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Nicholas Ampazis
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2020 – today
- 2024
- [c16]Nicholas Ampazis:
Improving RAG Quality for Large Language Models with Topic-Enhanced Reranking. AIAI (2) 2024: 74-87 - 2020
- [j13]Flora Sakketou, Nicholas Ampazis:
A constrained optimization algorithm for learning GloVe embeddings with semantic lexicons. Knowl. Based Syst. 195: 105628 (2020)
2010 – 2019
- 2019
- [j12]Nicholas Ampazis, Theodoros Emmanouilidis, Flora Sakketou:
A Matrix Factorization Algorithm for Efficient Recommendations in Social Rating Networks Using Constrained Optimization. Mach. Learn. Knowl. Extr. 1(3): 928-944 (2019) - [c15]Flora Sakketou, Nicholas Ampazis:
On the Invariance of the SELU Activation Function on Algorithm and Hyperparameter Selection in Neural Network Recommenders. AIAI 2019: 673-685 - [c14]Flora Sakketou, Nicholas Ampazis:
A Hessian Free Neural Networks Training Algorithm with Curvature Scaled Adaptive Momentum. LION 2019: 94-105 - 2018
- [c13]Flora Sakketou, Nicholas Ampazis, Dimosthenis Drivaliaris:
Generating Recommendations by Graph Traversal in Social Rating Networks. SETN 2018: 15:1-15:7 - 2015
- [j11]Nikolaos Ampazis, Stavros J. Perantonis, Dimosthenis Drivaliaris:
Improved Jacobian Eigen-Analysis Scheme for Accelerating Learning in Feedforward Neural Networks. Cogn. Comput. 7(1): 86-102 (2015) - [j10]Nicholas Ampazis, Theodoros Emmanouilidis:
FALCON: A matrix factorization framework for recommender systems using constrained optimization. Intell. Decis. Technol. 9(3): 221-232 (2015) - [j9]Nicholas Ampazis:
Forecasting Demand in Supply Chain Using Machine Learning Algorithms. Int. J. Artif. Life Res. 5(1): 56-73 (2015) - [c12]Tao Ye, Danny Bickson, Nicholas Ampazis, András A. Benczúr:
LSRS'15: Workshop on Large-Scale Recommender Systems. RecSys 2015: 349-350 - 2014
- [c11]Ioannis G. Sideratos, Agapios N. Platis, Vasilis P. Koutras, Nicholas Ampazis:
Reliability Analysis of a Two-Stage Goel-Okumoto and Yamada S-shaped Model. DepCoS-RELCOMEX 2014: 393-402 - [c10]Nicholas Ampazis, Theodoros Emmanouilidis:
Exploring Semantic Features for Producing Top-N Recommendation Lists from Binary User Feedback. SemWebEval@ESWC 2014: 157-162 - [c9]Theopi Eleftheriadou, Nikolaos Ampazis, Vasilios P. Androvitsaneas, Ioannis F. Gonos, Georgios Dounias, Ioannis A. Stathopulos:
Ground Resistance Estimation Using Feed-Forward Neural Networks, Linear Regression and Feature Selection Models. SETN 2014: 418-429 - 2013
- [j8]Nicholas Ampazis, Stavros J. Perantonis:
An Efficient Constrained Learning Algorithm for Stable 2D IIR Filter Factorization. Adv. Artif. Neural Syst. 2013: 292567:1-292567:7 (2013) - 2010
- [c8]Nicholas Ampazis:
Large Scale Problem Solving with Neural Networks: The Netflix Prize Case. ICANN (3) 2010: 429-434 - [c7]Nikolaos Ampazis, Nikolaos D. Alexopoulos:
Prediction of Aircraft Aluminum Alloys Tensile Mechanical Properties Degradation Using Support Vector Machines. SETN 2010: 9-18
2000 – 2009
- 2008
- [c6]S. Lalas, Nikolaos Ampazis, Athanasios Tsakonas, Georgios Dounias, K. Vemmos:
Modeling Stroke Diagnosis with the Use of Intelligent Techniques. SETN 2008: 352-358 - 2007
- [c5]Nikolaos Ampazis, Helen Iakovaki, Georgios Dounias:
Author Identification of E-mail Messages with OLMAM Trained Feedforward Neural Networks. ICTAI (2) 2007: 413-417 - 2004
- [j7]Nikolaos Ampazis, Ioannis Minis:
Design of cellular manufacturing systems using Latent Semantic Indexing and Self Organizing Maps. Comput. Manag. Sci. 1(3-4): 275-292 (2004) - [j6]Nikolaos Ampazis, Stavros J. Perantonis:
LSISOM - A Latent Semantic Indexing Approach to Self-Organizing Maps of Document Collections. Neural Process. Lett. 19(2): 157-173 (2004) - [c4]Nikolaos Ampazis, Georgios Dounias, Jan Jantzen:
Pap-Smear Classification Using Efficient Second Order Neural Network Training Algorithms. SETN 2004: 230-245 - 2002
- [j5]Nikolaos Ampazis, Stavros J. Perantonis:
Two highly efficient second-order algorithms for training feedforward networks. IEEE Trans. Neural Networks 13(5): 1064-1074 (2002) - 2001
- [j4]Nikolaos Ampazis, Stavros J. Perantonis, John G. Taylor:
A dynamical model for the analysis and acceleration of learning in feedforward networks. Neural Networks 14(8): 1075-1088 (2001) - 2000
- [j3]Stavros J. Perantonis, Nikolaos Ampazis, Vassilis Virvilis:
A Learning Framework for Neural Networks Using Constrained Optimization Methods. Ann. Oper. Res. 99(1-4): 385-401 (2000) - [c3]Nikolaos Ampazis, Stavros J. Perantonis:
Levenberg-Marquardt Algorithm with Adaptive Momentum for the Efficient Training of Feedforward Networks. IJCNN (1) 2000: 126-131 - [c2]Stavros J. Perantonis, Nikolaos Ampazis, S. Spirou:
Training Feedforward Neural Networks with the Dogleg Method and BFGS Hessian Updates. IJCNN (1) 2000: 138-145
1990 – 1999
- 1999
- [j2]Nikolaos Ampazis, Stavros J. Perantonis, John G. Taylor:
Dynamics of multilayer networks in the vicinity of temporary minima. Neural Networks 12(1): 43-58 (1999) - [c1]Nikolaos Ampazis, Stavros J. Perantonis, John G. Taylor:
Acceleration of learning in feedforward networks using dynamical systems analysis and matrix perturbation theory. IJCNN 1999: 1850-1855 - 1998
- [j1]Stavros J. Perantonis, Nikolaos Ampazis, Stavros Varoufakis, George Antoniou:
Constrained Learning in Neural Networks: Application to Stable Factorization of 2-D Polynomials. Neural Process. Lett. 7(1): 5-14 (1998)
Coauthor Index
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