Barnabas Poczos
Barnabas Poczos
Associate professor, Carnegie Mellon University
Verified email at cs.cmu.edu - Homepage
Title
Cited by
Cited by
Year
Deep sets
M Zaheer, S Kottur, S Ravanbakhsh, B Poczos, R Salakhutdinov, A Smola
arXiv preprint arXiv:1703.06114, 2017
10742017
Gradient descent provably optimizes over-parameterized neural networks
SS Du, X Zhai, B Poczos, A Singh
arXiv preprint arXiv:1810.02054, 2018
5792018
Stochastic variance reduction for nonconvex optimization
SJ Reddi, A Hefny, S Sra, B Poczos, A Smola
International conference on machine learning, 314-323, 2016
4572016
Mmd gan: Towards deeper understanding of moment matching network
CL Li, WC Chang, Y Cheng, Y Yang, B Póczos
arXiv preprint arXiv:1705.08584, 2017
4452017
Bayesian optimization with robust bayesian neural networks
JT Springenberg, A Klein, S Falkner, F Hutter
Advances in Neural Information Processing Systems, 4134-4142, 2016
403*2016
Neural architecture search with bayesian optimisation and optimal transport
K Kandasamy, W Neiswanger, J Schneider, B Poczos, E Xing
arXiv preprint arXiv:1802.07191, 2018
3222018
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
2592017
High dimensional Bayesian optimisation and bandits via additive models
K Kandasamy, J Schneider, B Póczos
International conference on machine learning, 295-304, 2015
2092015
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
1712018
Estimation of R\'enyi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs
D Pál, B Póczos, C Szepesvári
arXiv preprint arXiv:1003.1954, 2010
1702010
On variance reduction in stochastic gradient descent and its asynchronous variants
SJ Reddi, A Hefny, S Sra, B Poczos, A Smola
arXiv preprint arXiv:1506.06840, 2015
1662015
Gradient descent can take exponential time to escape saddle points
SS Du, C Jin, JD Lee, MI Jordan, B Poczos, A Singh
arXiv preprint arXiv:1705.10412, 2017
1642017
Deep learning with sets and point clouds
S Ravanbakhsh, J Schneider, B Poczos
arXiv preprint arXiv:1611.04500, 2016
1392016
A survey on graph kernels
NM Kriege, FD Johansson, C Morris
Applied Network Science 5 (1), 1-42, 2020
1352020
Multi-fidelity bayesian optimisation with continuous approximations
K Kandasamy, G Dasarathy, J Schneider, B Póczos
International Conference on Machine Learning, 1799-1808, 2017
1202017
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
1192015
Parallelised bayesian optimisation via thompson sampling
K Kandasamy, A Krishnamurthy, J Schneider, B Póczos
International Conference on Artificial Intelligence and Statistics, 133-142, 2018
1132018
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
1132018
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
1122019
On the estimation of alpha-divergences
B Póczos, J Schneider
Proceedings of the Fourteenth International Conference on Artificial …, 2011
1102011
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