David D. Jensen

ORCID

Publication Activity (10 Years)

Years Active: 1996-2024
Publications (10 Years): 28

Top Venues

Publications

Purva Pruthi, David D. Jensen
Compositional Models for Estimating Causal Effects. CoRR (2024)
Katherine Avery, Amir Houmansadr, David D. Jensen
The Effect of Alter Ego Accounts on A/B Tests in Social Networks. WWW (Companion Volume) (2024)
Pracheta Amaranath, Peter J. Haas, David D. Jensen, Sam Witty
Causal Dynamic Bayesian Networks for Simulation Metamodeling. WSC (2023)
Kaleigh Clary, Emma Tosch, Jeremiah Onaolapo, David D. Jensen
Stick It to The Man: Correcting for Non-Cooperative Behavior of Subjects in Experiments on Social Networks. USENIX Security Symposium (2022)
Jeff Druce, James Niehaus, Vanessa Moody, David D. Jensen, Michael L. Littman
Brittle AI, Causal Confusion, and Bad Mental Models: Challenges and Successes in the XAI Program. CoRR (2021)
Emma Tosch, Eytan Bakshy, Emery D. Berger, David D. Jensen, J. Eliot B. Moss
PlanAlyzer: assessing threats to the validity of online experiments. Commun. ACM 64 (9) (2021)
Akanksha Atrey, Prashant J. Shenoy, David D. Jensen
Preserving Privacy in Personalized Models for Distributed Mobile Services. ICDCS (2021)
Akanksha Atrey, Prashant J. Shenoy, David D. Jensen
Preserving Privacy in Personalized Models for Distributed Mobile Services. CoRR (2021)
David D. Jensen
Improving Causal Inference by Increasing Model Expressiveness. AAAI (2021)
Sam Witty, David D. Jensen, Vikash Mansinghka
A Simulation-Based Test of Identifiability for Bayesian Causal Inference. CoRR (2021)
Akanksha Atrey, Kaleigh Clary, David D. Jensen
Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning. ICLR (2020)
Sam Witty, Kenta Takatsu, David D. Jensen, Vikash Mansinghka
Causal Inference using Gaussian Processes with Structured Latent Confounders. ICML (2020)
Sam Witty, Kenta Takatsu, David D. Jensen, Vikash Mansinghka
Causal Inference using Gaussian Processes with Structured Latent Confounders. CoRR (2020)
David D. Jensen, Javier Burroni, Matthew J. Rattigan
Object Conditioning for Causal Inference. UAI (2019)
Kaleigh Clary, Emma Tosch, John Foley, David D. Jensen
Let's Play Again: Variability of Deep Reinforcement Learning Agents in Atari Environments. CoRR (2019)
Emma Tosch, Kaleigh Clary, John Foley, David D. Jensen
Toybox: A Suite of Environments for Experimental Evaluation of Deep Reinforcement Learning. CoRR (2019)
Emma Tosch, Eytan Bakshy, Emery D. Berger, David D. Jensen, J. Eliot B. Moss
PlanAlyzer: Assessing Threats to the Validity of Online Experiments. CoRR (2019)
Hüseyin Oktay, Akanksha Atrey, David D. Jensen
Identifying When Effect Restoration Will Improve Estimates of Causal Effect. SDM (2019)
Akanksha Atrey, Kaleigh Clary, David D. Jensen
Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep RL. CoRR (2019)
Sam Witty, Alexander K. Lew, David D. Jensen, Vikash Mansinghka
Bayesian causal inference via probabilistic program synthesis. CoRR (2019)
Emma Tosch, Eytan Bakshy, Emery D. Berger, David D. Jensen, J. Eliot B. Moss
PlanAlyzer: assessing threats to the validity of online experiments. Proc. ACM Program. Lang. 3 (OOPSLA) (2019)
John Foley, Emma Tosch, Kaleigh Clary, David D. Jensen
ToyBox: Better Atari Environments for Testing Reinforcement Learning Agents. CoRR (2018)
Sam Witty, Jun Ki Lee, Emma Tosch, Akanksha Atrey, Michael L. Littman, David D. Jensen
Measuring and Characterizing Generalization in Deep Reinforcement Learning. CoRR (2018)
David T. Arbour, Dan Garant, David D. Jensen
Inferring Network Effects from Observational Data. KDD (2016)
Katerina Marazopoulou, Rumi Ghosh, Prasanth Lade, David D. Jensen
Causal Discovery for Manufacturing Domains. CoRR (2016)
Dan Garant, David D. Jensen
Evaluating Causal Models by Comparing Interventional Distributions. CoRR (2016)
Shiri Dori-Hacohen, David D. Jensen, James Allan
Controversy Detection in Wikipedia Using Collective Classification. SIGIR (2016)
David T. Arbour, Katerina Marazopoulou, David D. Jensen
Inferring Causal Direction from Relational Data. UAI (2016)
Katerina Marazopoulou, Marc E. Maier, David D. Jensen
Learning the Structure of Causal Models with Relational and Temporal Dependence. UAI (2015)
Jerod J. Weinman, David D. Jensen, David Lopatto
Teaching Computing as Science in a Research Experience. SIGCSE (2015)
Katerina Marazopoulou, Marc E. Maier, David D. Jensen
Learning the Structure of Causal Models with Relational and Temporal Dependence. ACI@UAI (2015)
Phillip B. Kirlin, David D. Jensen
Learning to Uncover Deep Musical Structure. AAAI (2015)
Xiaoxi Xu, David D. Jensen, Edwina L. Rissland
Strategy Mining. FLAIRS Conference (2014)
Katerina Marazopoulou, David T. Arbour, David D. Jensen
Refining the Semantics of Social Influence. CoRR (2014)
Kun Tu, Bruno F. Ribeiro, Hua Jiang, Xiaodong Wang, David D. Jensen, Benyuan Liu, Don Towsley
Online Dating Recommendations: Matching Markets and Learning Preferences. CoRR (2014)
Lisa Friedland, Amanda Gentzel, David D. Jensen
Classifier-Adjusted Density Estimation for Anomaly Detection and One-Class Classification. SDM (2014)
David T. Arbour, Katerina Marazopoulou, Dan Garant, David D. Jensen
Propensity Score Matching for Causal Inference with Relational Data. CI@UAI (2014)
Kun Tu, Bruno F. Ribeiro, David D. Jensen, Don Towsley, Benyuan Liu, Hua Jiang, Xiaodong Wang
Online dating recommendations: matching markets and learning preferences. WWW (Companion Volume) (2014)
Marc E. Maier, Katerina Marazopoulou, David T. Arbour, David D. Jensen
A Sound and Complete Algorithm for Learning Causal Models from Relational Data. CoRR (2013)
Lisa Friedland, David D. Jensen, Michael Lavine
Copy or Coincidence? A Model for Detecting Social Influence and Duplication Events. ICML (3) (2013)
Ted E. Senator, Henry G. Goldberg, Alex Memory, William T. Young, Brad Rees, Robert Pierce, Daniel Huang, Matthew Reardon, David A. Bader, Edmond Chow, Irfan A. Essa, Joshua Jones, Vinay Bettadapura, Duen Horng Chau, Oded Green, Oguz Kaya, Anita Zakrzewska, Erica Briscoe, Rudolph L. Mappus IV, Robert McColl, Lora Weiss, Thomas G. Dietterich, Alan Fern, Weng-Keen Wong, Shubhomoy Das, Andrew Emmott, Jed Irvine, Jay Yoon Lee, Danai Koutra, Christos Faloutsos, Daniel D. Corkill, Lisa Friedland, Amanda Gentzel, David D. Jensen
Detecting insider threats in a real corporate database of computer usage activity. KDD (2013)
Marc E. Maier, Katerina Marazopoulou, David T. Arbour, David D. Jensen
A Sound and Complete Algorithm for Learning Causal Models from Relational Data. UAI (2013)
Marc E. Maier, Katerina Marazopoulou, David D. Jensen
Reasoning about Independence in Probabilistic Models of Relational Data CoRR (2013)
Phillip B. Kirlin, David D. Jensen
Probabilistic Modeling of Hierarchical Music Analysis. ISMIR (2011)
Marc E. Maier, Matthew J. Rattigan, David D. Jensen
Indexing Network Structure with Shortest-Path Trees. ACM Trans. Knowl. Discov. Data 5 (3) (2011)
Matthew J. Rattigan, Marc E. Maier, David D. Jensen
Relational Blocking for Causal Discovery. AAAI (2011)
Brian Delaney, Andrew S. Fast, William M. Campbell, Clifford J. Weinstein, David D. Jensen
The Application of Statistical Relational Learning to a Database of Criminal and Terrorist Activity. SDM (2010)
Marc E. Maier, Brian J. Taylor, Hüseyin Oktay, David D. Jensen
Learning Causal Models of Relational Domains. AAAI (2010)
Matthew J. Rattigan, David D. Jensen
Leveraging D-Separation for Relational Data Sets. ICDM (2010)
Michael Hay, Gerome Miklau, David D. Jensen, Donald F. Towsley, Chao Li
Resisting structural re-identification in anonymized social networks. VLDB J. 19 (6) (2010)
Hüseyin Oktay, Brian J. Taylor, David D. Jensen
Causal discovery in social media using quasi-experimental designs. SOMA@KDD (2010)
Michael Hay, Chao Li, Gerome Miklau, David D. Jensen
Accurate Estimation of the Degree Distribution of Private Networks. ICDM (2009)
David D. Jensen
Knowledge Discovery by Design. KDIR (2009)
Ravi Kumar, Alexander Tuzhilin, Christos Faloutsos, David D. Jensen, Gueorgi Kossinets, Jure Leskovec, Andrew Tomkins
Social networks: looking ahead. KDD (2008)
Michael Hay, Gerome Miklau, David D. Jensen, Donald F. Towsley, Philipp Weis
Resisting structural re-identification in anonymized social networks. Proc. VLDB Endow. 1 (1) (2008)
Andrew S. Fast, David D. Jensen
Why Stacked Models Perform Effective Collective Classification. ICDM (2008)
Özgür Simsek, David D. Jensen
Navigating networks by using homophily and degree. Proc. Natl. Acad. Sci. USA 105 (35) (2008)
David D. Jensen, Andrew S. Fast, Brian J. Taylor, Marc E. Maier
Automatic identification of quasi-experimental designs for discovering causal knowledge. KDD (2008)
David D. Jensen, Andrew S. Fast, Brian J. Taylor, Marc E. Maier, Matthew J. Rattigan
Automatic Identification of Quasi-Experimental Designs for Scientific Discovery. AAAI Fall Symposium: Automated Scientific Discovery (2008)
Jennifer Neville, David D. Jensen
A bias/variance decomposition for models using collective inference. Mach. Learn. 73 (1) (2008)
Amy McGovern, David D. Jensen
Optimistic pruning for multiple instance learning. Pattern Recognit. Lett. 29 (9) (2008)
Lisa Friedland, David D. Jensen
Finding tribes: identifying close-knit individuals from employment patterns. KDD (2007)
Jennifer Neville, David D. Jensen
Bias/Variance Analysis for Relational Domains. ILP (2007)
Matthew J. Rattigan, Marc E. Maier, David D. Jensen
Graph clustering with network structure indices. ICML (2007)
Matthew J. Rattigan, Marc E. Maier, David D. Jensen, Bin Wu, Xin Pei, Jianbin Tan, Yi Wang
Exploiting Network Structure for Active Inference in Collective Classification. ICDM Workshops (2007)
Trevor Strohman, W. Bruce Croft, David D. Jensen
Recommending citations for academic papers. SIGIR (2007)
Jennifer Neville, David D. Jensen
Relational Dependency Networks. J. Mach. Learn. Res. 8 (2007)
David D. Jensen
Beyond Prediction: Directions for Probabilistic and Relational Learning. ILP (2007)
Andrew S. Fast, Lisa Friedland, Marc E. Maier, Brian J. Taylor, David D. Jensen, Henry G. Goldberg, John Komoroske
Relational data pre-processing techniques for improved securities fraud detection. KDD (2007)
Chirag Shah, W. Bruce Croft, David D. Jensen
Representing documents with named entities for story link detection (SLD). CIKM (2006)
Matthew J. Rattigan, Marc E. Maier, David D. Jensen
Using structure indices for efficient approximation of network properties. KDD (2006)
Hendrik Blockeel, David D. Jensen, Stefan Kramer
Introduction to the special issue on multi-relational data mining and statistical relational learning. Mach. Learn. 62 (1-2) (2006)
John Burgess, Brian Gallagher, David D. Jensen, Brian Neil Levine
MaxProp: Routing for Vehicle-Based Disruption-Tolerant Networks. INFOCOM (2006)
Andrew S. Fast, David D. Jensen
The NFL Coaching Network: Analysis of the Social Network among Professional Football Coaches. AAAI Fall Symposium: Capturing and Using Patterns for Evidence Detection (2006)
George Dean Bissias, Marc Liberatore, David D. Jensen, Brian Neil Levine
Privacy Vulnerabilities in Encrypted HTTP Streams. Privacy Enhancing Technologies (2005)
Andrew S. Fast, David D. Jensen, Brian Neil Levine
Creating social networks to improve peer-to-peer networking. KDD (2005)
Jennifer Neville, Özgür Simsek, David D. Jensen, John Komoroske, Kelly Palmer, Henry G. Goldberg
Using relational knowledge discovery to prevent securities fraud. KDD (2005)
Özgür Simsek, David D. Jensen
Decentralized Search in Networks Using Homophily and Degree Disparity. IJCAI (2005)
Matthew J. Rattigan, David D. Jensen
The case for anomalous link discovery. SIGKDD Explor. 7 (2) (2005)
Jennifer Neville, David D. Jensen
Leveraging Relational Autocorrelation with Latent Group Models. ICDM (2005)
Stephen Hart, Roderic A. Grupen, David D. Jensen
A Relational Representation for Procedural Task Knowledge. AAAI (2005)
Jennifer Neville, David D. Jensen
Leveraging relational autocorrelation with latent group models. Probabilistic, Logical and Relational Learning (2005)
David D. Jensen, Jennifer Neville, Brian Gallagher
Why collective inference improves relational classification. KDD (2004)
Jennifer Neville, David D. Jensen
Dependency Networks for Relational Data. ICDM (2004)
Jennifer Neville, David D. Jensen, Lisa Friedland, Michael Hay
Learning relational probability trees. KDD (2003)
Amy McGovern, David D. Jensen
Identifying Predictive Structures in Relational Data Using Multiple Instance Learning. ICML (2003)
David D. Jensen, Matthew J. Rattigan, Hannah Blau
Information awareness: a prospective technical assessment. KDD (2003)
Jennifer Neville, David D. Jensen, Brian Gallagher
Simple Estimators for Relational Bayesian Classifiers. ICDM (2003)
Amy McGovern, Lisa Friedland, Michael Hay, Brian Gallagher, Andrew S. Fast, Jennifer Neville, David D. Jensen
Exploiting relational structure to understand publication patterns in high-energy physics. SIGKDD Explor. 5 (2) (2003)
David D. Jensen, Jennifer Neville, Michael Hay
Avoiding Bias when Aggregating Relational Data with Degree Disparity. ICML (2003)
David D. Jensen, Jennifer Neville
Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning. ICML (2002)
David D. Jensen, Jennifer Neville
Autocorrelation and Linkage Cause Bias in Evaluation of Relational Learners. ILP (2002)
Fawzi Daud, Michael Mateas, Phoebe Sengers, Susan Brennan, Alain Giboin, David R. Traum, Vinay K. Chaudri, Richard Fikes, Donia Scott, Richard Power, David D. Jensen
Reports on the AAAI Fall Symposia (November 1999 and November 1998). AI Mag. 21 (2) (2000)
David D. Jensen, Paul R. Cohen
Multiple Comparisons in Induction Algorithms. Mach. Learn. 38 (3) (2000)
David D. Jensen
Knowledge Discovery from Graphs (Invited Talk). Graph Drawing (2000)
Victor Lavrenko, Matthew D. Schmill, Dawn J. Lawrie, Paul Ogilvie, David D. Jensen, James Allan
Language Models for Financial News Recommendation. CIKM (2000)
David D. Jensen
Data Snooping, Dredging and Fishing: The Dark Side of Data Mining, A SIGKDD99 Panel Report. SIGKDD Explor. 1 (2) (2000)
Foster J. Provost, David D. Jensen, Tim Oates
Efficient Progressive Sampling. KDD (1999)
David D. Jensen
Statistical challenges to inductive inference in linked data. AISTATS (1999)
David D. Jensen, Yulin Dong, Barbara Staudt Lerner, Eric K. McCall, Leon J. Osterweil, Stanley M. Sutton Jr., Alexander E. Wise
Coordinating agent activities in knowledge discovery processes. WACC (1999)

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Publication Activity (10 Years)

Top Topics

Top Venues

David D. Jensen