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ORCID11. ICANN 2001: Vienna, Austria
- Georg Dorffner
, Horst Bischof, Kurt Hornik:
Artificial Neural Networks - ICANN 2001, International Conference Vienna, Austria, August 21-25, 2001 Proceedings. Lecture Notes in Computer Science 2130, Springer 2001, ISBN 3-540-42486-5
Invited Papers
- Stephen Grossberg:
The Complementary Brain (Abstract). 3-4 - Alessandro Sperduti:
Neural Networks for Adaptive Processing of Structured Data. 5-12 - Florentin Wörgötter:
Bad Design and Good Performance: Strategies of the Visual System for Enhanced Scene Analysis. 13-18
Data Analysis and Pattern Recognition
- Nicol N. Schraudolph:
Fast Curvature Matrix-Vector Products. 19-26 - José R. Dorronsoro, Ana M. González, Carlos Santa Cruz:
Architecture Selection in NLDA Networks. 27-32 - Vicente Ruiz de Angulo, Carme Torras:
Neural Learning Invariant to Network Size Changes. 33-40 - Yves Grandvalet, Florence d'Alché-Buc, Christophe Ambroise:
Boosting Mixture Models for Semi-supervised Learning. 41-48 - Yves Grandvalet:
Bagging Can Stabilize without Reducing Variance. 49-56 - Achim F. Müller, Hans-Georg Zimmermann:
Symbolic Prosody Modeling by Causal Retro-causal NNs with Variable Context Length. 57-64 - Atsushi Sato:
Discriminative Dimensionality Reduction Based on Generalized LVQ. 65-72 - Hirotaka Nakayama, Masao Arakawa, Rie Sasaki:
A Computational Intelligence Approach to Optimization with Unknown Objective Functions. 73-80 - Samuel Kaski, Janne Sinkkonen, Janne Nikkilä:
Clustering Gene Expression Data by Mutual Information with Gene Function. 81-86 - Sepp Hochreiter, A. Steven Younger, Peter R. Conwell:
Learning to Learn Using Gradient Descent. 87-94 - Anita C. Faul, Michael E. Tipping:
A Variational Approach to Robust Regression. 95-102 - Stephen J. Roberts, Christopher C. Holmes, Dave Denison:
Minimum-Entropy Data Clustering Using Reversible Jump Markov Chain Monte Carlo. 103-110 - Sara Dolnicar, Friedrich Leisch:
Behavioral Market Segmentation of Binary Guest Survey Data with Bagged Clustering. 111-118 - Evangelos Dermatas:
Direct Estimation of Polynomial Densities in Generalized RBF Networks Using Moments. 119-126 - Xavier Parra, Núria Agell, Xari Rovira:
Generalisation Improvement of Radial Basis Function Networks Based on Qualitative Input Conditioning for Financial Credit Risk Prediction. 127-134 - Yoshifusa Ito, Cidambi Srinivasan:
Approximation of Bayesian Discriminant Function by Neural Networks in Terms of Kullback-Leibler Information. 135-140 - Mark Zlochin, Yoram Baram:
The Bias-Variance Dilemma of the Monte Carlo Method. 141-147 - Takehiro Nishiyama, Kazuo Tsuchiya, Katsuyoshi Tsujita:
A Markov Chain Monte Carlo Algorithm for the Quadratic Assignment Problem Based on Replicator Equations. 148-155 - Michael Weeks, Jim Austin, Anthony Moulds, Aaron Turner, Zygmunt Ulanowski, Julian Young:
Mapping Correlation Matrix Memory Applications onto a Beowulf Cluster. 156-163 - Alfred Strey, Martin Bange:
Accelerating RBF Network Simulation by Using Multimedia Extensions of Modern Microprocessors. 164-169 - Wai-Keung Fung, Yun-Hui Liu:
A Game-Theoretic Adaptive Categorization Mechanism for ART-Type Networks. 170-176 - Irwin W. Sandberg:
Gaussian Radial Basis Functions and Inner-Product Spaces. 177-182 - Masahiro Tanaka:
Mixture of Probabilistic Factor Analysis Model and Its Applications. 183-188 - José María Valls, Pedro Isasi, Inés María Galván:
Deferring the Learning for Better Generalization in Radial Basis Neural Networks. 189-195 - Christophe Lurette, Stéphane Lecoeuche:
Improvement of Cluster Detection and Labeling Neural Network by Introducing Elliptical Basis Function. 196-202 - Krista Lagus, Esa Alhoniemi, Harri Valpola:
Independent Variable Group Analysis. 203-210 - Fatih Köksal, Ethem Alpaydin, Günhan Dündar:
Weight Quantization for Multi-layer Perceptrons Using Soft Weight Sharing. 211-216 - Evgenia Dimitriadou, Andreas Weingessel, Kurt Hornik:
Voting-Merging: An Ensemble Method for Clustering. 217-224 - James Cannady, Raymond C. Garcia:
The Application of Fuzzy ARTMAP in the Detection of Computer Network Attacks. 225-230 - Chun Hung Li, Pong Chi Yuen:
Transductive Learning: Learning Iris Data with Two Labeled Data. 231-236 - Achim Lewandowski, Peter Protzel:
Approximation of Time-Varying Functions with Local Regression Models. 237-246
Theory
- Michael Schmitt:
Complexity of Learning for Networks of Spiking Neurons with Nonlinear Synaptic Interactions. 247-252 - Michael Schmitt:
Product Unit Neural Networks with Constant Depth and Superlinear VC Dimension. 253-258 - Gérald Gavin:
Generalization Performances of Perceptrons. 259-264 - Olivier Teytaud, Hélène Paugam-Moisy:
Bounds on the Generalization Ability of Bayesian Inference and Gibbs Algorithms. 265-270 - Dörthe Malzahn, Manfred Opper:
Learning Curves for Gaussian Processes Models: Fluctuations and Universality. 271-276 - Vera Kurková, Marcello Sanguineti:
Tight Bounds on Rates of Neural-Network Approximation. 277-284
Kernel Methods
- Volker Tresp, Anton Schwaighofer:
Scalable Kernel Systems. 285-291 - Shigeyuki Oba, Masa-aki Sato, Shin Ishii:
On-Line Learning Methods for Gaussian Processes. 292-299 - Lehel Csató, Dan Cornford, Manfred Opper:
Online Approximations for Wind-Field Models. 300-307 - Shigeo Abe, Takuya Inoue:
Fast Training of Support Vector Machines by Extracting Boundary Data. 308-313 - Eddy Mayoraz:
Multiclass Classification with Pairwise Coupled Neural Networks or Support Vector Machines. 314-321 - Liva Ralaivola, Florence d'Alché-Buc:
Incremental Support Vector Machine Learning: A Local Approach. 322-330 - Koji Tsuda, Gunnar Rätsch, Sebastian Mika, Klaus-Robert Müller:
Learning to Predict the Leave-One-Out Error of Kernel Based Classifiers. 331-338 - Volker Roth:
Sparse Kernel Regressors. 339-346 - Thore Graepel, Mike Goutrié, Marco Krüger, Ralf Herbrich:
Learning on Graphs in the Game of Go. 347-352 - Thomas Melzer, Michael Reiter, Horst Bischof:
Nonlinear Feature Extraction Using Generalized Canonical Correlation Analysis. 353-360 - Ken-ichi Amemori, Shin Ishii:
Gaussian Process Approach to Stochastic Spiking Neurons with Reset. 361-368 - Olivier Teytaud, David Sarrut:
Kernel Based Image Classification. 369-375 - Mohammed El-Beltagy, W. Andy Wright:
Gaussian Processes for Model Fusion. 376-383 - Tony Van Gestel, Johan A. K. Suykens, Jos De Brabanter, Bart De Moor, Joos Vandewalle:
Kernel Canonical Correlation Analysis and Least Squares Support Vector Machines. 384-389 - Thomas Frontzek, Thomas Navin Lal, Rolf Eckmiller:
Learning and Prediction of the Nonlinear Dynamics of Biological Neurons with Support Vector Machines. 390-398 - Chellu Chandra Sekhar, Kazuya Takeda, Fumitada Itakura:
Close-Class-Set Discrimination Method for Recognition of Stop_Consonant-Vowel Utterances Using Support Vector Machines. 399-404 - James T. Kwok:
Linear Dependency between epsilon and the Input Noise in epsilon-Support Vector Regression. 405-410 - Anton Schwaighofer, Volker Tresp:
The Bayesian Committee Support Vector Machine. 411-420
Topographic Mapping
- Peter Tiño, Ian T. Nabney, Yi Sun:
Using Directional Curvatures to Visualize Folding Patterns of the GTM Projection Manifolds. 421-428 - Manuel Martín-Merino, Alberto Muñoz:
Self Organizing Map and Sammon Mapping for Asymmetric Proximities. 429-435 - Michele Milano, Jürgen Schmidhuber, Petros Koumoutsakos:
Active Learning with Adaptive Grids. 436-442 - Ignacio Díaz Blanco, Alberto B. Diez González, Abel Alberto Cuadrado Vega:
Complex Process Visualization through Continuous Feature Maps Using Radial Basis Functions. 443-449 - Jakob J. Verbeek, Nikos Vlassis, Ben J. A. Kröse:
A Soft k-Segments Algorithm for Principal Curves. 450-456 - Christakis Charalambous, George C. Hadjinicola, Eitan Muller:
Product Positioning Using Principles from the Self-Organizing Map. 457-463 - Kristof Van Laerhoven:
Combining the Self-Organizing Map and K-Means Clustering for On-Line Classification of Sensor Data. 464-469 - Antonios Atsalakis, Ioannis Andreadis, Nikos Papamarkos:
Histogram Based Color Reduction through Self-Organized Neural Networks. 470-476 - Motonobu Hattori, Hiroya Arisumi, Hiroshi Ito:
Sequential Learning for SOM Associative Memory with Map Reconstruction. 477-484 - Jarkko Venna, Samuel Kaski:
Neighborhood Preservation in Nonlinear Projection Methods: An Experimental Study. 485-491 - Méziane Yacoub, Fouad Badran, Sylvie Thiria:
A Topological Hierarchical Clustering: Application to Ocean Color Classification. 492-499 - Michael Dittenbach, Dieter Merkl, Andreas Rauber:
Hierarchical Clustering of Document Archives with the Growing Hierarchical Self-Organizing Map. 500-508
Independent Component Analysis
- Roland Vollgraf, Ingo Schießl, Klaus Obermayer:
Blind Source Separation of Single Components from Linear Mixtures. 509-514 - Konstantinos I. Diamantaras:
Blind Source Separation Using Principal Component Neural Networks. 515-520 - Rubén Martín-Clemente, José I. Acha, Carlos García Puntonet:
Blind Separation of Sources by Differentiating the Output Cumulants and Using Newton's Method. 521-526 - Stephen J. Roberts, William D. Penny:
Mixtures of Independent Component Analysers. 527-534 - Shotaro Akaho:
Conditionally Independent Component Extraction for Naive Bayes Inference. 535-540 - Nikos Vlassis:
Fast Score Function Estimation with Application in ICA. 541-546 - Alexander Ypma, Co Melissant, Ole Baunbæk-Jensen, Robert P. W. Duin:
Health Monitoring with Learning Methods. 547-553 - Ioanna Christoyianni, Athanasios Koutras, Evangelos Dermatas, George K. Kokkinakis:
Breast Tissue Classification in Mammograms Using ICA Mixture Models. 554-560 - Athanasios Koutras, Evangelos Dermatas, George K. Kokkinakis:
Neural Network Based Blind Source Separation of Non-linear Mixtures. 561-567 - Nojun Kwak, Chong-Ho Choi, Jin-Young Choi:
Feature Extraction Using ICA. 568-576
Signal Processing
- Edmondo Trentin, Marco Gori:
Continuous Speech Recognition with a Robust Connectionist/Markovian Hybrid Model. 577-582 - Martin Bouchard:
Faster Convergence and Improved Performance in Least-Squares Training of Neural Networks for Active Sound Cancellation. 583-592 - Ilyas Potamitis, Nikos Fakotakis, George K. Kokkinakis:
Bayesian Independent Component Analysis as Applied to One-Channel Speech Enhancement. 593-600 - Bao-Liang Lu, Jonghan Shin, Michinori Ichikawa:
Massively Parallel Classification of EEG Signals Using Min-Max Modular Neural Networks. 601-608 - Arthur Flexer, Herbert Bauer, Claus Lamm, Georg Dorffner:
Single Trial Estimation of Evoked Potentials Using Gaussian Mixture Models with Integrated Noise Component. 609-616 - Peter Sykacek, Stephen J. Roberts, Iead Rezek, Arthur Flexer, Georg Dorffner:
A Probabilistic Approach to High-Resolution Sleep Analysis. 617-624 - Vladimir Cherkassky, Steven Kilts:
Comparison of Wavelet Thresholding Methods for Denoising ECG Signals. 625-629 - G. Sita, A. G. Ramakrishnan:
Evoked Potential Signal Estimation Using Gaussian Radial Basis Function Network. 630-635 - Bernhard Obermaier, Gernot R. Müller, Gert Pfurtscheller:
'Virtual Keyboard' Controlled by Spontaneous EEG Activity. 636-641 - David Sommer, Martin Golz:
Clustering of EEG-Segments Using Hierarchical Agglomerative Methods and Self-Organizing Maps. 642-649 - Wei Lee Woon, David Lowe:
Nonlinear Signal Processing for Noise Reduction of Unaveraged Single Channel MEG Data. 650-660
Time Series Processing
- Sepp Hochreiter, Michael Mozer:
A Discrete Probabilistic Memory Model for Discovering Dependencies in Time. 661-668 - Felix A. Gers, Douglas Eck, Jürgen Schmidhuber:
Applying LSTM to Time Series Predictable through Time-Window Approaches. 669-676 - Marc Strickert, Thorsten Bojer, Barbara Hammer:
Generalized Relevance LVQ for Time Series. 677-683 - Magdalena Klapper-Rybicka, Nicol N. Schraudolph, Jürgen Schmidhuber:
Unsupervised Learning in LSTM Recurrent Neural Networks. 684-691 - Hiroshi Murata, Takashi Onoda:
Applying Kernel Based Subspace Classification to a Non-intrusive Monitoring for Household Electric Appliances. 692-698 - Alessio Plebe, Marcello A. Anile, Salvatore Rinaudo:
Neural Networks in Circuit Simulators. 699-705 - Gustavo Camps-Valls, Emilio Soria-Olivas, José David Martín-Guerrero, Antonio J. Serrano-López, Juan José Pérez-Ruixo, N. Víctor Jiménez:
Neural Networks Ensemble for Cyclosporine Concentration Monitoring. 706-711 - Hirotaka Inoue, Yoshinobu Fukunaga, Hiroyuki Narihisa:
Efficient Hybrid Neural Network for Chaotic Time Series Prediction. 712-718 - Juan Antonio Pérez-Ortiz, Jorge Calera-Rubio, Mikel L. Forcada:
Online Symbolic-Sequence Prediction with Discrete-Time Recurrent Neural Networks. 719-724 - Stanislav Kaleta, Daniel Novotný, Peter Sincak:
Prediction Systems Based on FIR BP Neural Networks. 725-730 - Barbara Hammer:
On the Generalization Ability of Recurrent Networks. 731-736 - Michal Cernanský, Lubica Benusková:
Finite-State Reber Automaton and the Recurrent Neural Networks Trained in Supervised and Unsupervised Manner. 737-742 - Volodymyr Turchenko, Volodymyr Kochan, Anatoly Sachenko:
Estimation of Computational Complexity of Sensor Accuracy Improvement Algorithm Based on Neural Networks. 743-748 - Christian Dietrich, Friedhelm Schwenker, Günther Palm:
Fusion Architectures for the Classification of Time Series. 749-758
Special Session: Agent-Based Economic Modeling
- Bruce Edmonds, Scott Moss:
The Importance of Representing Cognitive Processes in Multi-agent Models. 759-766 - Hans-Georg Zimmermann, Ralph Neuneier, Ralph Grothmann:
Multi-agent FX-Market Modeling Based on Cognitive Systems. 767-774 - Taisei Kaizoji:
Speculative Dynamics in a Heterogeneous-Agent Model. 775-781 - Andrea Gaunersdorfer, Cars H. Hommes:
Nonlinear Adaptive Beliefs and the Dynamics of Financial Markets: The Role of the Evolutionary Fitness Measure. 782-789 - Harald Hruschka, Werner Fettes, Markus Probst:
Analyzing Purchase Data by a Neural Net Extension of the Multinomial Logit Model. 790-798
Selforganization and Dynamical Systems
- Heiko Wersing, Helge J. Ritter:
Using Maximal Recurrence in Linear Threshold Competitive Layer Networks. 799-805 - Jirí Síma, Pekka Orponen:
Exponential Transients in Continuous-Time Symmetric Hopfield Nets. 806-813 - Hugo de Garis, Andrzej Buller, Leo de Penning, Tomasz Chodakowski, Derek Decesare:
Initial Evolution Results on CAM-Brain Machines (CBMs). 814-819 - Christof Teuscher, Eduardo Sanchez:
Self-Organizing Topology Evolution of Turing Neural Networks. 820-826 - Brijnesh J. Jain, Fritz Wysotzki:
Efficient Pattern Discrimination with Inhibitory WTA Nets. 827-834 - Ryotaro Kamimura, Taeko Kamimura:
Cooperative Information Control to Coordinate Competition and Cooperation. 835-842 - Yasuaki Kuroe, Naoki Hashimoto, Takehiro Mori:
Qualitative Analysis of Continuous Complex-Valued Associative Memories. 843-850 - Nils Goerke, Florian Kintzler, Rolf Eckmiller:
Self Organized Partitioning of Chaotic Attractors for Control. 851-856 - W. Andy Wright, Robert E. Smith, Martin Danek, Pillip Greenway:
A Generalisable Measure of Self-Organisation and Emergence. 857-864 - Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber:
Market-Based Reinforcement Learning in Partially Observable Worlds. 865-873 - W. Andy Wright:
Sequential Strategy for Learning Multi-stage Multi-agent Collaborative Games. 874-884
Robotics and Control
- Volker Stephan, Horst-Michael Gross:
Neural Architecture for Mental Imaging of Sequences Based on Optical Flow Predictions. 885-890 - Gunther Heidemann, Helge J. Ritter:
Visual Checking of Grasping Positions of a Three-Fingered Robot Hand. 891-898