P. Pintelas

发表

Logitboost of Simple Bayesian Classifier

Sotiris B. Kotsiantis, Panayiotis E. Pintelas, S. Kotsiantis, 2005, Informatica.

EVALUATING AND IMPROVING EDUCATIONAL MATERIAL AND TUTORING ASPECTS OF DISTANCE LEARNING SYSTEMS

Panayiotis E. Pintelas, Christos Pierrakeas, Michalis Xenos, 2003 .

Combining Classification and Model Trees for Handling Ordinal Problems

P. Pintelas, D. Anyfantis, M. K. S. B. Kotsiantis, 2007 .

A nearly exact method for solving large-scale TRS

D. G. Sotiropoulos, M. S. Apostolopoulou, C. Botsaris, 2009, 2009 7th IEEE International Conference on Industrial Informatics.

On Constructing a Financial Decision Support System

S. Kotsiantis, V. Tampakas, P. Pintelas, 2005 .

A 2-BFGS updating in a trust region framework

D. G. Sotiropoulos, M. S. Apostolopoulou, P. Pintelas, 2007 .

Towards a generic Multi-Agent Architecture of ComputerBased Medical Education applications

G. Nikiforidis, A. Kameas, G. Kagadis, 2000 .

Predicting anxiety disorders and suicide tendency using machine learning: a review

Theodore Kotsilieris, Ioannis E. Livieris, Panayiotis E. Pintelas, 2020, Int. J. Medical Eng. Informatics.

tutoring aspects of Distance Learning Systems

Panayiotis E. Pintelas, Christos Pierrakeas, Michalis Xenos, 2003 .

Predicting Protein Localization Sites Using an Ensemble Self-Labeled Framework

Emmanuel G. Pintelas, P. Pintelas, 2018, Biomedical Journal of Scientific & Technical Research.

Peach Summer School 2007 Extended Abstract : Presence in stressful environments

T. Mikropoulos, P. Pintelas, Ioannis Vrellis, 2008 .

An Auto-Adjustable Semi-Supervised Self-Training Algorithm

Panayiotis E. Pintelas, Andreas Kanavos, Ioannis E. Livieris, 2018, Algorithms.

PREDICTING STUDENTS' PERFORMANCE IN DISTANCE LEARNING USING MACHINE LEARNING TECHNIQUES

Sotiris B. Kotsiantis, Panayiotis E. Pintelas, Christos Pierrakeas, 2004, Appl. Artif. Intell..

Local dagging of decision stumps for regression and classification problems

D.S. Anyfantis, M.G. Karagiannopoulos, S.B. Kotsiantis, 2007, 2007 Mediterranean Conference on Control & Automation.

A Fast Ensemble of Regressors

Panayiotis E. Pintelas, Sotiris Kotsiantis, M. Karagiannopoulos, 2007 .

Local Additive Regression of Decision Stumps

Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Panayiotis E. Pintelas, 2006, SETN.

Local Boosting of Decision Stumps for Regression and Classification Problems

Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Panayiotis E. Pintelas, 2006, J. Comput..

Machine learning: a review of classification and combining techniques

Sotiris B. Kotsiantis, Panayiotis E. Pintelas, Ioannis D. Zaharakis, 2006, Artificial Intelligence Review.

Preventing Student Dropout in Distance Learning Using Machine Learning Techniques

Sotiris B. Kotsiantis, Panayiotis E. Pintelas, Christos Pierrakeas, 2003, KES.

An Ensemble-Based Semi-Supervised Approach for Predicting Students’ Performance

Tassos A. Mikropoulos, Ioannis E. Livieris, Panayiotis E. Pintelas, 2018 .

Gender Recognition by Voice using an Improved Self-Labeled Algorithm

Ioannis E. Livieris, Emmanuel Pintelas, Panayiotis E. Pintelas, 2019, Mach. Learn. Knowl. Extr..

Classification of Large Biomedical Data Using ANNs Based on BFGS Method

Panayiotis E. Pintelas, Spyros Sioutas, Ioannis E. Livieris, 2009, 2009 13th Panhellenic Conference on Informatics.

Weight-Constrained Neural Networks in Forecasting Tourist Volumes: A Case Study

Theodore Kotsilieris, Ioannis E. Livieris, Emmanuel Pintelas, 2019, Electronics.

Handling imbalanced datasets: A review

Dimitris Kanellopoulos, Panayiotis E. Pintelas, Sotiris Kotsiantis, 2006 .

Data Preprocessing for Supervised Leaning

Dimitris Kanellopoulos, Panayiotis E. Pintelas, Sotiris Kotsiantis, 2007 .

A Grey-Box Ensemble Model Exploiting Black-Box Accuracy and White-Box Intrinsic Interpretability

Ioannis E. Livieris, Panayiotis E. Pintelas, Emmanuel G. Pintelas, 2020, Algorithms.

A novel explainable image classification framework: case study on skin cancer and plant disease prediction

Sotiris Kotsiantis, Ioannis E. Livieris, Panagiotis Pintelas, 2021, Neural Computing and Applications.

A CNN–LSTM model for gold price time-series forecasting

Ioannis E. Livieris, Panagiotis Pintelas, Emmanuel Pintelas, 2020, Neural Computing and Applications.

A review of machine learning prediction methods for anxiety disorders

Panayiotis E. Pintelas, Theodore Kotsilieris, Ioannis E. Livieris, 2018, DSAI.

Predicting Secondary Structure for Human Proteins Based on Chou-Fasman Method

Panayiotis E. Pintelas, Andreas Kanavos, Ioannis E. Livieris, 2019, AIAI.

Feature Selection for Regression Problems

M. Karagiannopoulos, D. Anyfantis, P. E. Pintelas, 2007 .

Local voting of weak classifiers

Sotiris B. Kotsiantis, Panayiotis E. Pintelas, S. Kotsiantis, 2005, Int. J. Knowl. Based Intell. Eng. Syst..

Local Bagging of Decision Stumps

Sotiris B. Kotsiantis, Panayiotis E. Pintelas, George E. Tsekouras, 2005, IEA/AIE.

Restartings: A Technique to Improve Classic Genetic Algorithms' Performance

Panayiotis E. Pintelas, Grigorios N. Beligiannis, Georgios A. Tsirogiannis, 2007, International Conference on Computational Intelligence.

"Intuition" Operator: Providing Genomes with Reason

Panayiotis E. Pintelas, Grigorios N. Beligiannis, Georgios A. Tsirogiannis, 2007, International Conference on Computational Intelligence.

Combining Bagging and Boosting

Panayiotis E. Pintelas, Sotiris Kotsiantis, S. Kotsiantis, 2007 .

A practical method for solving large-scale TRS

Panayiotis E. Pintelas, D. G. Sotiropoulos, M. S. Apostolopoulou, 2011, Optim. Lett..

Solving the quadratic trust-region subproblem in a low-memory BFGS framework

Panayiotis E. Pintelas, D. G. Sotiropoulos, M. S. Apostolopoulou, 2008, Optim. Methods Softw..

Predicting students marks in Hellenic Open University

Sotiris B. Kotsiantis, Panayiotis E. Pintelas, S. Kotsiantis, 2005, Fifth IEEE International Conference on Advanced Learning Technologies (ICALT'05).

A survey on student dropout rates and dropout causes concerning the students in the Course of Informatics of the Hellenic Open University

Panayiotis E. Pintelas, Michalis Nik Xenos, Christos Pierrakeas, 2002, Comput. Educ..

EVALUATING AND IMPROVING EDUCATIONAL MATERIAL AND TUTORING ASPECTS OF DISTANCE LEARNING SYSTEMS

M. Xenos, C. Pierrakeas, P. Pintelas, 2003 .

Comparative study and categorization of high-level petri nets

Panayiotis E. Pintelas, Achilles Kameas, Vassilis C. Gerogiannis, 1998, J. Syst. Softw..

Explainable Machine Learning Framework for Image Classification Problems: Case Study on Glioma Cancer Prediction

Ioannis E. Livieris, Panagiotis Pintelas, Sotiris Kotsiantis, 2020, J. Imaging.

Forecasting stock price index movement using a constrained deep neural network training algorithm

Panayiotis E. Pintelas, Theodore Kotsilieris, Ioannis E. Livieris, 2020, Intell. Decis. Technol..

A dropout weight-constrained recurrent neural network model for forecasting the price of major cryptocurrencies and CCi30 index

Theodore Kotsilieris, Ioannis E. Livieris, Panagiotis Pintelas, 2021, Evol. Syst..

Mixture of Expert Agents for Handling Imbalanced Data Sets

Panayiotis E. Pintelas, Sotiris Kotsiantis, S. Kotsiantis, 2003 .

Investigating the Problem of Cryptocurrency Price Prediction: A Deep Learning Approach

Theodore Kotsilieris, Ioannis E. Livieris, Panagiotis Pintelas, 2020, AIAI.

Ontology-based Learning Applications: A Development Methodology

Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Panayiotis E. Pintelas, 2006, IASTED Conf. on Software Engineering.

A descent hybrid conjugate gradient method based on the memoryless BFGS update

P. Pintelas, I. Livieris, V. Tampakas, 2018, Numerical Algorithms.

A versatile Kernel proposal for a multimicroprocessor system environment

Mike P. Papazpglou, Panayotis Pintelas, M. Papazoglou, 1988, Microprocess. Microprogramming.

A hierarchical multimicroprocessor system for object oriented languages

Mike Papazoglou, Panayotis Pintelas, M. Papazoglou, 1987 .

Special Issue on Ensemble Learning and Applications

Panayiotis E. Pintelas, Ioannis E. Livieris, P. Pintelas, 2020, Algorithms.

A decision support prototype tool for predicting student performance in an ODL environment

Sotiris B. Kotsiantis, Panayiotis E. Pintelas, S. Kotsiantis, 2004, Interact. Technol. Smart Educ..

On ensemble techniques of weight-constrained neural networks

Ioannis E. Livieris, Panagiotis Pintelas, Lazaros Iliadis, 2020, Evolving Systems.

Increasing the Classification Accuracy of Simple Bayesian Classifier

Sotiris B. Kotsiantis, Panayiotis E. Pintelas, S. Kotsiantis, 2004, AIMSA.

MeT: The expert methodology tutor of GENITOR

Panayiotis E. Pintelas, Achilles Kameas, Ioannis D. Zaharakis, 1994, Microprocess. Microprogramming.

Microprocessing and Microprogramming Met: the Expert Methodology Tutor of Genitor

A. Kameas, P. Pintelas, 2022 .

Bagging Model Trees for Classification Problems

Sotiris B. Kotsiantis, Panayiotis E. Pintelas, George E. Tsekouras, 2005, Panhellenic Conference on Informatics.

An Integrated Environment for Building Distributed Multi-agent Educational Applications

Panayiotis E. Pintelas, Tasos Triantis, P. Pintelas, 2004, AIMSA.

A Cost Sensitive Technique for Ordinal Classification Problems

Sotiris B. Kotsiantis, Panayiotis E. Pintelas, S. Kotsiantis, 2004, SETN.

A Weighted Voting Ensemble Self-Labeled Algorithm for the Detection of Lung Abnormalities from X-Rays

Panayiotis E. Pintelas, Andreas Kanavos, Ioannis E. Livieris, 2019, Algorithms.

A Convolutional Autoencoder Topology for Classification in High-Dimensional Noisy Image Datasets

Panayiotis E. Pintelas, Ioannis E. Livieris, Emmanuel G. Pintelas, 2021, Sensors.

Robustness of learning techniques in handling class noise in imbalanced datasets

Sotiris B. Kotsiantis, Panayiotis E. Pintelas, M. Karagiannopoulos, 2007, AIAI.

A new conjugate gradient algorithm for training neural networks based on a modified secant equation

Panayiotis E. Pintelas, Ioannis E. Livieris, P. Pintelas, 2013, Appl. Math. Comput..

An Improved spectral conjugate Gradient Neural Network Training Algorithm

Panayiotis E. Pintelas, Ioannis E. Livieris, P. Pintelas, 2012, Int. J. Artif. Intell. Tools.

On Ensemble SSL Algorithms for Credit Scoring Problem

Panayiotis E. Pintelas, Andreas Kanavos, Ioannis E. Livieris, 2018, Informatics.

An adaptive nonmonotone active set - weight constrained - neural network training algorithm

Ioannis E. Livieris, Panayiotis E. Pintelas, P. Pintelas, 2019, Neurocomputing.

Improving the evaluation process of students’ performance utilizing a decision support software

T. Kotsilieris, P. Pintelas, I. Livieris, 2018, Neural Computing and Applications.

Selective costing ensemble for handling imbalanced data sets

Sotiris B. Kotsiantis, Panayiotis E. Pintelas, S. Kotsiantis, 2009, Int. J. Hybrid Intell. Syst..

Predicting anxiety disorders and suicide tendency using machine learning: a review

Emmanuel G. Pintelas, T. Kotsilieris, P. Pintelas, 2020, Int. J. Medical Eng. Informatics.

Bagging Random Trees for Estimation of Tissue Softness

Sotiris B. Kotsiantis, Panayiotis E. Pintelas, George E. Tsekouras, 2005, MLDM.

Globally convergent modified Perry's conjugate gradient method

Panayiotis E. Pintelas, Ioannis E. Livieris, P. Pintelas, 2012, Appl. Math. Comput..

Assessing Supervised Machine Learning Techniques for Predicting Student Learning Preferences

Sotiris Kotsiantis, I. D. Zaharakis, P. E. Pintelas, 2002 .

A Hybrid Decision Support Tool - Using Ensemble of Classifiers

Sotiris B. Kotsiantis, Panayiotis E. Pintelas, S. Kotsiantis, 2004, ICEIS.

Detecting Lung Abnormalities From X-rays Using an Improved SSL Algorithm

Panayiotis E. Pintelas, Andreas Kanavos, Ioannis E. Livieris, 2019, BRAINS/WS-AFFIN@AmI.

A modified Perry conjugate gradient method and its global convergence

Panayiotis E. Pintelas, Ioannis E. Livieris, P. Pintelas, 2015, Optim. Lett..

An Ensemble SSL Algorithm for Efficient Chest X-Ray Image Classification

Panayiotis E. Pintelas, Andreas Kanavos, Ioannis E. Livieris, 2018, J. Imaging.

Decision Support Software for Forecasting Patient's Length of Stay

Panayiotis E. Pintelas, Theodore Kotsilieris, Ioannis E. Livieris, 2018, Algorithms.

Fuzzy Clustering of Categorical Attributes and its Use in Analyzing Cultural Data

Sotiris B. Kotsiantis, Panayiotis E. Pintelas, George E. Tsekouras, 2007, International Conference on Computational Intelligence.

A new class of nonmonotone conjugate gradient training algorithms

Panayiotis E. Pintelas, Ioannis E. Livieris, P. Pintelas, 2015, Appl. Math. Comput..

A decision support system for predicting students’ performance

Tassos A. Mikropoulos, Ioannis E. Livieris, Panayiotis E. Pintelas, 2016 .

Bagged Voting Ensembles

Sotiris B. Kotsiantis, Panayiotis E. Pintelas, S. Kotsiantis, 2004, AIMSA.

Combining Bagging and Boosting

P. Pintelas, S. B. Kotsiantis, 2022 .