Barnabas Poczos
Barnabas Poczos
Associate professor, Carnegie Mellon University
Adresse e-mail validée de cs.cmu.edu - Page d'accueil
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Deep sets
M Zaheer, S Kottur, S Ravanbakhsh, B Poczos, RR Salakhutdinov, ...
Advances in neural information processing systems, 3391-3401, 2017
7072017
Stochastic variance reduction for nonconvex optimization
SJ Reddi, A Hefny, S Sra, B Poczos, A Smola
International conference on machine learning, 314-323, 2016
3902016
Gradient descent provably optimizes over-parameterized neural networks
SS Du, X Zhai, B Poczos, A Singh
arXiv preprint arXiv:1810.02054, 2018
3842018
Bayesian optimization with robust bayesian neural networks
JT Springenberg, A Klein, S Falkner, F Hutter
Advances in Neural Information Processing Systems, 4134-4142, 2016
342*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
3242017
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
2042017
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
1982018
High dimensional Bayesian optimisation and bandits via additive models
K Kandasamy, J Schneider, B Póczos
International conference on machine learning, 295-304, 2015
1652015
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
1522015
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
1502010
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
1492018
Local similarity-aware deep feature embedding
C Huang, CC Loy, X Tang
arXiv preprint arXiv:1610.08904, 2016
139*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
1202017
Deep learning with sets and point clouds
S Ravanbakhsh, J Schneider, B Poczos
arXiv preprint arXiv:1611.04500, 2016
1042016
On the estimation of alpha-divergences
B Póczos, J Schneider
Proceedings of the Fourteenth International Conference on Artificial …, 2011
1002011
On the decreasing power of kernel and distance based nonparametric hypothesis tests in high dimensions
SJ Reddi, A Ramdas, B Póczos, A Singh, L Wasserman
arXiv preprint arXiv:1406.2083, 2014
952014
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
872018
Gaussian process bandit optimisation with multi-fidelity evaluations
K Kandasamy, G Dasarathy, JB Oliva, J Schneider, B Póczos
Advances in neural information processing systems 29, 992-1000, 2016
852016
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
842016
Nonparametric divergence estimation with applications to machine learning on distributions
B Póczos, L Xiong, J Schneider
arXiv preprint arXiv:1202.3758, 2012
822012
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