Barnabas Poczos

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Jeff SchneiderCarnegie Mellon UniversityEmail yang diverifikasi di cs.cmu.edu
Kirthevasan KandasamyUniversity of Wisconsin-MadisonEmail yang diverifikasi di cs.wisc.edu
Siamak RavanbakhshAssistant Professor, McGill UniversityEmail yang diverifikasi di cs.mcgill.ca
Sashank J. ReddiResearch Scientist, Google ResearchEmail yang diverifikasi di cs.cmu.edu
Aarti SinghProfessor of Machine Learning Department, Carnegie Mellon UniversityEmail yang diverifikasi di cmu.edu
Alex SmolaBoson AIEmail yang diverifikasi di smola.org
Chun-Liang LiResearch Scientist, AppleEmail yang diverifikasi di apple.com
Lorincz, AndrasEotvos Lorand UniversityEmail yang diverifikasi di inf.elte.hu
Ruslan SalakhutdinovUPMC Professor, Machine Learning Department, CMUEmail yang diverifikasi di cs.cmu.edu
Shashank SinghMax Planck Institute for Intelligent SystemsEmail yang diverifikasi di tuebingen.mpg.de
Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UEmail yang diverifikasi di cs.cmu.edu
Manzil ZaheerGoogle ResearchEmail yang diverifikasi di cmu.edu
Junier OlivaAssociate Professor, University of North CarolinaEmail yang diverifikasi di cs.unc.edu
Zoltan SzaboProfessor, LSEEmail yang diverifikasi di lse.ac.uk
Simon Shaolei DuAssistant Professor, School of Computer Science and Engineering, University of WashingtonEmail yang diverifikasi di cs.washington.edu
Willie NeiswangerAssistant Professor of Computer Science, University of Southern CaliforniaEmail yang diverifikasi di cs.stanford.edu
Larry WassermanProfessor, Department of Statistics and Machine Learning Department, Carnegie Mellon UniversityEmail yang diverifikasi di stat.cmu.edu
Bharath SriperumbudurPennsylvania State UniversityEmail yang diverifikasi di psu.edu
Suvrit SraTUM and MITEmail yang diverifikasi di mit.edu
Akshay KrishnamurthyUniversity of Massachusetts AmherstEmail yang diverifikasi di cs.umass.edu

Ikuti

Barnabas Poczos

Associate professor, Carnegie Mellon University

Email yang diverifikasi di cs.cmu.edu - Beranda

Artificial Intelligence Machine Learning Statistics


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Deep sets M Zaheer, S Kottur, S Ravanbakhsh, B Poczos, RR Salakhutdinov, ... Advances in neural information processing systems 30, 2017	2948	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	865	2017
Gradient descent provably optimizes over-parameterized neural networks SS Du, X Zhai, B Poczos, A Singh arXiv preprint arXiv:1810.02054, 2018	831	2018
Bayesian optimization with robust bayesian neural networks JT Springenberg, A Klein, S Falkner, F Hutter Advances in Neural Information Processing Systems, 4134-4142, 2016	799*	2016
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	722	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	681	2016
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	578	2019
High dimensional Bayesian optimisation and bandits via additive models K Kandasamy, J Schneider, B Póczos International conference on machine learning, 295-304, 2015	430	2015
Found in translation: Learning robust joint representations by cyclic translations between modalities H Pham, PP Liang, T Manzini, LP Morency, B Póczos Proceedings of the AAAI conference on artificial intelligence 33 (01), 6892-6899, 2019	424	2019
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	398	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	368	2019
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	305	2017
Graph neural tangent kernel: Fusing graph neural networks with graph kernels SS Du, K Hou, RR Salakhutdinov, B Poczos, R Wang, K Xu Advances in neural information processing systems 32, 2019	300	2019
Parallelised Bayesian optimisation via Thompson sampling K Kandasamy, A Krishnamurthy, J Schneider, B Póczos International conference on artificial intelligence and statistics, 133-142, 2018	295	2018
Equivariance through parameter-sharing S Ravanbakhsh, J Schneider, B Poczos International conference on machine learning, 2892-2901, 2017	274	2017
Multi-fidelity bayesian optimisation with continuous approximations K Kandasamy, G Dasarathy, J Schneider, B Póczos International conference on machine learning, 1799-1808, 2017	257	2017
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	256	2019
Point cloud gan CL Li, M Zaheer, Y Zhang, B Poczos, R Salakhutdinov arXiv preprint arXiv:1810.05795, 2018	255	2018
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	249	2018
Tuning hyperparameters without grad students: Scalable and robust bayesian optimisation with dragonfly K Kandasamy, KR Vysyaraju, W Neiswanger, B Paria, CR Collins, ... Journal of Machine Learning Research 21 (81), 1-27, 2020	228	2020

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