Eric Xing

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Amr AhmedSenior Staff Research Scientist, Google AIPatvirtintas el. paštas google.com
Jun ZhuProfessor of Computer Science, Tsinghua UniversityPatvirtintas el. paštas mail.tsinghua.edu.cn
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyPatvirtintas el. paštas cs.berkeley.edu
Noah A. SmithUniversity of Washington; Allen Institute for Artificial IntelligencePatvirtintas el. paštas cs.washington.edu
Garth Alan GibsonPresident & CEO, Vector Institute; Consulting Professor of Computer Science, Carnegie MellonPatvirtintas el. paštas vectorinstitute.ai
Mladen KolarThe University of Chicago, Booth School of BusinessPatvirtintas el. paštas chicagobooth.edu
Jacob EisensteinGoogle ResearchPatvirtintas el. paštas google.com
Kumar Avinava DubeyGoogle ResearchPatvirtintas el. paštas google.com
David BleiProfessor of Statistics and Computer Science, Columbia UniversityPatvirtintas el. paštas columbia.edu
Edoardo M AiroldiProfessor of Statistics & Data Science Temple University & PI, Harvard UniversityPatvirtintas el. paštas fas.harvard.edu
Li Fei-FeiProfessor of Computer Science, Stanford UniversityPatvirtintas el. paštas cs.stanford.edu
Andre MartinsCarnegie Mellon University and Instituto Superior TecnicoPatvirtintas el. paštas cs.cmu.edu
Gunhee KimAssociate Professor, Seoul National UniversityPatvirtintas el. paštas snu.ac.kr
William W. CohenGoogle AIPatvirtintas el. paštas google.com
Mario A. T. FigueiredoInstituto de Telecomunicações, Instituto Superior Técnico, Universidade de LisboaPatvirtintas el. paštas tecnico.ulisboa.pt
Bin ZhaoMachine Learning Department, Carnegie Mellon UniversityPatvirtintas el. paštas cs.cmu.edu
Pedro M. Q. AguiarInstitute for Systems and Robotics (ISR/IST), LARSyS, Instituto Superior Técnico, Univ LisboaPatvirtintas el. paštas isr.ist.utl.pt
Chong WangApplePatvirtintas el. paštas cs.princeton.edu
Steve HannekePurdue UniversityPatvirtintas el. paštas ttic.edu
Sinead WilliamsonAssistant professor, University of Texas at AustinPatvirtintas el. paštas mccombs.utexas.edu

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Eric Xing

President at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon U

Patvirtintas el. paštas cs.cmu.edu - Pagrindinis puslapis

Machine Learning ML Systems Optimization Statistics Network Analysis


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Distance metric learning with application to clustering with side-information E Xing, M Jordan, SJ Russell, A Ng Advances in neural information processing systems 15, 2002	3910	2002
Mixed membership stochastic blockmodels EM Airoldi, D Blei, S Fienberg, E Xing Advances in neural information processing systems 21, 2008	2515	2008
Theoretically principled trade-off between robustness and accuracy H Zhang, Y Yu, J Jiao, E Xing, L El Ghaoui, M Jordan International conference on machine learning, 7472-7482, 2019	1950	2019
Object bank: A high-level image representation for scene classification & semantic feature sparsification LJ Li, H Su, L Fei-Fei, E Xing Advances in neural information processing systems 23, 2010	1207	2010
Toward controlled generation of text Z Hu, Z Yang, X Liang, R Salakhutdinov, EP Xing International conference on machine learning, 1587-1596, 2017	1143*	2017
Feature selection for high-dimensional genomic microarray data EP Xing, MI Jordan, RM Karp Icml 1 (3), 601-608, 2001	946	2001
A latent variable model for geographic lexical variation J Eisenstein, B O’Connor, NA Smith, E Xing Proceedings of the 2010 conference on empirical methods in natural language …, 2010	881	2010
More effective distributed ml via a stale synchronous parallel parameter server Q Ho, J Cipar, H Cui, S Lee, JK Kim, PB Gibbons, GA Gibson, G Ganger, ... Advances in neural information processing systems 26, 2013	864	2013
Deep kernel learning AG Wilson, Z Hu, R Salakhutdinov, EP Xing Artificial intelligence and statistics, 370-378, 2016	832	2016
Harnessing deep neural networks with logic rules Z Hu, X Ma, Z Liu, E Hovy, E Xing arXiv preprint arXiv:1603.06318, 2016	699	2016
Tree-guided group lasso for multi-response regression with structured sparsity, with an application to eQTL mapping S Kim, EP Xing	647	2012
Petuum: A new platform for distributed machine learning on big data EP Xing, Q Ho, W Dai, JK Kim, J Wei, S Lee, X Zheng, P Xie, A Kumar, ... Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015	620	2015
Online detection of unusual events in videos via dynamic sparse coding B Zhao, L Fei-Fei, EP Xing CVPR 2011, 3313-3320, 2011	602	2011
Dags with no tears: Continuous optimization for structure learning X Zheng, B Aragam, PK Ravikumar, EP Xing Advances in neural information processing systems 31, 2018	584	2018
Neural architecture search with bayesian optimisation and optimal transport K Kandasamy, W Neiswanger, J Schneider, B Poczos, EP Xing Advances in neural information processing systems 31, 2018	583	2018
Discrete temporal models of social networks S Hanneke, W Fu, EP Xing	552	2010
Joint latent topic models for text and citations RM Nallapati, A Ahmed, EP Xing, WW Cohen Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008	548	2008
MedLDA: maximum margin supervised topic models for regression and classification J Zhu, A Ahmed, EP Xing Proceedings of the 26th annual international conference on machine learning …, 2009	543	2009
Self-challenging improves cross-domain generalization Z Huang, H Wang, EP Xing, D Huang Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020	430	2020
Learning robust global representations by penalizing local predictive power H Wang, S Ge, Z Lipton, EP Xing Advances in Neural Information Processing Systems 32, 2019	428	2019

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