Joseph J. Pfeiffer III

Affiliations:
  • Microsoft, Bellevue, WA, USA
  • Purdue University, West Lafayette, IN, USA (fomer)


According to our database1, Joseph J. Pfeiffer III authored at least 22 papers between 2009 and 2022.

Collaborative distances:

Timeline

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Bibliography

2022
Causal Inference in the Presence of Interference in Sponsored Search Advertising.
Frontiers Big Data, 2022

2021
Masked LARk: Masked Learning, Aggregation and Reporting worKflow.
CoRR, 2021

Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction.
Proceedings of the WSDM '21, 2021

2020
Causal Inference in the Presence of Interference in Sponsored Search Advertising.
CoRR, 2020

2019
Incentivized Social Sharing: Characteristics and Optimization.
Proceedings of the Influence and Behavior Analysis in Social Networks and Social Media, 2019

2018
Scalable and exact sampling method for probabilistic generative graph models.
Data Min. Knowl. Discov., 2018

Unbiased Estimation of the Value of an Optimized Policy.
CoRR, 2018

Modeling and Simultaneously Removing Bias via Adversarial Neural Networks.
CoRR, 2018

2017
Optimizing the Effectiveness of Incentivized Social Sharing.
Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017, Sydney, Australia, July 31, 2017

2015
Overcoming Relational Learning Biases to Accurately Predict Preferences in Large Scale Networks.
Proceedings of the 24th International Conference on World Wide Web, 2015

Modeling Website Topic Cohesion at Scale to Improve Webpage Classification.
Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2015

Incorporating Assortativity and Degree Dependence into Scalable Network Models.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Attributed graph models: modeling network structure with correlated attributes.
Proceedings of the 23rd International World Wide Web Conference, 2014

Assortativity in Chung Lu Random Graph Models.
Proceedings of the 8th Workshop on Social Network Mining and Analysis, 2014

Composite Likelihood Data Augmentation for Within-Network Statistical Relational Learning.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

A Scalable Method for Exact Sampling from Kronecker Family Models.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Active Exploration in Networks: Using Probabilistic Relationships for Learning and Inference.
Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

2012
Fast Generation of Large Scale Social Networks with Clustering
CoRR, 2012

Fast Generation of Large Scale Social Networks While Incorporating Transitive Closures.
Proceedings of the 2012 International Conference on Privacy, 2012

2011
Using Bayesian Filtering to Localize Flexible Materials During Manipulation.
IEEE Trans. Robotics, 2011

Methods to Determine Node Centrality and Clustering in Graphs with Uncertain Structure.
Proceedings of the Fifth International Conference on Weblogs and Social Media, 2011

2009
A general framework for reconciling multiple weak segmentations of an image.
Proceedings of the IEEE Workshop on Applications of Computer Vision (WACV 2009), 2009


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