Can educational data mining predict student performance and enhance personalized learning? | The Thomas B. Fordham Institute
AN IMPROVED SPECTRAL CONJUGATE GRADIENT NEURAL NETWORK TRAINING ALGORITHM
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Ioannis E. Livieris - Home Page
Smoothing and stationarity enforcement framework for deep learning time-series forecasting | Request PDF
Ioannis LIVIERIS | Senior Researcher | PhD | University of Patras, Pátra | UP | Department of Mathematics
PDF) An Advanced Conjugate Gradient Training Algorithm Based on a Modified Secant Equation | Panagiotis E Pintelas - Academia.edu
PDF) A decision support system for predicting students' performance
PDF) A new class of spectral conjugate gradient methods based on a modified secant equation for unconstrained optimization | Panagiotis E Pintelas - Academia.edu
Automatic classification of solitary pulmonary nodules in PET/CT imaging employing transfer learning techniques,Medical & Biological Engineering & Computing - X-MOL
Algorithms | Free Full-Text | Decision Support Software for Forecasting Patient's Length of Stay | HTML
An Ensemble-Based Semi-Supervised Approach for Predicting Students' Performance
IRJET- Students Performance Prediction through Educational Data Mining - An Uncomplicated Review by IRJET Journal - issuu
Ioannis E. Livieris - Home Page
Ensemble Algorithms and Their Applications: Pintelas, Panagiotis, Livieris, Ioannis E: 9783039369584: Amazon.com: Books
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Ensemble Algorithms and Their Applications: Pintelas, Panagiotis, Livieris, Ioannis E: 9783039369584: Amazon.com: Books
Engineering Applications of Neural Networks | springerprofessional.de
A hybrid conjugate gradient method based on the self-scaled memoryless BFGS update
An adaptive nonmonotone active set – weight constrained – neural network training algorithm - ScienceDirect
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PDF) Forecasting Economy-Related Data Utilizing Weight-Constrained Recurrent Neural Networks
Research Article An Advanced Conjugate Gradient Training Algorithm Based on a Modified Secant Equation
A CNN–LSTM model for gold price time-series forecasting | springerprofessional.de
