Haytham Elghazel

59 papers A* 3A 1B 10C 5Misc 1Journal 14Unranked 24

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Artificial Intelligence and Big Data in Social Media Analytics: A Comprehensive Review of Methods, Applications and Trends. ICAART (5) Hichem Dabbèchi, Nahla Haddar, Haytham Elghazel, Kais Haddar
2024	J	`jnl`	A new sentence embedding framework for the education and professional training domain with application to hierarchical multi-label text classification. Data Knowl. Eng. Guillaume Lefebvre, Haytham Elghazel, Théodore Guillet, Alexandre Aussem, Matthieu Sonnati
2024	J	`jnl`	Multi-View Majority Vote Learning Algorithms: Direct Minimization of PAC-Bayesian Bounds. CoRR Mehdi Hennequin, Abdelkrim Zitouni, Khalid Benabdeslem, Haytham Elghazel, Yacine Gaci
2024	J	`jnl`	PAC-Bayesian Domain Adaptation Bounds for Multi-view learning. CoRR Mehdi Hennequin, Khalid Benabdeslem, Haytham Elghazel
2023	C	`conf`	A New Time-Aware LSTM based Framework for Multi-label Classification on Healthcare Data. AICCSA Abdelhamid Gaddari, Haytham Elghazel, Rakia Jaziri, Mohand-Said Hacid, Pierre-Henri Comble
2023	B	`conf`	Accounting for Imputation Uncertainty During Neural Network Training. DaWaK Thomas Ranvier, Haytham Elghazel, Emmanuel Coquery, Khalid Benabdeslem
2023	Misc	`conf`	BERTEPro : A new Sentence Embedding Framework for the Education and Professional Training domain. SAC Guillaume Lefebvre, Haytham Elghazel, Théodore Guillet, Alexandre Aussem, Matthieu Sonnati
2023	—	`conf`	BERTEPro : Une nouvelle approche de représentation sémantique dans le domaine de l'éducation et de la formation professionnelle. EGC Guillaume Lefebvre, Haytham Elghazel, Théodore Guillet, Alexandre Aussem, Matthieu Sonnati
2023	—	`conf`	Classification multi-label de données médicales par LSTM temporel et clustering flou. EGC Abdelhamid Gaddari, Haytham Elghazel, Rakia Jaziri, Mohand-Saïd Hacid, Pierre-Henri Comble
2022	B	`conf`	Adversarial Multi - View Domain Adaptation for Regression. IJCNN Mehdi Hennequin, Khalid Benabdeslem, Haytham Elghazel
2022	—	`conf`	Autoencoder-Based Attribute Noise Handling Method for Medical Data. ICONIP (6) Thomas Ranvier, Haytham Elghazel, Emmanuel Coquery, Khalid Benabdeslem
2022	J	`jnl`	Autoencoder-based Attribute Noise Handling Method for Medical Data. CoRR Thomas Ranvier, Haytham Elghazel, Emmanuel Coquery, Khalid Benabdeslem
2022	B	`conf`	Localized Feature Ranking approach for Multi-Target Regression. IJCNN Hugo Bertrand, Haytham Elghazel, Sahar Masmoudi, Emmanuel Coquery, Mohand-Saïd Hacid
2022	—	`conf`	Multi-view Self-attention for Regression Domain Adaptation with Feature Selection. ICONIP (1) Mehdi Hennequin, Khalid Benabdeslem, Haytham Elghazel, Thomas Ranvier, Eric Michoux
2021	—	`conf`	Data-Efficient Information Extraction from Documents with Pre-trained Language Models. ICDAR Workshops (2) Clément Sage, Thibault Douzon, Alex Aussem, Véronique Eglin, Haytham Elghazel, Stefan Duffner, Christophe Garcia, Jérémy Espinas
2020	—	`conf`	End-to-End Extraction of Structured Information from Business Documents with Pointer-Generator Networks. SPNLP@EMNLP Clément Sage, Alex Aussem, Véronique Eglin, Haytham Elghazel, Jérémy Espinas
2020	B	`conf`	Identifying Conditionally Independent Target Subsets for Multi-Target Regression*Note: Sub-titles are not captured in Xplore and should not be used. ICTAI Orhan Yazar, Haytham Elghazel, Mohand-Saïd Hacid, Nathalie Castin
2020	C	`conf`	NoSQL Data Lake: A Big Data Source from Social Media. HIS Hichem Dabbèchi, Nahla Zaaboub Haddar, Haytham Elghazel, Kais Haddar
2020	C	`conf`	Social Media Data Integration: From Data Lake to NoSQL Data Warehouse. ISDA Hichem Dabbèchi, Nahla Zaaboub Haddar, Haytham Elghazel, Kais Haddar
2020	—	`conf`	Streaming Time Series Forecasting using Multi-Target Regression with Dynamic Ensemble Selection. IEEE BigData Dihia Boulegane, Albert Bifet, Haytham Elghazel, Giyyarpuram Madhusudan
2019	—	`conf`	Conditionally Decorrelated Multi-Target Regression. ICONIP (2) Orhan Yazar, Haytham Elghazel, Mohand-Said Hacid, Nathalie Castin
2019	A	`conf`	Recurrent Neural Network Approach for Table Field Extraction in Business Documents. ICDAR Clément Sage, Alexandre Aussem, Haytham Elghazel, Véronique Eglin, Jérémy Espinas
2017	—	`conf`	Dynamic Ensemble Selection with Probabilistic Classifier Chains. ECML/PKDD (1) Anil Narassiguin, Haytham Elghazel, Alex Aussem
2016	—	`conf`	A Semi-Supervised Ensemble Approach for Multi-label Learning. ICDM Workshops Ouadie Gharroudi, Haytham Elghazel, Alexandre Aussem
2016	J	`jnl`	An extensive empirical comparison of ensemble learning methods for binary classification. Pattern Anal. Appl. Anil Narassiguin, Mohamed Bibimoune, Haytham Elghazel, Alex Aussem
2016	J	`jnl`	Ensemble constrained Laplacian score for efficient and robust semi-supervised feature selection. Knowl. Inf. Syst. Khalid Benabdeslem, Haytham Elghazel, Mohammed M. Al-Hindawi
2016	J	`jnl`	Ensemble multi-label text categorization based on rotation forest and latent semantic indexing. Expert Syst. Appl. Haytham Elghazel, Alex Aussem, Ouadie Gharroudi, Wafa Saadaoui
2016	B	`conf`	Semi-supervised co-selection: Features and instances by a weighting approach. IJCNN Raywat Makkhongkaew, Khalid Benabdeslem, Haytham Elghazel
2016	—	`conf`	Similarity Tree Pruning: A Novel Dynamic Ensemble Selection Approach. ICDM Workshops Anil Narassiguin, Haytham Elghazel, Alex Aussem
2015	J	`jnl`	A hybrid algorithm for Bayesian network structure learning with application to multi-label learning. CoRR Maxime Gasse, Alex Aussem, Haytham Elghazel
2015	J	`jnl`	An Experimental Comparison of Hybrid Algorithms for Bayesian Network Structure Learning. CoRR Maxime Gasse, Alex Aussem, Haytham Elghazel
2015	—	`conf`	Calibrated k-labelsets for Ensemble Multi-label Classification. ICONIP (1) Ouadie Gharroudi, Haytham Elghazel, Alex Aussem
2015	B	`conf`	Ensemble Multi-label Classification: A Comparative Study on Threshold Selection and Voting Methods. ICTAI Ouadie Gharroudi, Haytham Elghazel, Alex Aussem
2015	A*	`conf`	On the Optimality of Multi-Label Classification under Subset Zero-One Loss for Distributions Satisfying the Composition Property. ICML Maxime Gasse, Alexandre Aussem, Haytham Elghazel
2015	J	`jnl`	Unsupervised feature selection with ensemble learning. Mach. Learn. Haytham Elghazel, Alex Aussem
2014	—	`conf`	A Comparison of Multi-Label Feature Selection Methods Using the Random Forest Paradigm. Canadian AI Ouadie Gharroudi, Haytham Elghazel, Alex Aussem
2014	J	`jnl`	A hybrid algorithm for Bayesian network structure learning with application to multi-label learning. Expert Syst. Appl. Maxime Gasse, Alex Aussem, Haytham Elghazel
2014	J	`jnl`	Different Aspects of Clustering The Self-Organizing Maps. Neural Process. Lett. Haytham Elghazel, Khalid Benabdeslem
2012	—	`conf`	A Relational-Based Approach for Aggregated Search in Graph Databases. DASFAA (1) Thanh-Huy Le, Haytham Elghazel, Mohand-Said Hacid
2012	J	`jnl`	A semi-supervised feature ranking method with ensemble learning. Pattern Recognit. Lett. Fazia Bellal, Haytham Elghazel, Alex Aussem
2012	—	`conf`	An Experimental Comparison of Hybrid Algorithms for Bayesian Network Structure Learning. ECML/PKDD (1) Maxime Gasse, Alex Aussem, Haytham Elghazel
2011	—	`conf`	A Graph Enrichment Based Clustering over Vertically Partitioned Data. ADMA (1) Khalid Benabdeslem, Brice Effantin, Haytham Elghazel
2011	—	`conf`	Aggregated Search in Graph Databases: Preliminary Results. GbRPR Haytham Elghazel, Mohand-Said Hacid
2011	—	`conf`	Graph Aggregation Based Image Modeling and Indexing for Video Annotation. CAIP (2) Najib Ben Aoun, Haytham Elghazel, Mohand-Said Hacid, Chokri Ben Amar
2011	A*	`conf`	Semi-supervised Feature Importance Evaluation with Ensemble Learning. ICDM Hasna Barkia, Haytham Elghazel, Alex Aussem
2011	—	`ch.`	Trading-Off Diversity and Accuracy for Optimal Ensemble Tree Selection in Random Forests. Ensembles in Machine Learning Applications Haytham Elghazel, Alex Aussem, Florence Perraud
2010	—	`conf`	A Graph Based Framework for Clustering and Characterization of SOM. ICANN (3) Rakia Jaziri, Khalid Benabdeslem, Haytham Elghazel
2010	B	`conf`	Consensus clustering by graph based approach. ESANN Haytham Elghazel, Khalid Benabdeslem, Fatma Hamdi
2010	A*	`conf`	Feature Selection for Unsupervised Learning Using Random Cluster Ensembles. ICDM Haytham Elghazel, Alex Aussem
2009	C	`conf`	McSOM: Minimal Coloring of Self-Organizing Map. ADMA Haytham Elghazel, Khalid Benabdeslem, Hamamache Kheddouci
2009	—	`conf`	Towards B-Coloring of SOM. MLDM Haytham Elghazel, Khalid Benabdeslem
2008	J	`jnl`	A Graph b-coloring Framework for Data Clustering. J. Math. Model. Algorithms Haytham Elghazel, Hamamache Kheddouci, Véronique Deslandres, Alain Dussauchoy
2008	B	`conf`	An Integrated Graph and Probability Based Clustering Framework for Sequential Data. Discovery Science Haytham Elghazel, Tetsuya Yoshida, Mohand-Said Hacid
2007	—	`conf`	A New Greedy Algorithm for Improving b-Coloring Clustering. GbRPR Haytham Elghazel, Tetsuya Yoshida, Véronique Deslandres, Mohand-Said Hacid, Alain Dussauchoy
2007	B	`conf`	A Partially Dynamic Clustering Algorithm for Data Insertion and Removal. Discovery Science Haytham Elghazel, Hamamache Kheddouci, Véronique Deslandres, Alain Dussauchoy
2007	—	`conf`	Clinical pathway analysis using graph-based approach and Markov models. ICDIM Haytham Elghazel, Véronique Deslandres, Kassem Kallel, Alain Dussauchoy
2007	B	`conf`	Constrained Graph b-Coloring Based Clustering Approach. DaWaK Haytham Elghazel, Khalid Benabdeslem, Alain Dussauchoy
2006	C	`conf`	A New Clustering Approach for Symbolic Data and Its Validation: Application to the Healthcare Data. ISMIS Haytham Elghazel, Véronique Deslandres, Mohand-Said Hacid, Alain Dussauchoy, Hamamache Kheddouci
2006	—	`conf`	A New Clustering Approach for Symbolic Data: Algorithms and Application to Healthcare Data. BDA Haytham Elghazel, Mohand-Said Hacid, Hamamache Kheddouci, Alain Dussauchoy