Peter Tiño

ORCID

Publication Activity (10 Years)

Years Active: 1995-2022
Publications (10 Years): 59

Top Venues

Publications

Marco Canducci, Peter Tiño, Michele Mastropietro
Probabilistic modelling of general noisy multi-manifold data sets. Artif. Intell. 302 (2022)
Hayatullahi Bolaji Adeyemo, Rami Bahsoon, Peter Tiño
Surrogate-based Digital Twin for Predictive Fault Modelling and Testing of Cyber Physical Systems. BDCAT (2022)
Marco Canducci, P. Awad, Abolfazl Taghribi, Mohammad Mohammadi, Michele Mastropietro, Sven De Rijcke, Reynier Peletier, Rory Smith, Kerstin Bunte, Peter Tiño
1-DREAM: 1D Recovery, Extraction and Analysis of Manifolds in noisy environments. Astron. Comput. 41 (2022)
Stephen Friess, Peter Tiño, Zhao Xu, Stefan Menzel, Bernhard Sendhoff, Xin Yao
Artificial Neural Networks as Feature Extractors in Continuous Evolutionary Optimization. IJCNN (2021)
Yu Zhang, Peter Tiño, Ales Leonardis, Ke Tang
A Survey on Neural Network Interpretability. IEEE Trans. Emerg. Top. Comput. Intell. 5 (5) (2021)
Fengzhen Tang, Haifeng Feng, Peter Tiño, Bailu Si, Daxiong Ji
Probabilistic Learning Vector Quantization on Manifold of Symmetric Positive Definite Matrices. CoRR (2021)
Fengzhen Tang, Mengling Fan, Peter Tiño
Generalized Learning Riemannian Space Quantization: A Case Study on Riemannian Manifold of SPD Matrices. IEEE Trans. Neural Networks Learn. Syst. 32 (1) (2021)
Giuseppe Serra, Zhao Xu, Mathias Niepert, Carolin Lawrence, Peter Tiño, Xin Yao
Interpreting Node Embedding with Text-labeled Graphs. IJCNN (2021)
Seyma Kucukozer Cavdar, Tugba Taskaya-Temizel, Mirco Musolesi, Peter Tiño
A Multi-perspective Analysis of Social Context and Personal Factors in Office Settings for the Design of an Effective Mobile Notification System. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4 (1) (2020)
Yu Zhang, Peter Tiño, Ales Leonardis, Ke Tang
A Survey on Neural Network Interpretability. CoRR (2020)
Pietro Verzelli, Cesare Alippi, Lorenzo Livi, Peter Tiño
Input representation in recurrent neural networks dynamics. CoRR (2020)
Stephen Friess, Peter Tiño, Stefan Menzel, Bernhard Sendhoff, Xin Yao
Representing Experience in Continuous Evolutionary optimisation through Problem-tailored Search Operators. CEC (2020)
Stephen Friess, Peter Tiño, Stefan Menzel, Bernhard Sendhoff, Xin Yao
Improving Sampling in Evolution Strategies Through Mixture-Based Distributions Built from Past Problem Instances. PPSN (1) (2020)
Tom Goodman, Karoline van Gemst, Peter Tiño
A Geometric Framework for Pitch Estimation on Acoustic Musical Signals. CoRR (2020)
Sreejita Ghosh, Peter Tiño, Kerstin Bunte
Visualisation and knowledge discovery from interpretable models. IJCNN (2020)
Abolfazl Taghribi, Kerstin Bunte, Rory Smith, Jihye Shin, Michele Mastropietro, Reynier F. Peletier, Peter Tiño
LAAT: Locally Aligned Ant Technique for detecting manifolds of varying density. CoRR (2020)
Abolfazl Taghribi, Kerstin Bunte, Michele Mastropietro, Sven De Rijcke, Peter Tiño
ASAP - A Sub-sampling Approach for Preserving Topological Structures. ESANN (2020)
Frank-Michael Schleif, Christoph Raab, Peter Tiño
Sparsification of core set models in non-metric supervised learning. Pattern Recognit. Lett. 129 (2020)
Peter Tiño
Dynamical Systems as Temporal Feature Spaces. J. Mach. Learn. Res. 21 (2020)
Lukas Pfannschmidt, Jonathan Jakob, Fabian Hinder, Michael Biehl, Peter Tiño, Barbara Hammer
Feature relevance determination for ordinal regression in the context of feature redundancies and privileged information. Neurocomputing 416 (2020)
Sreejita Ghosh, Peter Tiño, Kerstin Bunte
Visualisation and knowledge discovery from interpretable models. CoRR (2020)
Lukas Pfannschmidt, Jonathan Jakob, Fabian Hinder, Michael Biehl, Peter Tiño, Barbara Hammer
Feature Relevance Determination for Ordinal Regression in the Context of Feature Redundancies and Privileged Information. CoRR (2019)
María Pérez-Ortiz, Pedro Antonio Gutiérrez, Peter Tiño, Carlos Casanova-Mateo, Sancho Salcedo-Sanz
A mixture of experts model for predicting persistent weather patterns. CoRR (2019)
Stephen Friess, Peter Tiño, Stefan Menzel, Bernhard Sendhoff, Xin Yao
Learning Transferable Variation Operators in a Continuous Genetic Algorithm. SSCI (2019)
Abdessalam Elhabbash, Maria Salama, Rami Bahsoon, Peter Tiño
Self-awareness in Software Engineering: A Systematic Literature Review. ACM Trans. Auton. Adapt. Syst. 14 (2) (2019)
Siang Yew Chong, Peter Tiño, Jun He, Xin Yao
A New Framework for Analysis of Coevolutionary Systems - Directed Graph Representation and Random Walks. Evol. Comput. 27 (2) (2019)
María Pérez-Ortiz, Peter Tiño, Rafal Mantiuk, César Hervás-Martínez
Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets. CoRR (2019)
Lukas Pfannschmidt, Jonathan Jakob, Michael Biehl, Peter Tiño, Barbara Hammer
Feature relevance bounds for ordinal regression. ESANN (2019)
Lukas Pfannschmidt, Jonathan Jakob, Michael Biehl, Peter Tiño, Barbara Hammer
Feature Relevance Bounds for Ordinal Regression. CoRR (2019)
Jana Svehlíková, Jan Zelinka, Milan Tysler, Peter Tiño
Multiobjective Optimization Approach to Localization of Ectopic Beats by Single Dipole: Case Study. CinC (2019)
Peter Tiño
Dynamical Systems as Temporal Feature Spaces. CoRR (2019)
Robert Simon Fong, Peter Tiño
Extended stochastic derivative-free optimization on riemannian manifolds. GECCO (Companion) (2019)
María Pérez-Ortiz, Peter Tiño, Rafal Mantiuk, César Hervás-Martínez
Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets. AAAI (2019)
Siang Yew Chong, Peter Tiño, Jun He
Coevolutionary systems and PageRank. Artif. Intell. 277 (2019)
Frank-Michael Schleif, Andrej Gisbrecht, Peter Tiño
Supervised low rank indefinite kernel approximation using minimum enclosing balls. Neurocomputing 318 (2018)
M. Pérez-Ortiz, Pedro Antonio Gutiérrez, Peter Tiño, Carlos Casanova-Mateo, Sancho Salcedo-Sanz
A mixture of experts model for predicting persistent weather patterns. IJCNN (2018)
Claudio Gallicchio, Alessio Micheli, Peter Tiño
Randomized Recurrent Neural Networks. ESANN (2018)
Peter Tiño
Asymptotic Fisher memory of randomized linear symmetric Echo State Networks. Neurocomputing 298 (2018)
Frank-Michael Schleif, Christoph Raab, Peter Tiño
Sparsification of Indefinite Learning Models. S+SSPR (2018)
Michael Biehl, Kerstin Bunte, Giuseppe Longo, Peter Tiño
Machine learning and data analysis in astroinformatics. ESANN (2018)
Abdessalam Elhabbash, Rami Bahsoon, Peter Tiño
Self-Awareness for Dynamic Knowledge Management in Self-Adaptive Volunteer Services. ICWS (2017)
Fengzhen Tang, Peter Tiño
Ordinal regression based on learning vector quantization. Neural Networks 93 (2017)
Frank-Michael Schleif, Peter Tiño
Indefinite Core Vector Machine. Pattern Recognit. 71 (2017)
Fani Tsapeli, Peter Tiño, Mirco Musolesi
Probabilistic matching: Causal inference under measurement errors. IJCNN (2017)
Yuan Shen, Peter Tiño, Krasimira Tsaneva-Atanasova
Classification of sparsely and irregularly sampled time series: A learning in model space approach. IJCNN (2017)
Peter Tiño
Fisher memory of linear Wigner echo state networks. ESANN (2017)
Fani Tsapeli, Nikolaos Bezirgiannidis, Peter Tiño, Mirco Musolesi
Linking Twitter Events With Stock Market Jitters. CoRR (2017)
Sreejita Ghosh, Elizabeth Sarah Baranowski, Rick van Veen, Gert-Jan de Vries, Michael Biehl, Wiebke Arlt, Peter Tiño, Kerstin Bunte
Comparison of strategies to learn from imbalanced classes for computer aided diagnosis of inborn steroidogenic disorders. ESANN (2017)
Luca Pasa, Alessandro Sperduti, Peter Tiño
Linear dynamical based models for sequential domains. IJCNN (2017)
María Pérez-Ortiz, Pedro Antonio Gutiérrez, Peter Tiño, César Hervás-Martínez
Oversampling the Minority Class in the Feature Space. IEEE Trans. Neural Networks Learn. Syst. 27 (9) (2016)
Hanin H. Alahmadi, Yuan Shen, Shereen Fouad, Caroline Di Bernardi Luft, Peter Bentham, Zoe Kourtzi, Peter Tiño
Classifying Cognitive Profiles Using Machine Learning with Privileged Information in Mild Cognitive Impairment. Frontiers Comput. Neurosci. 10 (2016)
Frank-Michael Schleif, Peter Tiño, Yingyu Liang
Learning in indefinite proximity spaces - recent trends. ESANN (2016)
Nikolaos Gianniotis, Sven Dennis Kügler, Peter Tiño, Kai Lars Polsterer
Model-Coupled Autoencoder for Time Series Visualisation. CoRR (2016)
Frank-Michael Schleif, Andrej Gisbrecht, Peter Tiño
Probabilistic classifiers with low rank indefinite kernels. CoRR (2016)
Nikolaos Gianniotis, Sven Dennis Kügler, Peter Tiño, Kai Lars Polsterer
Model-coupled autoencoder for time series visualisation. Neurocomputing 192 (2016)
Sultanah Al Otaibi, Peter Tiño, Somak Raychaudhury
Probabilistic Modelling for Delay Estimation in Gravitationally Lensed Photon Streams. IDEAL (2016)
Abdessalam Elhabbash, Rami Bahsoon, Peter Tiño
Interaction-Awareness for Self-Adaptive Volunteer Computing. SASO (2016)
Nahed Alowadi, Yuan Shen, Peter Tiño
Prototype-Based Spatio-Temporal Probabilistic Modelling of fMRI Data. WSOM (2016)
Frank-Michael Schleif, Ata Kabán, Peter Tiño
Finding Small Sets of Random Fourier Features for Shift-Invariant Kernel Approximation. ANNPR (2016)
Frank-Michael Schleif, Andrej Gisbrecht, Peter Tiño
Probabilistic Classification Vector Machine at large scale. ESANN (2015)
Frank-Michael Schleif, H. Chen, Peter Tiño
Incremental probabilistic classification vector machine with linear costs. IJCNN (2015)
Huanhuan Chen, Fengzhen Tang, Peter Tiño, Anthony G. Cohn, Xin Yao
Model Metric Co-Learning for Time Series Classification. IJCAI (2015)
Frank-Michael Schleif, Peter Tiño
Indefinite Proximity Learning: A Review. Neural Comput. 27 (10) (2015)
Nikolaos Gianniotis, Sven Dennis Kügler, Peter Tiño, Kai Polsterer, Ranjeev Misra
Autoencoding Time Series for Visualisation. CoRR (2015)
Nikolaos Gianniotis, Sven Dennis Kügler, Peter Tiño, Kai Polsterer, Ranjeev Misra
Autoencoding time series for visualisation. ESANN (2015)
Abdessalam Elhabbash, Rami Bahsoon, Peter Tiño, Peter R. Lewis
Self-Adaptive Volunteered Services Composition through Stimulus- and Time-Awareness. ICWS (2015)
Fengzhen Tang, Peter Tiño, Pedro Antonio Gutiérrez, Huanhuan Chen
The Benefits of Modeling Slack Variables in SVMs. Neural Comput. 27 (4) (2015)
Frank-Michael Schleif, Andrej Gisbrecht, Peter Tiño
Large Scale Indefinite Kernel Fisher Discriminant. SIMBAD (2015)
Rafee T. Ibrahem, Peter Tiño, Richard J. Pearson, Trevor J. Ponman, Arif Babul
Automated Detection of Galaxy Groups Through Probabilistic Hough Transform. ICONIP (3) (2015)
Fengzhen Tang, Peter Tiño, Pedro Antonio Gutiérrez, Huanhuan Chen
Support Vector Ordinal Regression using Privileged Information. ESANN (2014)
Fengzhen Tang, Peter Tiño, Huanhuan Chen
Learning the deterministically constructed Echo State Networks. IJCNN (2014)
Huanhuan Chen, Peter Tiño, Xin Yao
Cognitive fault diagnosis in Tennessee Eastman Process using learning in the model space. Comput. Chem. Eng. 67 (2014)
Huanhuan Chen, Peter Tiño, Xin Yao
Efficient Probabilistic Classification Vector Machine With Incremental Basis Function Selection. IEEE Trans. Neural Networks Learn. Syst. 25 (2) (2014)
Yuan Shen, Stephen D. Mayhew, Zoe Kourtzi, Peter Tiño
Spatial-temporal modelling of fMRI data through spatially regularized mixture of hidden process models. NeuroImage 84 (2014)
Joseba Quevedo, Huanhuan Chen, Miquel A. Cugueró, Peter Tiño, Vicenç Puig, Diego García, Ramon Sarrate, Xin Yao
Combining learning in model space fault diagnosis with data validation/reconstruction: Application to the Barcelona water network. Eng. Appl. Artif. Intell. 30 (2014)
Frank-Michael Schleif, Peter Tiño, Thomas Villmann
Recent trends in learning of structured and non-standard data. ESANN (2014)
Abdessalam Elhabbash, Rami Bahsoon, Peter Tiño, Peter R. Lewis
A Utility Model for Volunteered Service Composition. UCC (2014)
Huanhuan Chen, Peter Tiño, Ali Rodan, Xin Yao
Learning in the Model Space for Cognitive Fault Diagnosis. IEEE Trans. Neural Networks Learn. Syst. 25 (1) (2014)
Abdessalam Elhabbash, Rami Bahsoon, Peter Tiño
Towards Self-Aware Service Composition. HPCC/CSS/ICESS (2014)
Pedro Antonio Gutiérrez, Peter Tiño, César Hervás-Martínez
Ordinal regression neural networks based on concentric hyperspheres. Neural Networks 59 (2014)
Jakub Mazgut, Peter Tiño, Mikael Bodén, Hong Yan
Dimensionality reduction and topographic mapping of binary tensors. Pattern Anal. Appl. 17 (3) (2014)
Phil Weber, Behzad Bordbar, Peter Tiño
A Framework for the Analysis of Process Mining Algorithms. IEEE Trans. Syst. Man Cybern. Syst. 43 (2) (2013)
Phil Weber, Behzad Bordbar, Peter Tiño
A principled approach to mining from noisy logs using Heuristics Miner. CIDM (2013)
Peter Tiño
Pushing for the Extreme: Estimation of Poisson Distribution from Low Count Unreplicated Data - How Close Can We Get? Entropy 15 (4) (2013)
Weishan Dong, Tianshi Chen, Peter Tiño, Xin Yao
Scaling Up Estimation of Distribution Algorithms for Continuous Optimization. IEEE Trans. Evol. Comput. 17 (6) (2013)
Alessio Micheli, Frank-Michael Schleif, Peter Tiño
Novel approaches in machine learning and computational intelligence. Neurocomputing 112 (2013)
Javier Sánchez-Monedero, Pedro Antonio Gutiérrez, Peter Tiño, César Hervás-Martínez
Exploitation of Pairwise Class Distances for Ordinal Classification. Neural Comput. 25 (9) (2013)
Boris Rudolf, Mária Markosová, Martin Cajági, Peter Tiño
Degree distribution and scaling in the Connecting Nearest Neighbors model CoRR (2013)
Huanhuan Chen, Fengzhen Tang, Peter Tiño, Xin Yao
Model-based kernel for efficient time series analysis. KDD (2013)
Peter Tiño, Ali Rodan
Short term memory in input-driven linear dynamical systems. Neurocomputing 112 (2013)
Shereen Fouad, Peter Tiño
Ordinal-based metric learning for learning using privileged information. IJCNN (2013)
Shuo Wang, Leandro L. Minku, Davide Ghezzi, Daniele Caltabiano, Peter Tiño, Xin Yao
Concept drift detection for online class imbalance learning. IJCNN (2013)
Yuan Shen, Stephen D. Mayhew, Zoe Kourtzi, Peter Tiño
A Spatial Mixture Approach to Inferring Sub-ROI Spatio-temporal Patterns from Rapid Event-Related fMRI Data. MICCAI (2) (2013)
Orla M. Doyle, Krasimira Tsaneva-Atanasova, James Michael Harte, Paul A. Tiffin, Peter Tiño, Vanessa Díaz-Zuccarini
Bridging Paradigms: Hybrid Mechanistic-Discriminative Predictive Models. IEEE Trans. Biomed. Eng. 60 (3) (2013)
Nikolay I. Nikolaev, Peter Tiño, Evgueni N. Smirnov
Time-dependent series variance learning with recurrent mixture density networks. Neurocomputing 122 (2013)
Peter Tiño, Siang Yew Chong, Xin Yao
Complex Coevolutionary Dynamics - Structural Stability and Finite Population Effects. IEEE Trans. Evol. Comput. 17 (2) (2013)
Shereen Fouad, Peter Tiño, Somak Raychaudhury, Petra Schneider
Incorporating Privileged Information Through Metric Learning. IEEE Trans. Neural Networks Learn. Syst. 24 (7) (2013)
Huanhuan Chen, Peter Tiño, Xin Yao, Ali Rodan
Learning in the Model Space for Fault Diagnosis CoRR (2012)
Shereen Fouad, Peter Tiño, Somak Raychaudhury, Petra Schneider
Learning Using Privileged Information in Prototype Based Models. ICANN (2) (2012)
Shereen Fouad, Peter Tiño
Prototype Based Modelling for Ordinal Classification. IDEAL (2012)

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Publication Activity (10 Years)

Top Topics

Top Venues

Peter Tiño