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Aghiles Salah
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2020 – today
- 2024
- [c16]Lazhar Labiod
, Mohamed Nadif
, Aghiles Salah
:
WSDM 2024 Workshop on Representation Learning & Clustering. WSDM 2024: 1214-1215 - 2023
- [c15]Pablo Montalvo
, Aghiles Salah
:
Learning to Infer Product Attribute Values From Descriptive Texts and Images. WSDM 2023: 1293-1294 - [c14]Valeria Fionda
, Olaf Hartig
, Reyhaneh Abdolazimi
, Sihem Amer-Yahia, Hongzhi Chen
, Xiao Chen
, Peng Cui, Jeffrey Dalton
, Xin Luna Dong
, Lisette Espín-Noboa
, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Küçük-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei
, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne Trippas
, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang
, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang
, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu:
Tutorials at The Web Conference 2023. WWW (Companion Volume) 2023: 648-658 - 2022
- [j6]Mickael Febrissy, Aghiles Salah, Melissa Ailem, Mohamed Nadif:
Improving NMF clustering by leveraging contextual relationships among words. Neurocomputing 495: 105-117 (2022) - [i1]Aloïs de La Comble, Anuvabh Dutt, Pablo Montalvo, Aghiles Salah:
Multi-Modal Attribute Extraction for E-Commerce. CoRR abs/2203.03441 (2022) - 2021
- [j5]Quoc-Tuan Truong
, Aghiles Salah, Thanh-Binh Tran
, Jingyao Guo, Hady W. Lauw
:
Exploring Cross-Modality Utilization in Recommender Systems. IEEE Internet Comput. 25(4): 50-57 (2021) - [c13]Aghiles Salah, Thanh-Binh Tran, Hady W. Lauw
:
Towards Source-Aligned Variational Models for Cross-Domain Recommendation. RecSys 2021: 176-186 - [c12]Quoc-Tuan Truong, Aghiles Salah, Hady W. Lauw
:
Multi-Modal Recommender Systems: Hands-On Exploration. RecSys 2021: 834-837 - [c11]Quoc-Tuan Truong, Aghiles Salah, Hady W. Lauw
:
Bilateral Variational Autoencoder for Collaborative Filtering. WSDM 2021: 292-300 - 2020
- [j4]Aghiles Salah, Quoc-Tuan Truong, Hady W. Lauw:
Cornac: A Comparative Framework for Multimodal Recommender Systems. J. Mach. Learn. Res. 21: 95:1-95:5 (2020)
2010 – 2019
- 2019
- [j3]Aghiles Salah, Mohamed Nadif
:
Directional co-clustering. Adv. Data Anal. Classif. 13(3): 591-620 (2019) - 2018
- [c10]Aghiles Salah, Melissa Ailem, Mohamed Nadif:
Word Co-Occurrence Regularized Non-Negative Matrix Tri-Factorization for Text Data Co-Clustering. AAAI 2018: 3992-3999 - [c9]Aghiles Salah, Hady W. Lauw
:
A Bayesian Latent Variable Model of User Preferences with Item Context. IJCAI 2018: 2667-2674 - [c8]Aghiles Salah, Hady W. Lauw:
Probabilistic Collaborative Representation Learning for Personalized Item Recommendation. UAI 2018: 998-1008 - 2017
- [j2]Aghiles Salah
, Mohamed Nadif
:
Social regularized von Mises-Fisher mixture model for item recommendation. Data Min. Knowl. Discov. 31(5): 1218-1241 (2017) - [c7]Aghiles Salah, Melissa Ailem, Mohamed Nadif:
A Way to Boost Semi-NMF for Document Clustering. CIKM 2017: 2275-2278 - [c6]Aghiles Salah, Mohamed Nadif:
Model-based von Mises-Fisher Co-clustering with a Conscience. SDM 2017: 246-254 - [c5]Melissa Ailem, Aghiles Salah, Mohamed Nadif:
Non-negative Matrix Factorization Meets Word Embedding. SIGIR 2017: 1081-1084 - 2016
- [b1]Aghiles Salah:
Von Mises-Fisher based (co-)clustering for high-dimensional sparse data : application to text and collaborative filtering data. (Modèles de mélange de von Mises-Fisher pour la classification simple et croisée de données éparses de grande dimension). Paris Descartes University, France, 2016 - [j1]Aghiles Salah, Nicoleta Rogovschi, Mohamed Nadif
:
A dynamic collaborative filtering system via a weighted clustering approach. Neurocomputing 175: 206-215 (2016) - [c4]Aghiles Salah, Nicoleta Rogovschi, Mohamed Nadif:
Model-based Co-clustering for High Dimensional Sparse Data. AISTATS 2016: 866-874 - [c3]Aghiles Salah, Nicoleta Rogovschi, Mohamed Nadif
:
Stochastic Co-clustering for Document-Term Data. SDM 2016: 306-314 - 2015
- [c2]Aghiles Salah, Nicoleta Rogovschi, François Role, Mohamed Nadif:
Pour une meilleure exploitation de la classification croisée dans les systèmes de filtrage collaboratif. EGC 2015: 347-358 - [c1]Aghiles Salah, Nicoleta Rogovschi, Mohamed Nadif:
An Efficient Incremental Collaborative Filtering System. ICONIP (3) 2015: 375-383
Coauthor Index
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last updated on 2024-08-21 20:27 CEST by the dblp team
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