Barnabas Poczos

Citata da

	Tutte	Dal 2016
Citazioni	8480	7548
Indice H	49	47
i10-index	132	115

2900

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200620072008200920102011201220132014201520162017201820192020202126 37 15 56 36 78 97 107 164 230 449 679 1266 2189 2858 53

Coautori

Jeff SchneiderCarnegie Mellon UniversityEmail verificata su cs.cmu.edu
Kirthevasan KandasamyUniversity of California, BerkeleyEmail verificata su cs.cmu.edu
Sashank J. ReddiResearch Scientist, Google ResearchEmail verificata su cs.cmu.edu
Lorincz, AndrasEotvos Lorand UniversityEmail verificata su inf.elte.hu
Chun-Liang LiResearch Scientist, GoogleEmail verificata su google.com
Siamak RavanbakhshAssistant Professor, McGill UniversityEmail verificata su cs.mcgill.ca
Alex SmolaAmazon Web ServicesEmail verificata su smola.org
Zoltan SzaboSenior Researcher, Center of Applied Mathematics (CMAP), École PolytechniqueEmail verificata su polytechnique.edu
Junier OlivaAssistant Professor, University of North CarolinaEmail verificata su cs.unc.edu
Larry WassermanProfessor, Department of Statistics and Machine Learning Department, Carnegie Mellon UniversityEmail verificata su stat.cmu.edu
Ruslan SalakhutdinovUPMC Professor, Machine Learning Department, CMUEmail verificata su cs.cmu.edu
Eric XingProfessor of Machine Learning, Language Technology, Computer Science, Cargenie Mellon UniversityEmail verificata su cs.cmu.edu
Manzil ZaheerGoogle ResearchEmail verificata su cmu.edu
Simon Shaolei DuAssistant Professor, School of Computer Science and Engineering, University of WashingtonEmail verificata su cs.washington.edu
Bharath SriperumbudurPennsylvania State UniversityEmail verificata su psu.edu
Shashank SinghCarnegie Mellon University; GoogleEmail verificata su google.com
Suvrit SraMITEmail verificata su mit.edu
Willie NeiswangerPostdoc, Computer Science, Stanford UniversityEmail verificata su cs.stanford.edu
Danica J. SutherlandUniversity of British ColumbiaEmail verificata su cs.ubc.ca
Akshay KrishnamurthyUniversity of Massachusetts AmherstEmail verificata su cs.umass.edu

Barnabas Poczos

Associate professor, Carnegie Mellon University

Email verificata su cs.cmu.edu - Home page

Artificial Intelligence Machine Learning Statistics


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
Deep sets M Zaheer, S Kottur, S Ravanbakhsh, B Poczos, RR Salakhutdinov, ... Advances in neural information processing systems, 3391-3401, 2017	777	2017
Gradient descent provably optimizes over-parameterized neural networks SS Du, X Zhai, B Poczos, A Singh arXiv preprint arXiv:1810.02054, 2018	419	2018
Stochastic variance reduction for nonconvex optimization SJ Reddi, A Hefny, S Sra, B Poczos, A Smola International conference on machine learning, 314-323, 2016	410	2016
Bayesian optimization with robust bayesian neural networks JT Springenberg, A Klein, S Falkner, F Hutter Advances in Neural Information Processing Systems, 4134-4142, 2016	363*	2016
Mmd gan: Towards deeper understanding of moment matching network CL Li, WC Chang, Y Cheng, Y Yang, B Póczos Advances in neural information processing systems, 2203-2213, 2017	340	2017
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, 2016-2025, 2018	218	2018
One Network to Solve Them All--Solving Linear Inverse Problems Using Deep Projection Models JH Rick Chang, CL Li, B Poczos, BVK Vijaya Kumar, ... Proceedings of the IEEE International Conference on Computer Vision, 5888-5897, 2017	212	2017
High dimensional Bayesian optimisation and bandits via additive models K Kandasamy, J Schneider, B Póczos International conference on machine learning, 295-304, 2015	177	2015
On variance reduction in stochastic gradient descent and its asynchronous variants S J Reddi, A Hefny, S Sra, B Poczos, AJ Smola Advances in neural information processing systems 28, 2647-2655, 2015	156	2015
Estimation of Rényi entropy and mutual information based on generalized nearest-neighbor graphs D Pál, B Póczos, C Szepesvári Advances in neural information processing systems, 1849-1857, 2010	154	2010
Gradient descent learns one-hidden-layer cnn: Don’t be afraid of spurious local minima S Du, J Lee, Y Tian, A Singh, B Poczos International Conference on Machine Learning, 1339-1348, 2018	151	2018
Local similarity-aware deep feature embedding C Huang, CC Loy, X Tang arXiv preprint arXiv:1610.08904, 2016	142*	2016
Gradient descent can take exponential time to escape saddle points SS Du, C Jin, JD Lee, MI Jordan, A Singh, B Poczos Advances in neural information processing systems, 1067-1077, 2017	131	2017
Deep learning with sets and point clouds S Ravanbakhsh, J Schneider, B Poczos arXiv preprint arXiv:1611.04500, 2016	114	2016
On the decreasing power of kernel and distance based nonparametric hypothesis tests in high dimensions A Ramdas, SJ Reddi, B Póczos, A Singh, L Wasserman Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015	102	2015
On the estimation of alpha-divergences B Póczos, J Schneider Proceedings of the Fourteenth International Conference on Artificial …, 2011	102	2011
CMU DeepLens: deep learning for automatic image-based galaxy–galaxy strong lens finding F Lanusse, Q Ma, N Li, TE Collett, CL Li, S Ravanbakhsh, R Mandelbaum, ... Monthly Notices of the Royal Astronomical Society 473 (3), 3895-3906, 2018	91	2018
Gaussian process bandit optimisation with multi-fidelity evaluations K Kandasamy, G Dasarathy, JB Oliva, J Schneider, B Póczos Advances in neural information processing systems, 992-1000, 2016	90	2016
Stochastic frank-wolfe methods for nonconvex optimization SJ Reddi, S Sra, B Póczos, A Smola 2016 54th Annual Allerton Conference on Communication, Control, and …, 2016	87	2016
Group anomaly detection using flexible genre models L Xiong, B Póczos, J Schneider Advances in neural information processing systems 24, 1071-1079, 2011	87	2011

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