Barnabas Poczos
Barnabas Poczos
Associate professor, Carnegie Mellon University
Verifierad e-postadress på cs.cmu.edu - Startsida
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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
4422017
Stochastic variance reduction for nonconvex optimization
SJ Reddi, A Hefny, S Sra, B Póczos, A Smola
International conference on machine learning, 314-323, 2016
3122016
Bayesian optimization with robust bayesian neural networks
JT Springenberg, A Klein, S Falkner, F Hutter
Advances in Neural Information Processing Systems, 4134-4142, 2016
250*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
2362017
Gradient descent provably optimizes over-parameterized neural networks
SS Du, X Zhai, B Poczos, A Singh
arXiv preprint arXiv:1810.02054, 2018
2222018
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
1502017
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
1382010
High dimensional Bayesian optimisation and bandits via additive models
K Kandasamy, J Schneider, B Póczos
International Conference on Machine Learning, 295-304, 2015
1312015
On variance reduction in stochastic gradient descent and its asynchronous variants
SJ Reddi, A Hefny, S Sra, B Poczos, AJ Smola
Advances in neural information processing systems, 2647-2655, 2015
1292015
Gradient descent learns one-hidden-layer cnn: Don't be afraid of spurious local minima
SS Du, JD Lee, Y Tian, B Poczos, A Singh
arXiv preprint arXiv:1712.00779, 2017
1212017
Local similarity-aware deep feature embedding
C Huang, CC Loy, X Tang
Advances in neural information processing systems, 1262-1270, 2016
113*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, 2016-2025, 2018
1072018
On the estimation of alpha-divergences
B Póczos, J Schneider
Proceedings of the Fourteenth International Conference on Artificial …, 2011
952011
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
862017
Deep learning with sets and point clouds
S Ravanbakhsh, J Schneider, B Poczos
arXiv preprint arXiv:1611.04500, 2016
862016
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
Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
802015
Distribution to distribution regression
J Oliva, B Póczos, J Schneider
International Conference on Machine Learning, 1049-1057, 2013
722013
Nonparametric divergence estimation with applications to machine learning on distributions
B Póczos, L Xiong, J Schneider
arXiv preprint arXiv:1202.3758, 2012
722012
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
712018
Hierarchical probabilistic models for group anomaly detection
L Xiong, B Póczos, J Schneider, A Connolly, J VanderPlas
Proceedings of the fourteenth international conference on artificial …, 2011
702011
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Artiklar 1–20