Dawen Liang 个人学术档案 - 学术资源搜索

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	总计	2019 年至今
引用	6988	6096
h 指数	20	18
i10 指数	28	22

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Daniel P W EllisResearch Scientist, Google在 google.com 的电子邮件经过验证
Matthew D. HoffmanResearch Scientist, Google Research在 google.com 的电子邮件经过验证
Brian McFeeMusic and Performing Arts Professions / Center for Data Science, New York University在 nyu.edu 的电子邮件经过验证
Oriol NietoSenior Research Engineer at Adobe在 adobe.com 的电子邮件经过验证
David BleiProfessor of Statistics and Computer Science, Columbia University在 columbia.edu 的电子邮件经过验证
Colin RaffelUniversity of Toronto, Vector Institute and Hugging Face在 cs.toronto.edu 的电子邮件经过验证
Laurent CharlinAssociate Professor, HEC Montréal & Mila, Canada CIFAR AI Chair在 hec.ca 的电子邮件经过验证
Justin SalamonSenior Research Scientist, Adobe Research在 adobe.com 的电子邮件经过验证
Eric J. HumphreyLead Research Scientist, This One Ltd在 this.one 的电子邮件经过验证
James McInerneySenior Research Scientist, Netflix在 netflix.com 的电子邮件经过验证
Dustin TranResearch Scientist, Google在 google.com 的电子邮件经过验证
Alp KucukelbirAdjunct Professor of Computer Science, Columbia University在 cs.columbia.edu 的电子邮件经过验证
Maja RudolphLead Research Scientist, Bosch Center for AI在 cs.columbia.edu 的电子邮件经过验证
Adji Bousso DiengAssistant Professor of Computer Science, Princeton University在 princeton.edu 的电子邮件经过验证
Gus (Guangyu) XiaAssistant Professor of Machine Learning, MBZUAI在 nyu.edu 的电子邮件经过验证
Roger B. DannenbergProfessor of Computer Science, Carnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
Gautham J. MysoreSenior Principal Scientist, Adobe Research在 adobe.com 的电子邮件经过验证
Rachel M. BittnerSenior Research Scientist, Spotify在 spotify.com 的电子邮件经过验证
Nicolas GoldAssociate Professor in Computer Science, University College London在 ucl.ac.uk 的电子邮件经过验证
John PaisleyColumbia University在 columbia.edu 的电子邮件经过验证

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Dawen Liang

Research Scientist, Netflix Inc.

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Machine Learning Statistics Recommender Systems


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
librosa: Audio and music signal analysis in python. B McFee, C Raffel, D Liang, DPW Ellis, M McVicar, E Battenberg, O Nieto SciPy, 18-24, 2015	2960	2015
Variational autoencoders for collaborative filtering D Liang, RG Krishnan, MD Hoffman, T Jebara Proceedings of the 2018 World Wide Web Conference, 689-698, 2018	1279	2018
mir_eval: a transparent implementation of common MIR metrics C Raffel, B McFee, EJ Humphrey, J Salamon, O Nieto, D Liang, DPW Ellis ISMIR, 367-372, 2014	587	2014
Modeling user exposure in recommendation D Liang, L Charlin, J McInerney, DM Blei Proceedings of the 25th international conference on World Wide Web, 951-961, 2016	405	2016
Edward: A library for probabilistic modeling, inference, and criticism D Tran, A Kucukelbir, AB Dieng, M Rudolph, D Liang, DM Blei arXiv preprint arXiv:1610.09787, 2016	351	2016
Factorization meets the item embedding: Regularizing matrix factorization with item co-occurrence D Liang, J Altosaar, L Charlin, DM Blei Proceedings of the 10th ACM conference on recommender systems, 59-66, 2016	309	2016
Causal inference for recommender systems Y Wang, D Liang, L Charlin, DM Blei Proceedings of the 14th ACM Conference on Recommender Systems, 426-431, 2020	137	2020
Deep learning for recommender systems: A Netflix case study H Steck, L Baltrunas, E Elahi, D Liang, Y Raimond, J Basilico AI Magazine 42 (3), 7-18, 2021	119	2021
Causal inference for recommendation D Liang, L Charlin, DM Blei Causation: Foundation to Application, Workshop at UAI. AUAI 6 (41), 108, 2016	119	2016
Content-Aware Collaborative Music Recommendation Using Pre-trained Neural Networks D Liang, M Zhan, DPW Ellis ISMIR, 295-301, 2015	99	2015
On the challenges of learning with inference networks on sparse, high-dimensional data R Krishnan, D Liang, M Hoffman International conference on artificial intelligence and statistics, 143-151, 2018	91	2018
The deconfounded recommender: A causal inference approach to recommendation Y Wang, D Liang, L Charlin, DM Blei arXiv preprint arXiv:1808.06581, 2018	71	2018
Large language models as zero-shot conversational recommenders Z He, Z Xie, R Jha, H Steck, D Liang, Y Feng, BP Majumder, N Kallus, ... Proceedings of the 32nd ACM international conference on information and …, 2023	63	2023
librosa 0.5. 0 B McFee, M McVicar, O Nieto, S Balke, C Thome, D Liang, E Battenberg, ... Zenodo. URL: https://doi. org/10 5281, 2017	55	2017
librosa: 0.4. 1 B McFee, M McVicar, C Raffel, D Liang, O Nieto, E Battenberg, J Moore, ... Zenodo, 2015	47	2015
Beta Process Sparse Nonnegative Matrix Factorization for Music D Liang, MD Hoffman, DPW Ellis ISMIR, 375-380, 2013	34	2013
Methods and prospects for human–computer performance of popular music RB Dannenberg, NE Gold, D Liang, G Xia Computer Music Journal 38 (2), 36-50, 2014	30	2014
Music genre classification with the million song dataset D Liang, H Gu, B O’Connor Machine Learning Department, CMU, 2011	29	2011
Active scores: Representation and synchronization in human–computer performance of popular music RB Dannenberg, NE Gold, D Liang, G Xia Computer Music Journal 38 (2), 51-62, 2014	22	2014
Codebook-based Scalable Music Tagging with Poisson Matrix Factorization D Liang, J Paisley, DPW Ellis ISMIR, 167-172, 2014	21	2014

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