Barnabas Poczos

Получаване на мой собствен потребителски профил

Позовавания

	Всички	От 2017
Позовавания	12023	10726
h-индекс	56	52
i10-индекс	139	119

3300

1650

825

2475

2009201020112012201320142015201620172018201920202021202255 29 73 118 83 164 229 402 644 1205 1963 2603 3215 1055

Публичен достъп

Преглед на всички

71 статии

3 статии

налични

неналични

Въз основа на изисквания при финансирането

Съавтори

Jeff SchneiderCarnegie Mellon UniversityПотвърден имейл адрес: cs.cmu.edu
Kirthevasan KandasamyUniversity of California, BerkeleyПотвърден имейл адрес: cs.cmu.edu
Sashank J. ReddiResearch Scientist, Google ResearchПотвърден имейл адрес: cs.cmu.edu
Chun-Liang LiResearch Scientist, GoogleПотвърден имейл адрес: google.com
Siamak RavanbakhshAssistant Professor, McGill UniversityПотвърден имейл адрес: cs.mcgill.ca
Aarti SinghAssociate Professor of Machine Learning Department, Carnegie Mellon UniversityПотвърден имейл адрес: cmu.edu
Lorincz, AndrasEotvos Lorand UniversityПотвърден имейл адрес: inf.elte.hu
Alex SmolaAmazon Web ServicesПотвърден имейл адрес: smola.org
Ruslan SalakhutdinovUPMC Professor, Machine Learning Department, CMUПотвърден имейл адрес: cs.cmu.edu
Zoltan SzaboProfessor, LSEПотвърден имейл адрес: lse.ac.uk
Manzil ZaheerGoogle ResearchПотвърден имейл адрес: cmu.edu
Junier OlivaAssistant Professor, University of North CarolinaПотвърден имейл адрес: cs.unc.edu
Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UПотвърден имейл адрес: cs.cmu.edu
Shashank SinghMax Planck Institute for Intelligent SystemsПотвърден имейл адрес: tuebingen.mpg.de
Larry WassermanProfessor, Department of Statistics and Machine Learning Department, Carnegie Mellon UniversityПотвърден имейл адрес: stat.cmu.edu
Simon Shaolei DuAssistant Professor, School of Computer Science and Engineering, University of WashingtonПотвърден имейл адрес: cs.washington.edu
Bharath SriperumbudurPennsylvania State UniversityПотвърден имейл адрес: psu.edu
Willie NeiswangerPostdoc, Computer Science, Stanford UniversityПотвърден имейл адрес: cs.stanford.edu
Suvrit SraMITПотвърден имейл адрес: mit.edu
Akshay KrishnamurthyUniversity of Massachusetts AmherstПотвърден имейл адрес: cs.umass.edu

Следене

Barnabas Poczos

Associate professor, Carnegie Mellon University

Потвърден имейл адрес: cs.cmu.edu - Начална страница

Artificial Intelligence Machine Learning Statistics


Заглавие Сортиране по цитати Сортиране по година Сортиране по заглавие	Позовавания Позовавания	Година
Deep sets M Zaheer, S Kottur, S Ravanbakhsh, B Poczos, RR Salakhutdinov, ... Advances in neural information processing systems 30, 2017	1423	2017
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 30, 2017	549	2017
Bayesian optimization with robust bayesian neural networks JT Springenberg, A Klein, S Falkner, F Hutter Advances in Neural Information Processing Systems, 4134-4142, 2016	501*	2016
Stochastic variance reduction for nonconvex optimization SJ Reddi, A Hefny, S Sra, B Poczos, A Smola International conference on machine learning, 314-323, 2016	499	2016
Gradient descent provably optimizes over-parameterized neural networks SS Du, X Zhai, B Poczos, A Singh arXiv preprint arXiv:1810.02054, 2018	436	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	402	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	290	2017
High dimensional Bayesian optimisation and bandits via additive models K Kandasamy, J Schneider, B Póczos International conference on machine learning, 295-304, 2015	251	2015
Characterizing and avoiding negative transfer Z Wang, Z Dai, B Póczos, J Carbonell Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019	193	2019
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	193	2018
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 30, 2017	188	2017
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, 2015	175	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 23, 2010	167	2010
Deep learning with sets and point clouds S Ravanbakhsh, J Schneider, B Poczos arXiv preprint arXiv:1611.04500, 2016	161	2016
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	147	2018
Parallelised Bayesian optimisation via Thompson sampling K Kandasamy, A Krishnamurthy, J Schneider, B Póczos International Conference on Artificial Intelligence and Statistics, 133-142, 2018	145	2018
Multi-fidelity bayesian optimisation with continuous approximations K Kandasamy, G Dasarathy, J Schneider, B Póczos International Conference on Machine Learning, 1799-1808, 2017	143	2017
Competence-based curriculum learning for neural machine translation EA Platanios, O Stretcu, G Neubig, B Poczos, TM Mitchell arXiv preprint arXiv:1903.09848, 2019	134	2019
Learning to predict the cosmological structure formation S He, Y Li, Y Feng, S Ho, S Ravanbakhsh, W Chen, B Póczos Proceedings of the National Academy of Sciences 116 (28), 13825-13832, 2019	131	2019
Equivariance through parameter-sharing S Ravanbakhsh, J Schneider, B Poczos International Conference on Machine Learning, 2892-2901, 2017	131	2017

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