Houssam Nassif

According to our database, Houssam Nassif authored at least 31 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Counterfactual Evaluation of Ads Ranking Models through Domain Adaptation.

Mohamed A. Radwan, Himaghna Bhattacharjee, Quinn Lanners, Jiasheng Zhang, Serkan Karakulak, Houssam Nassif, Murat Ali Bayir

CoRR, 2024

Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice.

Tanner Fiez, Houssam Nassif, Yu-Cheng Chen, Sergio Gamez, Lalit Jain

Proceedings of the ACM on Web Conference 2024, 2024

2023

A Data-Driven State Aggregation Approach for Dynamic Discrete Choice Models.

Sinong Geng, Houssam Nassif, Carlos A. Manzanares

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Experimental Designs for Heteroskedastic Variance.

Justin Weltz, Tanner Fiez, Alexander Volfovsky, Eric Laber, Blake Mason, Houssam Nassif, Lalit Jain

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Neural Insights for Digital Marketing Content Design.

Fanjie Kong, Yuan Li, Houssam Nassif, Tanner Fiez, Ricardo Henao, Shreya Chakrabarti

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022

Bayesian Meta-Prior Learning Using Empirical Bayes.

Sareh Nabi, Houssam Nassif, Joseph Hong, Hamed Mamani, Guido Imbens

Manag. Sci., 2022

Adaptive Experimental Design and Counterfactual Inference.

Tanner Fiez, Sergio Gamez, Arick Chen, Houssam Nassif, Lalit Jain

CoRR, 2022

Instance-optimal PAC Algorithms for Contextual Bandits.

Zhaoqi Li, Lillian J. Ratliff, Houssam Nassif, Kevin G. Jamieson, Lalit Jain

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Improved Confidence Bounds for the Linear Logistic Model and Applications to Bandits.

Kwang-Sung Jun, Lalit Jain, Houssam Nassif, Blake Mason

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Improved Confidence Bounds for the Linear Logistic Model and Applications to Linear Bandits.

Kwang-Sung Jun, Lalit Jain, Houssam Nassif

CoRR, 2020

Identifying Reward Functions using Anchor Actions.

Sinong Geng, Houssam Nassif, Carlos A. Manzanares, A. Max Reppen, Ronnie Sircar

CoRR, 2020

Decoupling Learning Rates Using Empirical Bayes Priors.

Sareh Nabi, Houssam Nassif, Joseph Hong, Hamed Mamani, Guido Imbens

CoRR, 2020

Deep PQR: Solving Inverse Reinforcement Learning using Anchor Actions.

Sinong Geng, Houssam Nassif, Carlos A. Manzanares, A. Max Reppen, Ronnie Sircar

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Seeker: Real-Time Interactive Search.

Ari Biswas, Thai T. Pham, Michael Vogelsong, Benjamin Snyder, Houssam Nassif

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2018

Contextual Multi-Armed Bandits for Causal Marketing.

Neela Sawant, Chitti Babu Namballa, Narayanan Sadagopan, Houssam Nassif

CoRR, 2018

Diversifying Music Recommendations.

Houssam Nassif, Kemal Oral Cansizlar, Mitchell Goodman, S. V. N. Vishwanathan

CoRR, 2018

2017

An Efficient Bandit Algorithm for Realtime Multivariate Optimization.

Daniel N. Hill, Houssam Nassif, Yi Liu, Anand Iyer, S. V. N. Vishwanathan

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

2016

Adaptive, Personalized Diversity for Visual Discovery.

Choon Hui Teo, Houssam Nassif, Daniel N. Hill, Sriram Srinivasan, Mitchell Goodman, Vijai Mohan, S. V. N. Vishwanathan

Proceedings of the 10th ACM Conference on Recommender Systems, 2016

2014

Support Vector Machines for Differential Prediction.

Finn Kuusisto, Vítor Santos Costa, Houssam Nassif, Elizabeth S. Burnside, David Page, Jude W. Shavlik

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

2013

Score As You Lift (SAYL): A Statistical Relational Learning Approach to Uplift Modeling.

Houssam Nassif, Finn Kuusisto, Elizabeth S. Burnside, David Page, Jude W. Shavlik, Vítor Santos Costa

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Uplift Modeling with ROC: An SRL Case Study.

Houssam Nassif, Finn Kuusisto, Elizabeth S. Burnside, Jude W. Shavlik

Proceedings of the Late Breaking Papers of the 23rd International Conference on Inductive Logic Programming, Rio de Janeiro, Brazil, August 28th - to, 2013

Using machine learning to identify benign cases with non-definitive biopsy.

Finn Kuusisto, Inês de Castro Dutra, Houssam Nassif, Yirong Wu, Molly E. Klein, Heather B. Neuman, Jude W. Shavlik, Elizabeth S. Burnside

Proceedings of the IEEE 15th International Conference on e-Health Networking, 2013

Genetic Variants Improve Breast Cancer Risk Prediction on Mammograms.

Jie Liu, David Page, Houssam Nassif, Jude W. Shavlik, Peggy L. Peissig, Catherine A. McCarty, Adedayo A. Onitilo, Elizabeth S. Burnside

Proceedings of the AMIA 2013, 2013

2012

Automatic classification of mammography reports by BI-RADS breast tissue composition class.

Bethany Percha, Houssam Nassif, Jafi A. Lipson, Elizabeth S. Burnside, Daniel L. Rubin

J. Am. Medical Informatics Assoc., 2012

Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study.

José Carlos Almeida Santos, Houssam Nassif, David Page, Stephen H. Muggleton, Michael J. E. Sternberg

BMC Bioinform., 2012

Relational Differential Prediction.

Houssam Nassif, Vítor Santos Costa, Elizabeth S. Burnside, David Page

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Extracting BI-RADS features from Portuguese clinical texts.

Houssam Nassif, Filipe Cunha, Inês C. Moreira, Ricardo Cruz-Correia, Eliana Sousa, David Page, Elizabeth S. Burnside, Inês de Castro Dutra

Proceedings of the 2012 IEEE International Conference on Bioinformatics and Biomedicine, 2012

Logical Differential Prediction Bayes Net, improving breast cancer diagnosis for older women.

Houssam Nassif, Yirong Wu, David Page, Elizabeth S. Burnside

Proceedings of the AMIA 2012, 2012

2010

Uncovering age-specific invasive and DCIS breast cancer rules using inductive logic programming.

Houssam Nassif, David Page, Mehmet Ayvaci, Jude W. Shavlik, Elizabeth S. Burnside

Proceedings of the ACM International Health Informatics Symposium, 2010

2009

An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge.

Houssam Nassif, Hassan Al-Ali, Sawsan Khuri, Walid Keirouz, David Page

Proceedings of the Inductive Logic Programming, 19th International Conference, 2009

Information Extraction for Clinical Data Mining: A Mammography Case Study.

Houssam Nassif, Ryan W. Woods, Elizabeth S. Burnside, Mehmet Ayvaci, Jude W. Shavlik, David Page

Proceedings of the ICDM Workshops 2009, 2009