David D. Jensen

According to our database1, David D. Jensen authored at least 94 papers between 1996 and 2021.

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Bibliography

2021
A Simulation-Based Test of Identifiability for Bayesian Causal Inference.
CoRR, 2021

Preserving Privacy in Personalized Models for Distributed Mobile Services.
CoRR, 2021

2020
Causal Inference using Gaussian Processes with Structured Latent Confounders.
Proceedings of the 37th International Conference on Machine Learning, 2020

Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
PlanAlyzer: assessing threats to the validity of online experiments.
Proc. ACM Program. Lang., 2019

Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep RL.
CoRR, 2019

Bayesian causal inference via probabilistic program synthesis.
CoRR, 2019

Toybox: A Suite of Environments for Experimental Evaluation of Deep Reinforcement Learning.
CoRR, 2019

Let's Play Again: Variability of Deep Reinforcement Learning Agents in Atari Environments.
CoRR, 2019

Object Conditioning for Causal Inference.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Identifying When Effect Restoration Will Improve Estimates of Causal Effect.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

2018
Measuring and Characterizing Generalization in Deep Reinforcement Learning.
CoRR, 2018

ToyBox: Better Atari Environments for Testing Reinforcement Learning Agents.
CoRR, 2018

2016
Causal Discovery for Manufacturing Domains.
CoRR, 2016

Evaluating Causal Models by Comparing Interventional Distributions.
CoRR, 2016

Inferring Causal Direction from Relational Data.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Controversy Detection in Wikipedia Using Collective Classification.
Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016

Inferring Network Effects from Observational Data.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

2015
Learning the Structure of Causal Models with Relational and Temporal Dependence.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Learning the Structure of Causal Models with Relational and Temporal Dependence.
Proceedings of the UAI 2015 Workshop on Advances in Causal Inference co-located with the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), 2015

Teaching Computing as Science in a Research Experience.
Proceedings of the 46th ACM Technical Symposium on Computer Science Education, 2015

Learning to Uncover Deep Musical Structure.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Refining the Semantics of Social Influence.
CoRR, 2014

Online dating recommendations: matching markets and learning preferences.
Proceedings of the 23rd International World Wide Web Conference, 2014

Propensity Score Matching for Causal Inference with Relational Data.
Proceedings of the UAI 2014 Workshop Causal Inference: Learning and Prediction co-located with 30th Conference on Uncertainty in Artificial Intelligence (UAI 2014), 2014

Classifier-Adjusted Density Estimation for Anomaly Detection and One-Class Classification.
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

Strategy Mining.
Proceedings of the Twenty-Seventh International Florida Artificial Intelligence Research Society Conference, 2014

2013
Reasoning about Independence in Probabilistic Models of Relational Data
CoRR, 2013

A Sound and Complete Algorithm for Learning Causal Models from Relational Data.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013


Copy or Coincidence? A Model for Detecting Social Influence and Duplication Events.
Proceedings of the 30th International Conference on Machine Learning, 2013

2011
Indexing Network Structure with Shortest-Path Trees.
ACM Trans. Knowl. Discov. Data, 2011

Probabilistic Modeling of Hierarchical Music Analysis.
Proceedings of the 12th International Society for Music Information Retrieval Conference, 2011

Relational Blocking for Causal Discovery.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010
Resisting structural re-identification in anonymized social networks.
VLDB J., 2010

The Application of Statistical Relational Learning to a Database of Criminal and Terrorist Activity.
Proceedings of the SIAM International Conference on Data Mining, 2010

Causal discovery in social media using quasi-experimental designs.
Proceedings of the 3rd Workshop on Social Network Mining and Analysis, 2010

Leveraging D-Separation for Relational Data Sets.
Proceedings of the ICDM 2010, 2010

Learning Causal Models of Relational Domains.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009
Accurate Estimation of the Degree Distribution of Private Networks.
Proceedings of the ICDM 2009, 2009

Knowledge Discovery by Design.
Proceedings of the KDIR 2009 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval, Funchal, 2009

2008
Resisting structural re-identification in anonymized social networks.
Proc. VLDB Endow., 2008

Optimistic pruning for multiple instance learning.
Pattern Recognit. Lett., 2008

Navigating networks by using homophily and degree.
Proc. Natl. Acad. Sci. USA, 2008

A bias/variance decomposition for models using collective inference.
Mach. Learn., 2008

Social networks: looking ahead.
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

Automatic identification of quasi-experimental designs for discovering causal knowledge.
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

Why Stacked Models Perform Effective Collective Classification.
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

Automatic Identification of Quasi-Experimental Designs for Scientific Discovery.
Proceedings of the Automated Scientific Discovery, 2008

2007
Relational Dependency Networks.
J. Mach. Learn. Res., 2007

Recommending citations for academic papers.
Proceedings of the SIGIR 2007: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2007

Finding tribes: identifying close-knit individuals from employment patterns.
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

Relational data pre-processing techniques for improved securities fraud detection.
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

Bias/Variance Analysis for Relational Domains.
Proceedings of the Inductive Logic Programming, 17th International Conference, 2007

Beyond Prediction: Directions for Probabilistic and Relational Learning.
Proceedings of the Inductive Logic Programming, 17th International Conference, 2007

Graph clustering with network structure indices.
Proceedings of the Machine Learning, 2007

Exploiting Network Structure for Active Inference in Collective Classification.
Proceedings of the Workshops Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), 2007

2006
Introduction to the special issue on multi-relational data mining and statistical relational learning.
Mach. Learn., 2006

Using structure indices for efficient approximation of network properties.
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006

MaxProp: Routing for Vehicle-Based Disruption-Tolerant Networks.
Proceedings of the INFOCOM 2006. 25th IEEE International Conference on Computer Communications, 2006

Representing documents with named entities for story link detection (SLD).
Proceedings of the 2006 ACM CIKM International Conference on Information and Knowledge Management, 2006

The NFL Coaching Network: Analysis of the Social Network among Professional Football Coaches.
Proceedings of the Capturing and Using Patterns for Evidence Detection, 2006

2005
The case for anomalous link discovery.
SIGKDD Explor., 2005

Privacy Vulnerabilities in Encrypted HTTP Streams.
Proceedings of the Privacy Enhancing Technologies, 5th International Workshop, 2005

Using relational knowledge discovery to prevent securities fraud.
Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2005

Creating social networks to improve peer-to-peer networking.
Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2005

Decentralized Search in Networks Using Homophily and Degree Disparity.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Leveraging Relational Autocorrelation with Latent Group Models.
Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 2005

A Relational Representation for Procedural Task Knowledge.
Proceedings of the Proceedings, 2005

2004
Why collective inference improves relational classification.
Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

Dependency Networks for Relational Data.
Proceedings of the 4th IEEE International Conference on Data Mining (ICDM 2004), 2004

2003
Exploiting relational structure to understand publication patterns in high-energy physics.
SIGKDD Explor., 2003

Learning relational probability trees.
Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 24, 2003

Information awareness: a prospective technical assessment.
Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 24, 2003

Identifying Predictive Structures in Relational Data Using Multiple Instance Learning.
Proceedings of the Machine Learning, 2003

Avoiding Bias when Aggregating Relational Data with Degree Disparity.
Proceedings of the Machine Learning, 2003

Simple Estimators for Relational Bayesian Classifiers.
Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM 2003), 2003

2002
Autocorrelation and Linkage Cause Bias in Evaluation of Relational Learners.
Proceedings of the Inductive Logic Programming, 12th International Conference, 2002

Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning.
Proceedings of the Machine Learning, 2002

2000
Data Snooping, Dredging and Fishing: The Dark Side of Data Mining, A SIGKDD99 Panel Report.
SIGKDD Explor., 2000

Multiple Comparisons in Induction Algorithms.
Mach. Learn., 2000

Reports on the AAAI Fall Symposia (November 1999 and November 1998).
AI Mag., 2000

Knowledge Discovery from Graphs (Invited Talk).
Proceedings of the Graph Drawing, 8th International Symposium, 2000

Language Models for Financial News Recommendation.
Proceedings of the 2000 ACM CIKM International Conference on Information and Knowledge Management, 2000

1999
Coordinating agent activities in knowledge discovery processes.
Proceedings of the international joint conference on Work activities coordination and collaboration 1999, 1999

Efficient Progressive Sampling.
Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1999

Statistical challenges to inductive inference in linked data.
Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, 1999

Toward a Theoretical Understanding of Why and When Decision Tree Pruning Algorithms Fail.
Proceedings of the Sixteenth National Conference on Artificial Intelligence and Eleventh Conference on Innovative Applications of Artificial Intelligence, 1999

Learning Quantitative Knowledge for Multiagent Coordination.
Proceedings of the Sixteenth National Conference on Artificial Intelligence and Eleventh Conference on Innovative Applications of Artificial Intelligence, 1999

1998
Large Datasets Lead to Overly Complex Models: An Explanation and a Solution.
Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), 1998

1997
Adjusting for Multiple Comparisons in Decision Tree Pruning.
Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (KDD-97), 1997

Building Simple Models: A Case Study with Decision Trees.
Proceedings of the Advances in Intelligent Data Analysis, 1997

The Effects of Training Set Size on Decision Tree Complexity.
Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997

1996
Technology, language, and public decisions: finding common ground for experts and citizens.
Proceedings of the 1996 International Symposium on Technology and Society Technical Expertise and Public Decisions, 1996


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