Causal Inference in the Presence of Interference in Sponsored Search Advertising. - Nabi, Razieh; Pfeiffer, Joel; Charles, Denis; Kiciman, Emre (Frontiers Big Data, 2022)

Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction. - Zeng, Shuxi; Bayir, Murat Ali; Pfeiffer, Joseph J., III; Charles, Denis; Kiciman, Emre (2021)

Masked LARk: Masked Learning, Aggregation and Reporting worKflow. - Pfeiffer, Joseph J., III; Charles, Denis; Gilton, Davis; Jung, Young Hun; Parsana, Mehul; Anderson, Erik (CoRR, 2021)

Causal Inference in the Presence of Interference in Sponsored Search Advertising. - Nabi, Razieh; Pfeiffer, Joel; Bayir, Murat Ali; Charles, Denis; Kiciman, Emre (CoRR, 2020)

Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction. - Zeng, Shuxi; Bayir, Murat Ali; Pfeiffer, Joel; Charles, Denis; Kiciman, Emre (CoRR, 2020)

Incentivized Social Sharing: Characteristics and Optimization. - Pfeiffer, Joseph J., III; Zheleva, Elena (2019)

Scalable and exact sampling method for probabilistic generative graph models. - Moreno, Sebastián; Pfeiffer, Joseph J., III; Neville, Jennifer (Data Min. Knowl. Discov., 2018)

Modeling and Simultaneously Removing Bias via Adversarial Neural Networks. - Moore, John; Pfeiffer, Joel; Wei, Kai; Iyer, Rishabh K.; Charles, Denis; Gilad-Bachrach, Ran; Boyles, Levi; Manavoglu, Eren (CoRR, 2018)

Unbiased Estimation of the Value of an Optimized Policy. - Portugaly, Elon; Pfeiffer, Joseph J., III (CoRR, 2018)

Optimizing the Effectiveness of Incentivized Social Sharing. - Pfeiffer, Joseph J., III; Zheleva, Elena (2017)

Overcoming uncertainty for within-network relational machine learning - Pfeiffer, Joseph J., III (2015)

Incorporating Assortativity and Degree Dependence into Scalable Network Models. - Mussmann, Stephen; Moore, John; Pfeiffer, Joseph John, III; Neville, Jennifer (2015)

Modeling Website Topic Cohesion at Scale to Improve Webpage Classification. - Eswaran, Dhivya; Bennett, Paul N.; Pfeiffer, Joseph J., III (2015)

Overcoming Relational Learning Biases to Accurately Predict Preferences in Large Scale Networks. - Pfeiffer, Joseph J., III; Neville, Jennifer; Bennett, Paul N. (2015)

Active Exploration in Networks: Using Probabilistic Relationships for Learning and Inference. - Pfeiffer, Joseph John, III; Neville, Jennifer; Bennett, Paul N. (2014)

A Scalable Method for Exact Sampling from Kronecker Family Models. - Moreno, Sebastián; Pfeiffer, Joseph J., III; Neville, Jennifer; Kirshner, Sergey (2014)

Composite Likelihood Data Augmentation for Within-Network Statistical Relational Learning. - Pfeiffer, Joseph J., III; Neville, Jennifer; Bennett, Paul N. (2014)

Assortativity in Chung Lu Random Graph Models. - Mussmann, Stephen; Moore, John; Pfeiffer, Joseph J., III; Neville, Jennifer (2014)

Attributed graph models: modeling network structure with correlated attributes. - Pfeiffer, Joseph J., III; Moreno, Sebastián; Fond, Timothy La; Neville, Jennifer; Gallagher, Brian (2014)

Fast Generation of Large Scale Social Networks While Incorporating Transitive Closures. - Pfeiffer, Joseph J., III; Fond, Timothy La; Moreno, Sebastián; Neville, Jennifer (2012)

Fast Generation of Large Scale Social Networks with Clustering - Pfeiffer, Joseph J., III; Fond, Timothy La; Moreno, Sebastián; Neville, Jennifer (CoRR, 2012)

Using Bayesian Filtering to Localize Flexible Materials During Manipulation. - Platt, Robert, Jr.; Permenter, Frank; Pfeiffer, Joel (IEEE Trans. Robotics, 2011)

Methods to Determine Node Centrality and Clustering in Graphs with Uncertain Structure. - Pfeiffer, Joseph J., III; Neville, Jennifer (2011)

Methods to Determine Node Centrality and Clustering in Graphs with Uncertain Structure - Pfeiffer, Joseph J., III; Neville, Jennifer (CoRR, 2011)

A general framework for reconciling multiple weak segmentations of an image. - Ghosh, Soumya; Pfeiffer, Joseph J., III; Mulligan, Jane (2009)