Aghiles Salah

Rakuten RIT

aghiles.salah@rakuten.com

I am a Research Scientist in machine learning at Rakuten Institute of Technology. I am broadly interested in machine learning under a Probabilistic/Bayesian approach, including generative models, approximate inference & learning, as well as their applications in information retrieval, natural language processing, computer vision and other related topics.

I am also leading development of Cornac, which is a Python Framework for Multimodal Recommender Systems.

Publications

2021

Towards Source-Aligned Variational Models for Cross-Domain Recommendation
Aghiles Salah, Thanh Binh Tran, Hady W. Lauw
ACM International Conference on Recommender Systems (RecSys). 2021
Paper | Code

Bilateral Variational Autoencoder for Collaborative Filtering
Quoc-Tuan Truong, Aghiles Salah, Hady W. Lauw
ACM International Conference on Web Search and Data Mining (WSDM). 2021
Paper | Code

Exploring Cross-Modality Utilization in Recommender Systems
Quoc-Tuan Truong, Aghiles Salah, Thanh Binh Tran, Jingyao Guo, Hady W. Lauw
IEEE Internet Computing, Vol. 25, No. 4, pp. 50-57.. 2021
Paper | Code

Multi-Modal Recommender Systems: Hands-On Exploration
Quoc-Tuan Truong, Aghiles Salah, Hady W. Lauw
ACM International Conference on Recommender Systems (RecSys). 2021
Paper | Code

2020

Cornac: A Comparative Framework for Multimodal Recommender Systems
Aghiles Salah, Quoc-Tuan Truong, Hady W. Lauw
Journal of Machine Learning Research (JMLR). 2020
Paper | Code | Website

2019

Directional co-clustering
Aghiles Salah, Mohamed Nadif
Advances in Data Analysis and Classification, 13(3): 591–620. 2019
Paper | Code

2018

Probabilistic Collaborative Representation Learning for Personalized Item Recommendation
Aghiles Salah, Hady W. Lauw
Uncertainty in Artificial Intelligence (UAI), 2018
Paper | Code

A Bayesian Latent Variable Model of User Preferences with Item Context
Aghiles Salah, Hady W. Lauw
International Joint Conference on Artificial Intelligence (IJCAI), pages 2667–2674, 2018
Paper | Code | Blog

Word Co-Occurrence Regularized Non-Negative Matrix Tri-Factorization for Text Data Co-Clustering
Aghiles Salah, Ailem Melissa, Mohamed Nadif
International Conference on Artificial Intelligence (AAAI), 2018
Paper

2017

A Way to Boost Semi-NMF for Document Clustering
Aghiles Salah, Ailem Melissa, Mohamed Nadif
International Conference on Information and Knowledge Management (CIKM), pages 2275–2278, 2017
Paper

Non-negative Matrix Factorization Meets Word Embedding
Ailem Melissa, Aghiles Salah, Mohamed Nadif
International Conference on Research and Development in Information Retrieval (SIGIR), pages 1081–1084, 2017
Paper

Model-based von Mises-Fisher Co-clustering with a Conscience
Aghiles Salah, Mohamed Nadif
SIAM International Conference on Data Mining (SDM), pages 246–254, 2017
Paper | Code

Social regularized von Mises-Fisher mixture model for item recommendation
Aghiles Salah, Mohamed Nadif
Data Mining and Knowledge Discovery, 31(5): 1218–1241. 2017
Paper

2016

Model-based Co-clustering for High Dimensional Sparse Data
Aghiles Salah, Nicoleta Rogovschi, Mohamed Nadif
International Conference on Artificial Intelligence and Statistics (AISTATS), pages 866–874, 2016
Paper | Code

Stochastic Co-clustering for Document-Term Data
Aghiles Salah, Nicoleta Rogovschi, Mohamed Nadif
SIAM International Conference on Data Mining (SDM), pages 306–314, 2016
Paper | Code

A dynamic collaborative filtering system via a weighted clustering approach
Aghiles Salah, Nicoleta Rogovschi, Mohamed Nadif
Neurocomputing, 175, Part A: 206-215. 2016
Paper | Code

2015

An Efficient Incremental Collaborative Filtering System
Aghiles Salah, Nicoleta Rogovschi, Mohamed Nadif
International Conference on Neural Information Processing, pages 375-383, 2015
Paper | Code

Software

In parallel with fundamental research activities, I also develop frameworks/libraries to make this research convenient, as well as facilitate its adoption by practitioners in academia and industry.

Cornac - A Comparative Framework for Multimodal Recommender Systems
DirecCoclus - An R Package for Directional Co-clustering
DCC -Directional Co-clustering with a Conscience

Awards

Helga and Wolfgang Gaul Stiftung Award - International Federation of Classification Societies (IFCS) - 2019
This award is given biannually to a young researcher with high potential working in the area of Classification, Clustering and related topics.

Student Travel Grant - Society for Industrial and Applied Mathematics (SIAM) - 2016

Ph.D. Scholarship for 3 years (competitive) - Doctoral School EDITE DE PARIS - 2013

Blog

Why maximum likelihood-based training may lead to the generation of unrealistic samples - 04/2020
Context Matters: Why Aren’t You Leveraging Items’ Context to Boost Your Recommender Model? - 06/2019

UAI-2018 in Monterey - 09/2018

Teaching

I taught the following courses at the University of Paris Descartes, when I was a PhD student then ATER at the same university.

2016-2017

Introduction to Machine Learning - Master 1 in Artificial Intelligence
Technological Monitoring and Innovation - Master 1 MIAGE
Digital Data Processing and Analysis - Licence 3 in Computer Science
Software Engineering - Licence 3 in Computer Science
Analysis and Design of Information Systems - Licence 3 in Computer Science

2013-2016

Introduction to Machine Learning - Master 1 in Artificial Intelligence
Digital Data Processing and Analysis - Licence 3 in Computer Science
Software Engineering - Licence 3 in Computer Science

A brief history

2016 - 2017 Assistant Professor (ATER)
Department of Computer Science and Mathematics, University of Paris Descartes.

2013 - 2016    Ph.D., Computer Science, Machine Learning.
                         Distinction: Highest Honours.
                         Title: Von Mises-Fisher based (Co-)Clustering for High-dimensional Sparse data.
                         Advisor: Prof. Mohamed Nadif.
                         Institution: University of Paris Descartes.
03/2013 -        Research Intern, Computer Science Laboratory of Paris Descartes (LIPADE), France.
08/2013          Development and implementation of Machine Learning algorithms in the fields of
                         Waste Management and Environmental, in partnership with the TRINOV Company.

2011 - 2013    M.Sc., Computer Science, Specialization in Machine Learning.
                         Distinction: First class Honours.
                         Institution: University of Paris Descartes.