Houssam Nassif

42 papers A* 9A 2B 1C 1Misc 2Journal 20Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Fixed Budget is No Harder Than Fixed Confidence in Best-Arm Identification up to Logarithmic Factors. CoRR Kapilan Balagopalan, Yinan Li, Yao Zhao, Tuan Ngo Nguyen, Anton Daitche, Houssam Nassif, Kwang-Sung Jun
2025	J	`jnl`	Factor Learning Portfolio Optimization Informed by Continuous-Time Finance Models. Trans. Mach. Learn. Res. Sinong Geng, Houssam Nassif, Zhaobin Kuang, Anders Max Reppen, Ronnie Sircar
2024	A*	`conf`	Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice. WWW Tanner Fiez, Houssam Nassif, Yu-Cheng Chen, Sergio Gamez, Lalit Jain
2024	J	`jnl`	Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice. CoRR Tanner Fiez, Houssam Nassif, Yu-Cheng Chen, Sergio Gamez, Lalit Jain
2024	J	`jnl`	Counterfactual Evaluation of Ads Ranking Models through Domain Adaptation. CoRR Mohamed A. Radwan, Himaghna Bhattacharjee, Quinn Lanners, Jiasheng Zhang, Serkan Karakulak, Houssam Nassif, Murat Ali Bayir
2024	A*	`conf`	On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models. NeurIPS Boyao Li, Alexander Thomson, Houssam Nassif, Matthew Engelhard, David Page
2023	A	`conf`	A Data-Driven State Aggregation Approach for Dynamic Discrete Choice Models. UAI Sinong Geng, Houssam Nassif, Carlos A. Manzanares
2023	J	`jnl`	A Data-Driven State Aggregation Approach for Dynamic Discrete Choice Models. CoRR Sinong Geng, Houssam Nassif, Carlos A. Manzanares
2023	A*	`conf`	Experimental Designs for Heteroskedastic Variance. NeurIPS Justin Weltz, Tanner Fiez, Alexander Volfovsky, Eric Laber, Blake Mason, Houssam Nassif, Lalit Jain
2023	A*	`conf`	Neural Insights for Digital Marketing Content Design. KDD Fanjie Kong, Yuan Li, Houssam Nassif, Tanner Fiez, Ricardo Henao, Shreya Chakrabarti
2023	J	`jnl`	Neural Insights for Digital Marketing Content Design. CoRR Fanjie Kong, Yuan Li, Tanner Fiez, Shreya Chakrabarti, Ricardo Henao, Houssam Nassif
2022	J	`jnl`	Adaptive Experimental Design and Counterfactual Inference. CoRR Tanner Fiez, Sergio Gamez, Arick Chen, Houssam Nassif, Lalit Jain
2022	J	`jnl`	Bayesian Meta-Prior Learning Using Empirical Bayes. Manag. Sci. Sareh Nabi, Houssam Nassif, Joseph Hong, Hamed Mamani, Guido Imbens
2022	A*	`conf`	Instance-optimal PAC Algorithms for Contextual Bandits. NeurIPS Zhaoqi Li, Lillian J. Ratliff, Houssam Nassif, Kevin Jamieson, Lalit Jain
2022	J	`jnl`	Instance-optimal PAC Algorithms for Contextual Bandits. CoRR Zhaoqi Li, Lillian J. Ratliff, Houssam Nassif, Kevin Jamieson, Lalit Jain
2021	A*	`conf`	Improved Confidence Bounds for the Linear Logistic Model and Applications to Bandits. ICML Kwang-Sung Jun, Lalit Jain, Houssam Nassif, Blake Mason
2020	J	`jnl`	Decoupling Learning Rates Using Empirical Bayes Priors. CoRR Sareh Nabi, Houssam Nassif, Joseph Hong, Hamed Mamani, Guido Imbens
2020	A*	`conf`	Deep PQR: Solving Inverse Reinforcement Learning using Anchor Actions. ICML Sinong Geng, Houssam Nassif, Carlos A. Manzanares, A. Max Reppen, Ronnie Sircar
2020	J	`jnl`	Identifying Reward Functions using Anchor Actions. CoRR Sinong Geng, Houssam Nassif, Carlos A. Manzanares, A. Max Reppen, Ronnie Sircar
2020	J	`jnl`	Improved Confidence Bounds for the Linear Logistic Model and Applications to Linear Bandits. CoRR Kwang-Sung Jun, Lalit Jain, Houssam Nassif
2019	A*	`conf`	Seeker: Real-Time Interactive Search. KDD Ari Biswas, Thai T. Pham, Michael Vogelsong, Benjamin Snyder, Houssam Nassif
2019	J	`jnl`	Seeker: Real-Time Interactive Search. CoRR Ari Biswas, Thai T. Pham, Michael Vogelsong, Benjamin Snyder, Houssam Nassif
2018	J	`jnl`	Adaptive, Personalized Diversity for Visual Discovery. CoRR Choon Hui Teo, Houssam Nassif, Daniel N. Hill, Sriram Srinivasan, Mitchell Goodman, Vijai Mohan, S. V. N. Vishwanathan
2018	J	`jnl`	An Efficient Bandit Algorithm for Realtime Multivariate Optimization. CoRR Daniel N. Hill, Houssam Nassif, Yi Liu, Anand Iyer, S. V. N. Vishwanathan
2018	J	`jnl`	An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge. CoRR Houssam Nassif, Hassan Al-Ali, Sawsan Khuri, Walid Keirouz, David Page
2018	J	`jnl`	Contextual Multi-Armed Bandits for Causal Marketing. CoRR Neela Sawant, Chitti Babu Namballa, Narayanan Sadagopan, Houssam Nassif
2018	J	`jnl`	Diversifying Music Recommendations. CoRR Houssam Nassif, Kemal Oral Cansizlar, Mitchell Goodman, S. V. N. Vishwanathan
2017	A*	`conf`	An Efficient Bandit Algorithm for Realtime Multivariate Optimization. KDD Daniel N. Hill, Houssam Nassif, Yi Liu, Anand Iyer, S. V. N. Vishwanathan
2016	A	`conf`	Adaptive, Personalized Diversity for Visual Discovery. RecSys Choon Hui Teo, Houssam Nassif, Daniel N. Hill, Sriram Srinivasan, Mitchell Goodman, Vijai Mohan, S. V. N. Vishwanathan
2014	—	`conf`	Support Vector Machines for Differential Prediction. ECML/PKDD (2) Finn Kuusisto, Vítor Santos Costa, Houssam Nassif, Elizabeth S. Burnside, David Page, Jude W. Shavlik
2013	Misc	`conf`	Genetic Variants Improve Breast Cancer Risk Prediction on Mammograms. AMIA Jie Liu, David Page, Houssam Nassif, Jude W. Shavlik, Peggy L. Peissig, Catherine A. McCarty, Adedayo A. Onitilo, Elizabeth S. Burnside
2013	—	`conf`	Score As You Lift (SAYL): A Statistical Relational Learning Approach to Uplift Modeling. ECML/PKDD (3) Houssam Nassif, Finn Kuusisto, Elizabeth S. Burnside, David Page, Jude W. Shavlik, Vítor Santos Costa
2013	—	`conf`	Uplift Modeling with ROC: An SRL Case Study. ILP (Late Breaking Papers) Houssam Nassif, Finn Kuusisto, Elizabeth S. Burnside, Jude W. Shavlik
2013	C	`conf`	Using machine learning to identify benign cases with non-definitive biopsy. Healthcom Finn Kuusisto, Inês de Castro Dutra, Houssam Nassif, Yirong Wu, Molly E. Klein, Heather B. Neuman, Jude W. Shavlik, Elizabeth S. Burnside
2012	J	`jnl`	Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study. BMC Bioinform. José Carlos Almeida Santos, Houssam Nassif, David Page, Stephen H. Muggleton, Michael J. E. Sternberg
2012	J	`jnl`	Automatic classification of mammography reports by BI-RADS breast tissue composition class. J. Am. Medical Informatics Assoc. Bethany Percha, Houssam Nassif, Jafi A. Lipson, Elizabeth S. Burnside, Daniel L. Rubin
2012	—	`conf`	Extracting BI-RADS features from Portuguese clinical texts. BIBM Houssam Nassif, Filipe Cunha, Inês C. Moreira, Ricardo Cruz-Correia, Eliana Sousa, David Page, Elizabeth S. Burnside, Inês de Castro Dutra
2012	Misc	`conf`	Logical Differential Prediction Bayes Net, improving breast cancer diagnosis for older women. AMIA Houssam Nassif, Yirong Wu, David Page, Elizabeth S. Burnside
2012	—	`conf`	Relational Differential Prediction. ECML/PKDD (1) Houssam Nassif, Vítor Santos Costa, Elizabeth S. Burnside, David Page
2010	—	`conf`	Uncovering age-specific invasive and DCIS breast cancer rules using inductive logic programming. IHI Houssam Nassif, David Page, Mehmet Ayvaci, Jude W. Shavlik, Elizabeth S. Burnside
2009	B	`conf`	An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge. ILP Houssam Nassif, Hassan Al-Ali, Sawsan Khuri, Walid Keirouz, David Page
2009	—	`conf`	Information Extraction for Clinical Data Mining: A Mammography Case Study. ICDM Workshops Houssam Nassif, Ryan W. Woods, Elizabeth S. Burnside, Mehmet Ayvaci, Jude W. Shavlik, David Page