A Graphical Model for Collective Behavior Learning Using Minority Games. - Farhan Khawar; Zengchang Qin (PAKDD (2), 2014)

Collective game behavior learning with probabilistic graphical models. - Zengchang Qin; Farhan Khawar; Tao Wan 001 (Neurocomputing, 2016)

Latent tree models for hierarchical topic detection. - Peixian Chen; Nevin L. Zhang; Tengfei Liu; Leonard K. M. Poon; Zhourong Chen; Farhan Khawar (Artif. Intell., 2017)

Conformative Filtering for Implicit Feedback Data. - Farhan Khawar; Nevin L. Zhang; Jinxing Yu (CoRR, 2017)

Learning Hierarchical Item Categories from Implicit Feedback Data for Efficient Recommendations and Browsing. - Farhan Khawar; Nevin L. Zhang (CoRR, 2018)

Matrix Factorization Equals Efficient Co-occurrence Representation. - Farhan Khawar; Nevin L. Zhang (CoRR, 2018)

Using Taste Groups for Collaborative Filtering. - Farhan Khawar; Nevin L. Zhang (CoRR, 2018)

Conformative Filtering for Implicit Feedback Data. - Farhan Khawar; Nevin L. Zhang (ECIR (1), 2019)

Modeling Multidimensional User Preferences for Collaborative Filtering. - Farhan Khawar; Nevin L. Zhang (ICDE, 2019)

Cleaned Similarity for Better Memory-Based Recommenders. - Farhan Khawar; Nevin L. Zhang (SIGIR, 2019)

AutoFeature: Searching for Feature Interactions and Their Architectures for Click-through Rate Prediction. - Farhan Khawar; Xu Hang; Ruiming Tang; Bin Liu 072; Zhenguo Li; Xiuqiang He 001 (CIKM, 2020)

Learning the Structure of Auto-Encoding Recommenders. - Farhan Khawar; Leonard K. M. Poon; Nevin L. Zhang (WWW, 2020)

Non-popular Items for Accurate & Diverse Linear Auto-Encoding Recommenders. - Farhan Khawar; Adam Roegiest (ICTIR, 2022)