Deep personalized re-targeting. - Meisam Hejazinia; Pavlos Mitsoulis-Ntompos; Serena Zhang (ASONAM, 2019)

A Simple Deep Personalized Recommendation System. - Pavlos Mitsoulis-Ntompos; Meisam Hejazinia; Serena Zhang; Travis Brady (RecTour@RecSys, 2019)

A/B Testing Measurement Framework for Recommendation Models Based on Expected Revenue. - Meisam Hejazinia; Majid Hosseini; Bryant Sih (CoRR, 2019)

Accelerated learning from recommender systems using multi-armed bandit. - Meisam Hejazinia; Kyler Eastman; Shuqin Ye; Abbas Amirabadi; Ravi Divvela (CoRR, 2019)

Wide Network Learning with Differential Privacy. - Huanyu Zhang; Ilya Mironov; Meisam Hejazinia (CoRR, 2021)

FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning. - Meisam Hejazinia; Dzmitry Huba; Ilias Leontiadis; Kiwan Maeng; Mani Malek 001; Luca Melis; Ilya Mironov; Milad Nasr; Kaikai Wang; Carole-Jean Wu (CoRR, 2022)

Federated Linear Contextual Bandits with User-level Differential Privacy. - Ruiquan Huang; Huanyu Zhang; Luca Melis; Milan Shen; Meisam Hejazinia; Jing Yang 002 (ICML, 2023)

Federated Ensemble Learning: Increasing the Capacity of Label Private Recommendation Systems. - Meisam Hejazinia; Dzmitry Huba; Ilias Leontiadis; Kiwan Maeng; Mani Malek 001; Luca Melis; Ilya Mironov; Milad Nasr; Kaikai Wang; Carole-Jean Wu (IEEE Data Eng. Bull., 2023)