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Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments.

A. Popescul, L. Ungar, D. Pennock, and S. Lawrence. UAI, page 437-444. Morgan Kaufmann, (2001)

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H. Binz

H. Bungartz

Stefanie Ungar University of Stuttgart

H. Binz

Other publications of authors with the same name

Penn: Using Word Similarities to better Estimate Sentence Similarity.S. Jha, H. Schwartz, and L. Ungar. SemEval@NAACL-HLT, page 679-683. The Association for Computer Linguistics, (2012)Spectral Learning Algorithms for Natural Language Processing.S. Cohen, M. Collins, D. Foster, K. Stratos, and L. Ungar. HLT-NAACL, page 13-15. The Association for Computational Linguistics, (2013)An Empirical Study of the Behavior of Active Learning for Word Sense Disambiguation.J. Chen, A. Schein, L. Ungar, and M. Palmer. HLT-NAACL, The Association for Computational Linguistics, (2006)Localizing Search in Reinforcement Learning.G. Grudic, and L. Ungar. AAAI/IAAI, page 590-595. AAAI Press / The MIT Press, (2000)Efficient Feature Selection in the Presence of Multiple Feature Classes.P. Dhillon, D. Foster, and L. Ungar. ICDM, page 779-784. IEEE Computer Society, (2008)Faster Ridge Regression via the Subsampled Randomized Hadamard Transform.Y. Lu, P. Dhillon, D. Foster, and L. Ungar. NIPS, page 369-377. (2013)Static and Dynamic Analysis of the Internet's Susceptibility to Faults and Attacks.S. Park, A. Khrabrov, D. Pennock, S. Lawrence, C. Giles, and L. Ungar. INFOCOM, page 2144-2154. IEEE Computer Society, (2003)Choosing the Right Words: Characterizing and Reducing Error of the Word Count Approach.H. Schwartz, J. Eichstaedt, E. Blanco, L. Dziurzynski, M. Kern, S. Ramones, M. Seligman, and L. Ungar. *SEM@NAACL-HLT, page 296-305. Association for Computational Linguistics, (2013)Assessing Objective Recommendation Quality through Political Forecasting.H. Schwartz, M. Rouhizadeh, M. Bishop, P. Tetlock, B. Mellers, and L. Ungar. EMNLP, page 2348-2357. Association for Computational Linguistics, (2017)The Remarkable Benefit of User-Level Aggregation for Lexical-based Population-Level Predictions.S. Giorgi, D. Preotiuc-Pietro, A. Buffone, D. Rieman, L. Ungar, and H. Schwartz. EMNLP, page 1167-1172. Association for Computational Linguistics, (2018)

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Disambiguation of "Ungar, Lyle H."

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Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments.

Please choose a person to relate this publication to

H. Binz

H. Bungartz

Stefanie Ungar University of Stuttgart

H. Binz

H. Binz

Other publications of authors with the same name

Disambiguation

PUMA

Disambiguation of "Ungar, Lyle H."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments.

Please choose a person to relate this publication to

H. Binz

H. Bungartz

Stefanie Ungar University of Stuttgart

H. Binz

H. Binz

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments.