Kilian Weinberger

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Gao Huang （黄高）Assistant Professor, Tsinghua UniversityVerified email at tsinghua.edu.cn
Laurens van der MaatenResearch Director, Facebook AI ResearchVerified email at fb.com
Lawrence K SaulProfessor of Computer Science and Engineering, UC San DiegoVerified email at cs.ucsd.edu
Zhuang LiuPhD student at UC BerkeleyVerified email at berkeley.edu
Matt J. KusnerAssociate Professor, University College LondonVerified email at ucl.ac.uk
Zhixiang (Eddie) XuWashington UniversityVerified email at cse.wustl.edu
Minmin ChenResearch scientist, GoogleVerified email at google.com
Geoff PleissColumbia UniversityVerified email at columbia.edu
Stephen TyreeNVIDIAVerified email at nvidia.com
Jacob GardnerUniversity of PennsylvaniaVerified email at seas.upenn.edu
Fei ShaU of Southern CaliforniaVerified email at usc.edu
Yu SunEECS, UC BerkeleyVerified email at berkeley.edu
Felix WuASAPPVerified email at asapp.com
Chuan GuoResearch Scientist, Facebook AI ResearchVerified email at fb.com
Yixin ChenProfessor, Computer Science Department, Washington UniversityVerified email at cse.wustl.edu
Wenlin ChenFacebookVerified email at fb.com
Wei-Lun (Harry) ChaoAssistant Professor, The Ohio State UniversityVerified email at osu.edu
John BlitzerGoogle ResearchVerified email at google.com
Yan WangPh.D. student, Cornell UniversityVerified email at cornell.edu
Mark CampbellJohn A. Mellowes ‘60 Professor, Cornell UniversityVerified email at cornell.edu

Kilian Weinberger

Cornell University

Verified email at cornell.edu - Homepage

machine learning deep learning metric learning computer vision


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Densely connected convolutional networks G Huang, Z Liu, L Van Der Maaten, KQ Weinberger Proceedings of the IEEE conference on computer vision and pattern …, 2017	15126	2017
Distance metric learning for large margin nearest neighbor classification. KQ Weinberger, LK Saul Journal of machine learning research 10 (2), 2009	3471	2009
Distance metric learning for large margin nearest neighbor classification KQ Weinberger, J Blitzer, LK Saul Advances in neural information processing systems, 1473-1480, 2006	2192	2006
From word embeddings to document distances M Kusner, Y Sun, N Kolkin, K Weinberger International conference on machine learning, 957-966, 2015	1479	2015
On calibration of modern neural networks C Guo, G Pleiss, Y Sun, KQ Weinberger International Conference on Machine Learning, 1321-1330, 2017	1299	2017
Deep networks with stochastic depth G Huang, Y Sun, Z Liu, D Sedra, KQ Weinberger European conference on computer vision, 646-661, 2016	1145	2016
Unsupervised learning of image manifolds by semidefinite programming KQ Weinberger, LK Saul International journal of computer vision 70 (1), 77-90, 2006	1108	2006
Unsupervised learning of image manifolds by semidefinite programming KQ Weinberger, LK Saul CVPR 2, 988-995, 2004	1108	2004
Compressing neural networks with the hashing trick W Chen, J Wilson, S Tyree, K Weinberger, Y Chen International conference on machine learning, 2285-2294, 2015	947	2015
Feature hashing for large scale multitask learning K Weinberger, A Dasgupta, J Langford, A Smola, J Attenberg Proceedings of the 26th annual international conference on machine learning …, 2009	872	2009
Marginalized denoising autoencoders for domain adaptation M Chen, Z Xu, K Weinberger, F Sha arXiv preprint arXiv:1206.4683, 2012	742	2012
Learning a kernel matrix for nonlinear dimensionality reduction KQ Weinberger, F Sha, LK Saul Proceedings of the twenty-first international conference on Machine learning …, 2004	570	2004
Densely connected convolutional networks H Gao, L Zhuang, LVD Maaten, KQ Weinberger CVPR 1, 3, 2017	479	2017
Simplifying graph convolutional networks F Wu, A Souza, T Zhang, C Fifty, T Yu, K Weinberger International conference on machine learning, 6861-6871, 2019	420	2019
Condensenet: An efficient densenet using learned group convolutions G Huang, S Liu, L Van der Maaten, KQ Weinberger Proceedings of the IEEE conference on computer vision and pattern …, 2018	406	2018
Snapshot ensembles: Train 1, get m for free G Huang, Y Li, G Pleiss, Z Liu, JE Hopcroft, KQ Weinberger arXiv preprint arXiv:1704.00109, 2017	403	2017
Co-Training for Domain Adaptation. M Chen, KQ Weinberger, J Blitzer Nips 24, 2456-2464, 2011	383	2011
Fast solvers and efficient implementations for distance metric learning KQ Weinberger, LK Saul Proceedings of the 25th international conference on Machine learning, 1160-1167, 2008	351	2008
An introduction to nonlinear dimensionality reduction by maximum variance unfolding KQ Weinberger, LK Saul AAAI 6, 1683-1686, 2006	315	2006
Large margin multi-task metric learning S Parameswaran, KQ Weinberger Advances in neural information processing systems 23, 1867-1875, 2010	312	2010

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