HN
Houssam Nassif
cs.LGstat.MLstat.MEcs.IRArtificial Intelligencecs.AIstat.APmath.STstat.THAleph
On Valency
published · living versionsW_68ypjeqm·v1 · currentpublished
Let Them Peek: Group Sequential Designs for A/B Testing
with Lorenzo Perini, Mia Garrard, Rina Friedberg, Rohit Kumar +2
1 version
W_gp4y2f4t·v1published
Preprints & journals
41 papers in the corpus · 2009–2026Let Them Peek: Group Sequential Designs for A/B Testing2610.27899v1 · Lorenzo Perini, Mia Garrard, Rina Friedberg et al.2026 · 0 citationsarXivon Valency
Halve-Then-Greedy: Adaptive Sampling for Posterior Success with Near-Optimal Instance Dependence2610.20997v1 · Yinan Li, Kwang-Sung Jun, Kapilan Balagopalan et al.2026 · 0 citationsarXiv
Neutral Is Not Free: Evaluating Downside Risk in Neutral Launches2610.10223v1 · Pablo Alcain, Jason Kang, Mia Garrard et al.2026 · 0 citationsarXiv
Estimating the True Effect Size Distribution with SIMEX2608.23612v1 · Zhaoqi Li, Daniel Ting, Ilya Gorbachev et al.2026 · 0 citationsConference on Digital Experimentation @ MIT (CODE@MIT'24), Cambridge, MA, 2024
Impression Share Prediction: An Offline Evaluation Task for Ranking Systems2608.16872v1 · Mohsen Malmir, Houssam Nassif, Danish Nasir Shaikh et al.2026 · 0 citationsIn Proceedings of the ACM Conference on Recommender Systems (RecSys'26), Minneapolis, US, 2026
Breaking the Winner's Curse with Bayesian Hybrid Shrinkage2603.12867v1 · Richard Mudd, Abbas Zaidi, Rina Friedberg et al.2026 · 0 citationsarXiv
Fixed Budget is No Harder Than Fixed Confidence in Best-Arm Identification up to Logarithmic Factors2602.03972v3 · Kapilan Balagopalan, Yinan Li, Yao Zhao et al.2026 · 0 citationsInternational Conference on Machine Learning (ICML'26), Seoul, Korea, 2026
Evaluating Variance Estimates with Relative Efficiency2511.15961v1 · Kedar Karhadkar, Jack Klys, Daniel Ting et al.2025 · 0 citationsConference on Digital Experimentation @ MIT (CODE@MIT'25), Cambridge, MA, 2025
Breaking the Winner's Curse with Bayesian Hybrid Shrinkage2511.06318v1 · Richard Mudd, Rina Friedberg, Ilya Gorbachev et al.2025 · 0 citationsConference on Digital Experimentation @ MIT (CODE@MIT'25), Cambridge, MA, 2025
Counterfactual Evaluation of Ads Ranking Models through Domain Adaptation2409.19824v1 · Mohamed A. Radwan, Himaghna Bhattacharjee, Quinn Lanners et al.2024 · 0 citationsACM Conference on Recommender Systems (RecSys'24) Workshops, Bari, Italy, 2024
Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice2402.10870v3 · Tanner Fiez, Houssam Nassif, Yu-Cheng Chen et al.2024 · 6 citationsThe Web Conference (WWW'24), Singapore, pp. 3586 - 3597, 2024
Estimation of subsidiary performance metrics under optimal policies2401.04265v1 · Zhaoqi Li, Houssam Nassif, Alex Luedtke2024 · 0 citationsStatistica Sinica, 37(3), 2027
On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models.40196135 · Li, Boyao, Thomson, Alexander J, Nassif, Houssam et al.2025 · 1 citationAdvances in neural information processing systems. 2024;37:4598-4628
Experimental Designs for Heteroskedastic Variance2310.04390v1 · Justin Weltz, Tanner Fiez, Alexander Volfovsky et al.2023 · 1 citationConference on Neural Information Processing Systems (NeurIPS'23), New Orleans, pp. 65967-66005, 2023
On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models2305.17583v5 · Boyao Li, Alexander J. Thomson, Houssam Nassif et al.2023 · 1 citationConference on Neural Information Processing Systems (NeurIPS'24), Vancouver, BC, pp. 4598-4628, 2024
A Data-Driven State Aggregation Approach for Dynamic Discrete Choice Models2304.04916v3 · Sinong Geng, Houssam Nassif, Carlos A. Manzanares2023 · 1 citationThe Conference on Uncertainty in Artificial Intelligence (UAI'23), Pittsburgh, PA, pp. 647-657, 2023
Neural Insights for Digital Marketing Content Design2302.01416v3 · Fanjie Kong, Yuan Li, Houssam Nassif et al.2023 · 13 citationsInternational Conference on Knowledge Discovery and Data Mining (KDD'23), Long Beach, CA, pp. 4320-4332, 2023
Adaptive Experimental Design and Counterfactual Inference2210.14369v1 · Tanner Fiez, Sergio Gamez, Arick Chen et al.2022 · 1 citationarXiv
Instance-optimal PAC Algorithms for Contextual Bandits2207.02357v1 · Zhaoqi Li, Lillian Ratliff, Houssam Nassif et al.2022 · 5 citationsConference on Neural Information Processing Systems (NeurIPS'22), New Orleans, pp. 37590-37603, 2022
Improved Confidence Bounds for the Linear Logistic Model and Applications to Linear Bandits2011.11222v2 · Kwang-Sung Jun, Lalit Jain, Blake Mason et al.2020 · 2 citationsProceedings of the International Conference on Machine Learning (ICML'21), pp. 5148-5157, 2021
Deep PQR: Solving Inverse Reinforcement Learning using Anchor Actions2007.07443v2 · Sinong Geng, Houssam Nassif, Carlos A. Manzanares et al.2020 · 2 citationsIn Proceedings of the 37th ICML, Vienna, Austria, PMLR 119, pp. 3431-3441, 2020
Bayesian Meta-Prior Learning Using Empirical Bayes2002.01129v3 · Sareh Nabi, Houssam Nassif, Joseph Hong et al.2020 · 15 citationsManagement Science, 68(3):1737-1755, 2022
Seeker: Real-Time Interactive Search1905.13125v1 · Ari Biswas, Thai T Pham, Michael Vogelsong et al.2019 · 0 citationsKnowledge Discovery in Databases Conference (KDD'19), Anchorage, Alaska, pp. 2867-2875, 2019
An Efficient Bandit Algorithm for Realtime Multivariate Optimization1810.09558v1 · Daniel N Hill, Houssam Nassif, Yi Liu et al.2018 · 108 citationsDaniel N. Hill, Houssam Nassif, Yi Liu, Anand Iyer, and S. V. N. Vishwanathan. 2017. An Efficient Bandit Algorithm for Realtime Multivariate Optimization. In Proceedings of KDD'17, Halifax, NS, Canada, pp. 1813-1821, 2017
Adaptive, Personalized Diversity for Visual Discovery1810.01477v1 · Choon Hui Teo, Houssam Nassif, Daniel Hill et al.2018 · 61 citationsAdaptive, Personalized Diversity for Visual Discovery. Teo CH, Nassif H, Hill D, Srinavasan S, Goodman M, Mohan V, and Vishwanathan SVN. ACM Conference on Recommender Systems (RecSys'16), Boston, pp. 35-38, 2016
Diversifying Music Recommendations1810.01482v1 · Houssam Nassif, Kemal Oral Cansizlar, Mitchell Goodman et al.2018 · 9 citationsarXiv
Contextual Multi-Armed Bandits for Causal Marketing1810.01859v1 · Neela Sawant, Chitti Babu Namballa, Narayanan Sadagopan et al.2018 · 13 citationsSawant N, Namballa CB, Sadagopan N, and Nassif H. Contextual Multi-Armed Bandits for Causal Marketing. International Conference on Machine Learning (ICML'18) Workshops, Stockholm, Sweden, 2018
Rational Polypharmacology: Systematically Identifying and Engaging Multiple Drug Targets To Promote Axon Growth.26056718 · Al-Ali, Hassan, Lee, Do-Hun, Danzi, Matt C et al.2016 · 66 citationsACS chemical biology. 2015;10(8):1939-51
Predicting invasive breast cancer versus DCIS in different age groups.25112586 · Ayvaci, Mehmet U S, Alagoz, Oguzhan, Chhatwal, Jagpreet et al.2015 · 13 citationsBMC cancer. 2014;14:584
Support Vector Machines for Differential Prediction.26158123 · Kuusisto, Finn, Santos Costa, Vitor, Nassif, Houssam et al.2024 · 38 citationsMachine learning and knowledge discovery in databases : European Conference, ECML PKDD ... : proceedings. ECML PKDD (Conference). 2014;8725:50-65
Genetic variants improve breast cancer risk prediction on mammograms.24551380 · Liu, Jie, Page, David, Nassif, Houssam et al.2014 · 16 citationsAMIA ... Annual Symposium proceedings. AMIA Symposium. 2013;2013:876-85
Using Machine Learning to Identify Benign Cases with Non-Definitive Biopsy.26501132 · Kuusisto, Finn, Dutra, Inês, Nassif, Houssam et al.2020 · 4 citationsHealthcom. International Conference on e-Health Networking, Applications and Services. 2013;2013(15th):283-285
Score As You Lift (SAYL): A Statistical Relational Learning Approach to Uplift Modeling.26158122 · Nassif, Houssam, Kuusisto, Finn, Burnside, Elizabeth S et al.2024 · 14 citationsMachine learning and knowledge discovery in databases : European Conference, ECML PKDD ... : proceedings. ECML PKDD (Conference). 2013;8190:595-611
Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study.22783946 · A Santos, Jose C, Nassif, Houssam, Page, David et al.2013 · 23 citationsBMC bioinformatics. 2012;13:162
Automatic classification of mammography reports by BI-RADS breast tissue composition class.22291166 · Percha, Bethany, Nassif, Houssam, Lipson, Jafi et al.2013 · 60 citationsJournal of the American Medical Informatics Association : JAMIA. 2012;19(5):913-6
Logical Differential Prediction Bayes Net, improving breast cancer diagnosis for older women.23304412 · Nassif, Houssam, Wu, Yirong, Page, David et al.2013 · 11 citationsAMIA ... Annual Symposium proceedings. AMIA Symposium. 2012;2012:1330-9
Extracting BI-RADS Features from Portuguese Clinical Texts.23797461 · Nassif, Houssam, Cunha, Filipe, Moreira, Inês C et al.2024 · 14 citationsProceedings. IEEE International Conference on Bioinformatics and Biomedicine. 2012:1-4
Integrating machine learning and physician knowledge to improve the accuracy of breast biopsy.22195087 · Dutra, I, Nassif, H, Page, D et al.2013 · 11 citationsAMIA ... Annual Symposium proceedings. AMIA Symposium. 2011;2011:349-55
An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge.25309972 · Nassif, Houssam, Al-Ali, Hassan, Khuri, Sawsan et al.2021 · 10 citationsInductive logic programming. ILP. 2010;5989:149-165
Prediction of protein-glucose binding sites using support vector machines.19415755 · Nassif, Houssam, Al-Ali, Hassan, Khuri, Sawsan et al.2009 · 33 citationsProteins. 2009;77(1):121-32
Information Extraction for Clinical Data Mining: A Mammography Case Study.23765123 · Nassif, Houssam, Woods, Ryan, Burnside, Elizabeth et al.2024 · 63 citationsProceedings. IEEE International Conference on Data Mining. 2009:37-42
Career total: 63 works. 41 are in this corpus.
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