Peter Tino

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A principled approach to interactive hierarchical non-linear visualization of high-dimensional data

Yi Sun, Peter Tino, Ian T. Nabney, 2002 .

Classification framework for partially observed dynamical systems.

Yuan Shen, Peter Tino, Krasimira Tsaneva-Atanasova, 2016, Physical review. E.

GTM-based data visualisation with incomplete data

Yi Sun, Ian T. Nabney, Peter Tino, 2001 .

Still alive: Extending keep-alive intervals in P2P overlay networks

Richard Price, Peter Tino, 2009, CollaborateCom 2009.

A mathematical characterization of the architectural bias of recursive models

Alessio Micheli, Barbara Hammer, Peter Tino, 2004 .

Does money matter in inflation forecasting

Jonathan A. Tepper, Barry E. Jones, Graham Kendall, 2009 .

A symbolic dynamics approach to volatility prediction

Georg Dorffner, Peter Tino, Christian Schittenkopf, 1998 .

Parallel problem solving from nature - PPSN VIII : 8th International Conference, Birmingham, UK, September 18-22, 2004 : proceedings

Edmund K. Burke, Xin Yao, Jose A. Lozano, 2004 .

A framework for comparing process mining algorithms

Behzad Bordbar, Philip Weber, Peter Tino, 2011, 2011 IEEE GCC Conference and Exhibition (GCC).

Input representation in recurrent neural networks dynamics pdf

Lorenzo Livi, Cesare Alippi, Peter Tino, 2020, ArXiv.

Visualisation and knowledge discovery from interpretable models

Kerstin Bunte, Peter Tino, Sreejita Ghosh, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Multimodal imaging of brain connectivity reveals predictors of individual decision strategy in statistical learning

Rui Wang, Zoe Kourtzi, Petra E. Vértes, 2019, Nature Human Behaviour.

Neural networks with small weights implement finite memory machines

Barbara Hammer, Peter Tino, P. Tiňo, 2002 .

Learning of hierarchical temporal structures facilitates the prediction of future events

Rui Wang, Zoe Kourtzi, Peter Tino, 2014 .

Automatic Detection of Galaxy Groups by Probabilistic Hough Transform

Peter Tino, Arif Babul, R. T. Ibrahem, 2015, International Conference on Neural Information Processing.

On Early Stages of Learning in Connectionist Models with Feedback Connections

Barbara Hammer, Peter Tino, 2004, AAAI Technical Report.

Feature Relevance Determination for Ordinal Regression in the Context of Feature Redundancies and Privileged Information

Michael Biehl, Barbara Hammer, Peter Tino, 2020, Neurocomputing.

Generalized Learning Riemannian Space Quantization: A Case Study on Riemannian Manifold of SPD Matrices

Fengzhen Tang, Peter Tino, Mengling Fan, 2021, IEEE Transactions on Neural Networks and Learning Systems.

Intelligent Data Engineering and Automated Learning – IDEAL 2019: 20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part I

Ronaldo Menezes, Hujun Yin, David Camacho, 2019, IDEAL.

A Multi-perspective Analysis of Social Context and Personal Factors in Office Settings for the Design of an Effective Mobile Notification System

Mirco Musolesi, Peter Tino, Seyma Kucukozer Cavdar, 2020, Proc. ACM Interact. Mob. Wearable Ubiquitous Technol..

Multiobjective Optimization Approach to Localization of Ectopic Beats by Single Dipole: Case Study

Peter Tino, Milan Tysler, Jan Zelinka, 2019, 2019 Computing in Cardiology (CinC).

Intelligent Data Engineering and Automated Learning - IDEAL 2010, 11th International Conference, Paisley, UK, September 1-3, 2010. Proceedings

Hujun Yin, Peter Tino, Colin Fyfe, 2010, IDEAL.

IEEE Transactions on Neural Networks

Peter Tino, Vector Machines, P. Tiňo, 2009 .

ASAP - A Sub-sampling Approach for Preserving Topological Structures

Kerstin Bunte, Peter Tino, Sven De Rijcke, 2021, ESANN.

Self-awareness in Software Engineering

Rami Bahsoon, Peter Tino, Abdessalam Elhabbash, 2019, ACM Trans. Auton. Adapt. Syst..

Visualisation of Incomplete Data Using Class Information Constraints

Yi Sun, Peter Tino, Ian T. Nabney, 2002 .

A Geometric Framework for Pitch Estimation on Acoustic Musical Signals pdf

Peter Tino, Tom Goodman, Karoline van Gemst, 2020, ArXiv.

Dynamical Systems as Temporal Feature Spaces pdf

Peter Tino, P. Tiňo, 2019, J. Mach. Learn. Res..

Sparsification of core set models in non-metric supervised learning

Frank-Michael Schleif, Peter Tino, Christoph Raab, 2020, Pattern Recognit. Lett..

Ice Shape Characterization Using Self-Organizing Maps

Peter Tino, Richard E. Kreeger, Stephen T. McClain, 2009 .

Human brain circuits for learning hierarchical temporal structures.

Yuan Shen, Rui Wang, Zoe Kourtzi, 2015, Journal of vision.

Foreword to the Focus Issue on Machine Intelligence in Astronomy and Astrophysics

Giuseppe Longo, Peter Tino, Erzs'ebet Mer'enyi, 2019, Publications of the Astronomical Society of the Pacific.

Semi-supervised construction of general visualization hierarchies

Yi Sun, Peter Tino, Ian T. Nabney, 2002 .

Multimodal imaging of brain connectivity reveals predictors of individual decision strategy in statistical learning

Yuan Shen, Rui Wang, Zoe Kourtzi, 2019, Nature Human Behaviour.

White-Matter Pathways for Statistical Learning of Temporal Structures

Yuan Shen, Guy Williams, Guy B. Williams, 2018, eNeuro.

Temporal pattern recognition in noisy non-stationary time series based on quantization into symbolic streams. Lessons learned from financial volatility trading.

Georg Dorffner, Peter Tino, Christian Schittenkopf, 2000 .

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS Publication Information

Michael J. Watts, Haibo He, Giorgio Battistelli, 2020, IEEE Transactions on Neural Networks and Learning Systems.

Proceedings of the 11th international conference on Intelligent data engineering and automated learning

Hujun Yin, Peter Tino, Colin Fyfe, 2002 .

SequentialRelevanceVectorMachineLearning from Time Series

Peter Tino, B Birmingham, Nikolay Y. Nikolaev, 2005 .

Relevance Learning Vector Quantization in Variable Dimensional Spaces

Kerstin Bunte, Peter Tino, Wiebke Arlt, 2016 .

LAAT: Locally Aligned Ant Technique for detecting manifolds of varying density pdf

Rory Smith, Kerstin Bunte, Peter Tino, 2020, ArXiv.

Designing Robust Models for Behaviour Prediction Using Sparse Data from Mobile Sensing

Mirco Musolesi, Abhinav Mehrotra, Peter Tino, 2021, ACM Trans. Comput. Heal..

SOMiMS - Topographic Mapping in the Model Space

Peter Tino, Krasimira Tsaneva-Atanasova, Eder Zavala, 2021, IDEAL.

Attaining Meta-self-awareness through Assessment of Quality-of-Knowledge

Rami Bahsoon, Peter Tino, Abdessalam Elhabbash, 2021, 2021 IEEE International Conference on Web Services (ICWS).

Probabilistic Learning Vector Quantization on Manifold of Symmetric Positive Definite Matrices

Fengzhen Tang, Peter Tino, Bailu Si, 2021, Neural Networks.

Tracking the Temporal-Evolution of Supernova Bubbles in Numerical Simulations

Kerstin Bunte, Peter Tino, Reynier Peletier, 2021, IDEAL.

Label-Assisted Memory Autoencoder for Unsupervised Out-of-Distribution Detection

Peter Tino, Ke Pei, Xin Yao, 2021, ECML/PKDD.

Functional brain networks for learning predictive statistics

Zoe Kourtzi, Peter Tino, Joseph Giorgio, 2017, Cortex.

Unravelling socio-motor biomarkers in schizophrenia

Aude Billard, Ludovic Marin, Peter Tino, 2017, npj Schizophrenia.

Nonlinear Prediction of Quantitative StructureActivity Relationships.

Ian T. Nabney, Peter Tino, Bruce S. Williams, 2004 .

The benefit of information reduction for trading strategies

Georg Dorffner, Peter Tino, Christian Schittenkopf, 2002 .

Locally Based Kernel PLS Regression De-noising with Application to Event-Related Potentials

Roman Rosipal, Peter Tino, Leonard J. Trejo, 2002 .