Kilian Weinberger

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Gao Huang （黄高）Associate Professor, Tsinghua UniversityPatvirtintas el. paštas tsinghua.edu.cn
Laurens van der MaatenDistinguished Research Scientist, Llama Team, Meta AIPatvirtintas el. paštas meta.com
Felix WuGoogle DeepMindPatvirtintas el. paštas google.com
Geoff PleissAssistant Professor, University of British ColumbiaPatvirtintas el. paštas stat.ubc.ca
Zhuang LiuResearch Scientist, FAIR, MetaPatvirtintas el. paštas berkeley.edu
Mark CampbellJohn A. Mellowes ‘60 Professor, Cornell UniversityPatvirtintas el. paštas cornell.edu
Chuan GuoResearch Scientist, FAIR, MetaPatvirtintas el. paštas fb.com
Wei-Lun (Harry) Chao 趙偉崙Assistant Professor, The Ohio State UniversityPatvirtintas el. paštas osu.edu
bharath hariharanCornell UniversityPatvirtintas el. paštas cs.cornell.edu
Jacob GardnerUniversity of PennsylvaniaPatvirtintas el. paštas seas.upenn.edu
Minmin ChenResearch scientist, Google DeepmindPatvirtintas el. paštas google.com
Yu SunPostdoc, Stanford UniversityPatvirtintas el. paštas cs.stanford.edu
Matt J. KusnerUniversity College LondonPatvirtintas el. paštas ucl.ac.uk
Yan WangSenior Research Scientist, NVIDIA ResearchPatvirtintas el. paštas nvidia.com
Fei ShaGoogle ResearchPatvirtintas el. paštas feisha.org
Stephen TyreeNVIDIAPatvirtintas el. paštas nvidia.com
Varsha KishoreCornell UniversityPatvirtintas el. paštas cornell.edu
Yurong YouNVIDIA ResearchPatvirtintas el. paštas nvidia.com
Zhixiang (Eddie) XuWashington UniversityPatvirtintas el. paštas cse.wustl.edu
Tianyi ZhangStanford UniversityPatvirtintas el. paštas cornell.edu

Stebėti

Kilian Weinberger

Cornell University

Patvirtintas el. paštas cornell.edu - Pagrindinis puslapis

machine learning deep learning metric learning computer vision


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
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	51935	2017
On calibration of modern neural networks C Guo, G Pleiss, Y Sun, KQ Weinberger International conference on machine learning, 1321-1330, 2017	6901	2017
Bertscore: Evaluating text generation with bert T Zhang, V Kishore, F Wu, KQ Weinberger, Y Artzi arXiv preprint arXiv:1904.09675, 2019	5995	2019
Distance metric learning for large margin nearest neighbor classification. KQ Weinberger, LK Saul Journal of machine learning research 10 (2), 2009	5033	2009
Simplifying graph convolutional networks F Wu, A Souza, T Zhang, C Fifty, T Yu, K Weinberger International conference on machine learning, 6861-6871, 2019	3946	2019
From word embeddings to document distances M Kusner, Y Sun, N Kolkin, K Weinberger International conference on machine learning, 957-966, 2015	2973	2015
Deep networks with stochastic depth G Huang, Y Sun, Z Liu, D Sedra, KQ Weinberger Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016	2890	2016
Distance metric learning for large margin nearest neighbor classification KQ Weinberger, J Blitzer, L Saul Advances in neural information processing systems 18, 2005	2567	2005
Advances in neural information processing systems A Krizhevsky (No Title), 1097, 2012	2305	2012
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	1473	2015
Gpytorch: Blackbox matrix-matrix gaussian process inference with gpu acceleration J Gardner, G Pleiss, KQ Weinberger, D Bindel, AG Wilson Advances in neural information processing systems 31, 2018	1447	2018
Densely connected convolutional networks H Gao, L Zhuang, LVD Maaten, KQ Weinberger Proceedings of the IEEE conference on computer vision and pattern …, 2017	1443	2017
Pseudo-lidar from visual depth estimation: Bridging the gap in 3d object detection for autonomous driving Y Wang, WL Chao, D Garg, B Hariharan, M Campbell, KQ Weinberger Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019	1283	2019
Unsupervised learning of image manifolds by semidefinite programming KQ Weinberger, LK Saul International journal of computer vision 70 (1), 77-90, 2006	1255	2006
Unsupervised learning of image manifolds by semidefinite programming KQ Weinberger, LK Saul CVPR 2, 988-995, 2004	1255	2004
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	1246	2009
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	1180	2017
On fairness and calibration G Pleiss, M Raghavan, F Wu, J Kleinberg, KQ Weinberger Advances in neural information processing systems 30, 2017	1131	2017
Marginalized denoising auto-encoders for nonlinear representations M Chen, K Weinberger, F Sha, Y Bengio International conference on machine learning, 1476-1484, 2014	1115	2014
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	1039	2018

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