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Jennifer Neville Vis

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*2008
19EESarvjeet Singh, Chris Mayfield, Rahul Shah, Sunil Prabhakar, Susanne E. Hambrusch, Jennifer Neville, Reynold Cheng: Database Support for Probabilistic Attributes and Tuples. ICDE 2008: 1053-1061
18EERongjing Xiang, Jennifer Neville: Pseudolikelihood EM for Within-network Relational Learning. ICDM 2008: 1103-1108
17EEUmang Sharan, Jennifer Neville: Temporal-Relational Classifiers for Prediction in Evolving Domains. ICDM 2008: 540-549
16EEPelin Angin, Jennifer Neville: A Shrinkage Approach for Modeling Non-stationary Relational Autocorrelation. ICDM 2008: 707-712
15EEJames A. Hendler, Philipp Cimiano, Dmitri A. Dolgov, Anat Levin, Peter Mika, Brian Milch, Louis-Philippe Morency, Boris Motik, Jennifer Neville, Erik B. Sudderth, Luis von Ahn: AI's 10 to Watch. IEEE Intelligent Systems 23(3): 9-19 (2008)
14EEJennifer Neville, David Jensen: A bias/variance decomposition for models using collective inference. Machine Learning 73(1): 87-106 (2008)
2007
13EEJennifer Neville, David Jensen: Bias/Variance Analysis for Relational Domains. ILP 2007: 27-28
2005
12 Jennifer Neville: Structure Learning for Statistical Relational Models. AAAI 2005: 1656-1657
11EEJennifer Neville, David Jensen: Leveraging Relational Autocorrelation with Latent Group Models. ICDM 2005: 322-329
10EEJennifer Neville, Özgür Simsek, David Jensen, John Komoroske, Kelly Palmer, Henry G. Goldberg: Using relational knowledge discovery to prevent securities fraud. KDD 2005: 449-458
9EEJennifer Neville, David Jensen: Leveraging relational autocorrelation with latent group models. Probabilistic, Logical and Relational Learning 2005
2004
8EEJennifer Neville, David Jensen: Dependency Networks for Relational Data. ICDM 2004: 170-177
7EEDavid Jensen, Jennifer Neville, Brian Gallagher: Why collective inference improves relational classification. KDD 2004: 593-598
2003
6EEJennifer Neville, David Jensen, Brian Gallagher: Simple Estimators for Relational Bayesian Classifiers. ICDM 2003: 609-612
5 David Jensen, Jennifer Neville, Michael Hay: Avoiding Bias when Aggregating Relational Data with Degree Disparity. ICML 2003: 274-281
4EEJennifer Neville, David Jensen, Lisa Friedland, Michael Hay: Learning relational probability trees. KDD 2003: 625-630
3EEAmy McGovern, Lisa Friedland, Michael Hay, Brian Gallagher, Andrew Fast, Jennifer Neville, David Jensen: Exploiting relational structure to understand publication patterns in high-energy physics. SIGKDD Explorations 5(2): 165-172 (2003)
2002
2 David Jensen, Jennifer Neville: Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning. ICML 2002: 259-266
1EEDavid Jensen, Jennifer Neville: Autocorrelation and Linkage Cause Bias in Evaluation of Relational Learners. ILP 2002: 101-116

Coauthor Index

1Luis von Ahn [15]
2Pelin Angin [16]
3Reynold Cheng [19]
4Philipp Cimiano [15]
5Dmitri A. Dolgov [15]
6Andrew Fast [3]
7Lisa Friedland [3] [4]
8Brian Gallagher [3] [6] [7]
9Henry G. Goldberg [10]
10Susanne E. Hambrusch [19]
11Michael Hay [3] [4] [5]
12James A. Hendler (Jim Hendler) [15]
13David Jensen [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [13] [14]
14John Komoroske [10]
15Anat Levin [15]
16Chris Mayfield [19]
17Amy McGovern [3]
18Peter Mika [15]
19Brian Milch [15]
20Louis-Philippe Morency [15]
21Boris Motik [15]
22Kelly Palmer [10]
23Sunil Prabhakar [19]
24Rahul Shah [19]
25Umang Sharan [17]
26Özgür Simsek [10]
27Sarvjeet Singh [19]
28Erik B. Sudderth [15]
29Rongjing Xiang [18]

Colors in the list of coauthors

Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)