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Peter Tino
List of publications from the DBLP Bibliography Server - FAQ
2008 | ||
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47 | EE | Xiaoxia Wang, Peter Tiño, Mark A. Fardal: Multiple Manifolds Learning Framework Based on Hierarchical Mixture Density Model. ECML/PKDD (2) 2008: 566-581 |
46 | EE | Michal Cernanský, Peter Tiño: Predictive Modeling with Echo State Networks. ICANN (1) 2008: 778-787 |
45 | EE | Peter Tino: Equilibria of Iterative Softmax and Critical Temperatures for Intermittent Search in Self-Organizing Neural Networks. Recurrent Neural Networks 2008 |
44 | EE | Siang Yew Chong, Peter Tino, Xin Yao: Measuring Generalization Performance in Coevolutionary Learning. IEEE Trans. Evolutionary Computation 12(4): 479-505 (2008) |
2007 | ||
43 | Hujun Yin, Peter Tiño, Emilio Corchado, William Byrne, Xin Yao: Intelligent Data Engineering and Automated Learning - IDEAL 2007, 8th International Conference, Birmingham, UK, December 16-19, 2007, Proceedings Springer 2007 | |
42 | EE | Nikolaos Gianniotis, Peter Tino: Visualisation of tree-structured data through generative probabilistic modelling. ESANN 2007: 97-102 |
41 | EE | Michal Cernanský, Peter Tino: Comparison of Echo State Networks with Simple Recurrent Networks and Variable-Length Markov Models on Symbolic Sequences. ICANN (1) 2007: 618-627 |
40 | EE | Peter Tiño: Bifurcations of Renormalization Dynamics in Self-organizing Neural Networks. ICONIP (1) 2007: 405-414 |
39 | EE | Peter Tino, Nikolaos Gianniotis: Metric Properties of Structured Data Visualizations through Generative Probabilistic Modeling. IJCAI 2007: 1083-1088 |
38 | EE | Peter Tino: On Conditions for Intermittent Search in Self-organizing Neural Networks. MICAI 2007: 172-181 |
37 | EE | Peter Tino, Barbara Hammer, Mikael Bodén: Markovian Bias of Neural-based Architectures With Feedback Connections. Perspectives of Neural-Symbolic Integration 2007: 95-133 |
36 | EE | Peter Tino: Equilibria of Iterative Softmax and Critical Temperatures for Intermittent Search in Self-Organizing Neural Networks. Neural Computation 19(4): 1056-1081 (2007) |
2006 | ||
35 | EE | Juan C. Cuevas-Tello, Peter Tiño, Somak Raychaudhury: A Kernel-Based Approach to Estimating Phase Shifts Between Irregularly Sampled Time Series: An Application to Gravitational Lenses. ECML 2006: 614-621 |
34 | EE | Huanhuan Chen, Peter Tiño, Xin Yao: A Probabilistic Ensemble Pruning Algorithm. ICDM Workshops 2006: 878-882 |
33 | EE | Jane M. Binner, Barry Jones, Graham Kendall, Jonathan A. Tepper, Peter Tiño: Does Money Matter? An Artificial Intelligence Approach. JCIS 2006 |
32 | EE | Peter Tino: Critical Temperatures for Intermittent Search in Self-Organizing Neural Networks. PPSN 2006: 633-640 |
31 | EE | Juan C. Cuevas-Tello, Peter Tino, Somak Raychaudhury: How accurate are the time delay estimates in gravitational lensing? CoRR abs/astro-ph/0605042: (2006) |
30 | EE | Peter Tiño, Igor Farkas, Jort van Mourik: Dynamics and Topographic Organization of Recursive Self-Organizing Maps. Neural Computation 18(10): 2529-2567 (2006) |
29 | EE | Peter Tiño, Ashley J. S. Mills: Learning Beyond Finite Memory in Recurrent Networks of Spiking Neurons. Neural Computation 18(3): 591-613 (2006) |
2005 | ||
28 | EE | Peter Tiño, Ashley J. S. Mills: Learning Beyond Finite Memory in Recurrent Networks of Spiking Neurons. ICNC (2) 2005: 666-675 |
27 | EE | Peter Tiño, Igor Farkas: On Non-markovian Topographic Organization of Receptive Fields in Recursive Self-organizing Map. ICNC (2) 2005: 676-685 |
26 | EE | Peter Tiño, Igor Farkas, Jort van Mourik: Recursive Self-organizing Map as a Contractive Iterative Function System. IDEAL 2005: 327-334 |
25 | EE | Ian T. Nabney, Yi Sun, Peter Tiño, Ata Kabán: Semisupervised Learning of Hierarchical Latent Trait Models for Data Visualization. IEEE Trans. Knowl. Data Eng. 17(3): 384-400 (2005) |
24 | EE | Gavin Brown, Jeremy L. Wyatt, Peter Tino: Managing Diversity in Regression Ensembles. Journal of Machine Learning Research 6: 1621-1650 (2005) |
2004 | ||
23 | Xin Yao, Edmund K. Burke, José Antonio Lozano, Jim Smith, Juan J. Merelo Guervós, John A. Bullinaria, Jonathan E. Rowe, Peter Tiño, Ata Kabán, Hans-Paul Schwefel: Parallel Problem Solving from Nature - PPSN VIII, 8th International Conference, Birmingham, UK, September 18-22, 2004, Proceedings Springer 2004 | |
22 | Gabriela Polcicova, Peter Tiño: Introducing a Star Topology into Latent Class Models for Collaborative Filtering. AIAI 2004: 293-304 | |
21 | EE | Peter Tiño, Ata Kabán, Yi Sun: A generative probabilistic approach to visualizing sets of symbolic sequences. KDD 2004: 701-706 |
20 | EE | Richard Price, Peter Tiño: Evaluation of Adaptive Nature Inspired Task Allocation Against Alternate Decentralised Multiagent Strategies. PPSN 2004: 982-990 |
19 | EE | Peter Tiño, Ian T. Nabney, Bruce S. Williams, Jens Lösel, Yi Sun: Nonlinear Prediction of Quantitative Structure-Activity Relationships. Journal of Chemical Information and Modeling 44(5): 1647-1653 (2004) |
18 | EE | Gabriela Polcicová, Peter Tiño: Making sense of sparse rating data in collaborative filtering via topographic organization of user preference patterns. Neural Networks 17(8-9): 1183-1199 (2004) |
2003 | ||
17 | EE | Barbara Hammer, Peter Tiño: Recurrent Neural Networks with Small Weights Implement Definite Memory Machines. Neural Computation 15(8): 1897-1929 (2003) |
16 | EE | Peter Tiño, Barbara Hammer: Architectural Bias in Recurrent Neural Networks: Fractal Analysis. Neural Computation 15(8): 1931-1957 (2003) |
2002 | ||
15 | EE | Peter Tiño, Barbara Hammer: Architectural Bias in Recurrent Neural Networks - Fractal Analysis. ICANN 2002: 1359-1364 |
14 | EE | Ata Kabán, Peter Tiño, Mark Girolami: A General Framework for a Principled Hierarchical Visualization of Multivariate Data. IDEAL 2002: 518-523 |
13 | EE | Peter Tiño, Ian T. Nabney: Hierarchical GTM: Constructing Localized Nonlinear Projection Manifolds in a Principled Way. IEEE Trans. Pattern Anal. Mach. Intell. 24(5): 639-656 (2002) |
2001 | ||
12 | EE | Peter Tiño, Ian T. Nabney, Yi Sun: Using Directional Curvatures to Visualize Folding Patterns of the GTM Projection Manifolds. ICANN 2001: 421-428 |
11 | Peter Tiño, Georg Dorffner: Predicting the Future of Discrete Sequences from Fractal Representations of the Past. Machine Learning 45(2): 187-217 (2001) | |
10 | Peter Tiño, Bill G. Horne, C. Lee Giles: Attractive Periodic Sets in Discrete-Time Recurrent Networks (with Emphasis on Fixed-Point Stability and Bifurcations in Two-Neuron Networks). Neural Computation 13(6): 1379-1414 (2001) | |
9 | EE | Peter Tiño, Christian Schittenkopf, Georg Dorffner: Volatility Trading ia Temporal Pattern Recognition in Quantised Financial Time Series. Pattern Anal. Appl. 4(4): 283-299 (2001) |
2000 | ||
8 | EE | Peter Tiño, Michal Stancík, Lubica Benusková: Building Predictive Models on Complex Symbolic Sequences with a Second-Order Recurrent BCM Network with Lateral Inhibition. IJCNN (2) 2000: 265-270 |
1999 | ||
7 | EE | Shan Parfitt, Peter Tiño, Georg Dorffner: Graded Grammaticality in Prediction Fractal Machines. NIPS 1999: 52-58 |
6 | EE | Peter Tiño, Georg Dorffner: Building Predictive Models from Fractal Representations of Symbolic Sequences. NIPS 1999: 645-651 |
5 | EE | Peter Tino, Miroslav Koteles: Extracting finite-state representations from recurrent neural networks trained on chaotic symbolic sequences. IEEE Transactions on Neural Networks 10(2): 284-302 (1999) |
4 | Peter Tiño: Spatial representation of symbolic sequences through iterative function systems. IEEE Transactions on Systems, Man, and Cybernetics, Part A 29(4): 386-393 (1999) | |
1998 | ||
3 | Peter Tiño, Georg Dorffner, Christian Schittenkopf: Understanding State Space Organization in Recurrent Neural Networks with Iterative Function Systems Dynamics. Hybrid Neural Systems 1998: 255-269 | |
2 | Peter Tiño, Georg Dorffner: Recurrent Neural Networks with Iterated Function Systems Dynamics. NC 1998: 526-532 | |
1995 | ||
1 | EE | Tsungnan Lin, Bill G. Horne, Peter Tiño, C. Lee Giles: Learning long-term dependencies is not as difficult with NARX networks. NIPS 1995: 577-583 |