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1Courses for Numerical Sampling and Inference
Courses for Numerical Sampling and Inference at Duke
4 years ago by @kirk86
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1Computational Statistics in Python
Computational Statistics in Python Course
4 years ago by @kirk86
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1Interpretable Two Sample Test
Interpretable Two Sample Test
4 years ago by @kirk86
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1Kernel Statistical Test for Independence
Kernel Statistical Test for Independence
4 years ago by @kirk86
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11020069264-MIT.pdf
https://dspace.mit.edu/bitstream/handle/1721.1/113440/1020069264-MIT.pdf?sequence=1
5 years ago by @kirk86
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1The Amazing Power of Randomness: NP=RP
A. Faragó. (2020)cite arxiv:2008.00601Comment: 58 pages (not including title page).
4 years ago by @kirk86
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2On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification
T. Lin, Z. Zheng, E. Chen, M. Cuturi, and M. Jordan. (2020)cite arxiv:2006.12301Comment: Correct some typos; 46 Pages, 41 figures.
4 years ago by @kirk86
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complexitygenerative-modelsmisspecificationoptimal-transportreadingsrobustnesssampling
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1Robust Sampling in Deep Learning
A. Aguilera, A. Artés-Rodríguez, and F. Pérez-Cruz. (2020)cite arxiv:2006.02734Comment: 8 pages, 3 figures.
4 years ago by @kirk86
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2Meta-Model-Based Meta-Policy Optimization
T. Hiraoka, T. Imagawa, V. Tangkaratt, T. Osa, T. Onishi, and Y. Tsuruoka. (2020)cite arxiv:2006.02608.
4 years ago by @kirk86
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1Likelihood Ratio Gradient Estimation for Steady-State Parameters
P. Glynn, and M. Olvera-Cravioto. Stochastic Systems, 9 (2): 83--100 (June 2019)
4 years ago by @kirk86
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2On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient
J. Tang, and P. Abbeel. (2010)
4 years ago by @kirk86
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2From Importance Sampling to Doubly Robust Policy Gradient
J. Huang, and N. Jiang. (2019)cite arxiv:1910.09066Comment: 26 pages; 2 figures.
4 years ago by @kirk86
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2Thompson Sampling for Combinatorial Semi-bandits with Sleeping Arms and Long-Term Fairness Constraints
Z. Huang, Y. Xu, B. Hu, Q. Wang, and J. Pan. (2020)cite arxiv:2005.06725.
4 years ago by @kirk86
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2Non-Adaptive Adaptive Sampling on Turnstile Streams
S. Mahabadi, I. Razenshteyn, D. Woodruff, and S. Zhou. (2020)cite arxiv:2004.10969Comment: To appear at STOC 2020.
4 years ago by @kirk86
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3On Biased Random Walks, Corrupted Intervals, and Learning Under Adversarial Design
D. Berend, A. Kontorovich, L. Reyzin, and T. Robinson. (2020)cite arxiv:2003.13561Comment: 18 pages.
4 years ago by @kirk86
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2Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
R. Zhang, C. Li, J. Zhang, C. Chen, and A. Wilson. International Conference on Learning Representations, (2020)
4 years ago by @kirk86
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2Equivariant flow-based sampling for lattice gauge theory
G. Kanwar, M. Albergo, D. Boyda, K. Cranmer, D. Hackett, S. Racanière, D. Rezende, and P. Shanahan. (2020)cite arxiv:2003.06413Comment: 6 pages, 4 figures.
4 years ago by @kirk86
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1Monte Carlo theory, methods and examples
A. Owen. (2013)
4 years ago by @kirk86
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1A Tutorial on Bridge Sampling
Q. Gronau, A. Sarafoglou, D. Matzke, A. Ly, U. Boehm, M. Marsman, D. Leslie, J. Forster, E. Wagenmakers, and H. Steingroever. (2017)cite arxiv:1703.05984.
4 years ago by @kirk86
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2Creating High Resolution Images with a Latent Adversarial Generator
D. Berthelot, P. Milanfar, and I. Goodfellow. (2020)
4 years ago by @kirk86
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1On the Sample Complexity of Reinforcement Learning
M. Kakade. (2003)
4 years ago by @kirk86
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3Predictive Sampling with Forecasting Autoregressive Models
A. Wiggers, and E. Hoogeboom. (2020)cite arxiv:2002.09928Comment: 13 pages, 16 figures.
4 years ago by @kirk86
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2Generalized Bayesian Filtering via Sequential Monte Carlo
A. Boustati, Ö. Akyildiz, T. Damoulas, and A. Johansen. (2020)cite arxiv:2002.09998.
4 years ago by @kirk86
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2On Learning Distributions from their Samples
S. Kamath, A. Orlitsky, D. Pichapati, and A. Suresh. Proceedings of The 28th Conference on Learning Theory, volume 40 of Proceedings of Machine Learning Research, page 1066--1100. Paris, France, PMLR, (03--06 Jul 2015)
4 years ago by @kirk86
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2On How Well Generative Adversarial Networks Learn Densities: Nonparametric and Parametric Results
T. Liang. (2018)cite arxiv:1811.03179Comment: 36 pages, 3 figures.
4 years ago by @kirk86
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BibSonomy

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1Courses for Numerical Sampling and Inference

1Computational Statistics in Python

1Interpretable Two Sample Test

1Kernel Statistical Test for Independence

11020069264-MIT.pdf

publications (hide)81
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1The Amazing Power of Randomness: NP=RP

2On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification

1Robust Sampling in Deep Learning

2Meta-Model-Based Meta-Policy Optimization

1Likelihood Ratio Gradient Estimation for Steady-State Parameters

2On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient

2From Importance Sampling to Doubly Robust Policy Gradient

2Thompson Sampling for Combinatorial Semi-bandits with Sleeping Arms and Long-Term Fairness Constraints

2Non-Adaptive Adaptive Sampling on Turnstile Streams

3On Biased Random Walks, Corrupted Intervals, and Learning Under Adversarial Design

2Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning

2Equivariant flow-based sampling for lattice gauge theory

1Monte Carlo theory, methods and examples

1A Tutorial on Bridge Sampling

2Creating High Resolution Images with a Latent Adversarial Generator

1On the Sample Complexity of Reinforcement Learning

3Predictive Sampling with Forecasting Autoregressive Models

2Generalized Bayesian Filtering via Sequential Monte Carlo

2On Learning Distributions from their Samples

2On How Well Generative Adversarial Networks Learn Densities: Nonparametric and Parametric Results

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