogmus, Rodney Morejon, Weifeng Liu:
  Nonlinear Adaptive Filtering with MEE, MCC, and Applications. Information Theoretic Learning 2010: 181-218
• 
  Deniz Erdogmus, Dongxin Xu, Kenneth E. Hild II:
  Classification with EEC, Divergence Measures, and Error Bounds. Information Theoretic Learning 2010: 219-261
• 
  Robert Jenssen, Sudhir Rao:
  Clustering with ITL Principles. Information Theoretic Learning 2010: 263-298
• 
  Weifeng Liu, Puskal P. Pokharel, Jian-Wu Xu, Sohan Seth:
  Correntropy for Random Variables: Properties and Applications in Statistical Inference. Information Theoretic Learning 2010: 385-413
• 
  Puskal P. Pokharel, Ignacio Santamaría, Jianwu Xu, Kyu-Hwa Jeong, Weifeng Liu:
  Correntropy for Random Processes: Properties and Applications in Signal Processing. Information Theoretic Learning 2010: 415-455
• 
  José C. Príncipe:
  Information Theory, Machine Learning, and Reproducing Kernel Hilbert Spaces. Information Theoretic Learning 2010: 1-45
• 
  Sudhir Rao, Deniz Erdogmus, Dongxin Xu, Kenneth E. Hild II:
  Self-Organizing ITL Principles for Unsupervised Learning. Information Theoretic Learning 2010: 299-349
• 
  Dongxin Xu, Deniz Erdogmus:
  Renyi's Entropy, Divergence and Their Nonparametric Estimators. Information Theoretic Learning 2010: 47-102
• 
  Jian-Wu Xu, Robert Jenssen, António R. C. Paiva, Il Park:
  A Reproducing Kernel Hilbert Space Framework for ITL. Information Theoretic Learning 2010: 351-384
• 
  José C. Príncipe:
  Information Theoretic Learning - Renyi's Entropy and Kernel Perspectives. Springer 2010, ISBN 978-1-4419-1569-6 [contents]