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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, RR Salakhutdinov, ...
Advances in neural information processing systems 30, 2017
14232017
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
5492017
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
4992016
Gradient descent provably optimizes over-parameterized neural networks
SS Du, X Zhai, B Poczos, A Singh
arXiv preprint arXiv:1810.02054, 2018
4362018
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
4022018
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
2902017
High dimensional Bayesian optimisation and bandits via additive models
K Kandasamy, J Schneider, B Póczos
International conference on machine learning, 295-304, 2015
2512015
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
1932019
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
1932018
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
1882017
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
1752015
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
1672010
Deep learning with sets and point clouds
S Ravanbakhsh, J Schneider, B Poczos
arXiv preprint arXiv:1611.04500, 2016
1612016
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
1472018
Parallelised Bayesian optimisation via Thompson sampling
K Kandasamy, A Krishnamurthy, J Schneider, B Póczos
International Conference on Artificial Intelligence and Statistics, 133-142, 2018
1452018
Multi-fidelity bayesian optimisation with continuous approximations
K Kandasamy, G Dasarathy, J Schneider, B Póczos
International Conference on Machine Learning, 1799-1808, 2017
1432017
Competence-based curriculum learning for neural machine translation
EA Platanios, O Stretcu, G Neubig, B Poczos, TM Mitchell
arXiv preprint arXiv:1903.09848, 2019
1342019
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
1312019
Equivariance through parameter-sharing
S Ravanbakhsh, J Schneider, B Poczos
International Conference on Machine Learning, 2892-2901, 2017
1312017
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