Yuansi Chen

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Bin YUProfessor of Statistics and EECS, UC BerkeleyVerified email at stat.berkeley.edu
Raaz DwivediAssistant Professor, Cornell TechVerified email at cornell.edu
Martin WainwrightProfessor, EECS/Mathematics, Massachusetts Institute of TechnologyVerified email at mit.edu
Chi JinAssistant Professor, Princeton UniversityVerified email at princeton.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Nicolas FlammarionEPFLVerified email at epfl.ch
Yi-An MaUC San DiegoVerified email at ucsd.edu
Reza Abbasi-AslAssistant Professor, Neurology, Bioengineering and Therapeutic Sciences, UCSFVerified email at ucsf.edu
Adam BloniarzGoogleVerified email at google.com
Ronen EldanWeizmann InstituteVerified email at weizmann.ac.il
Julien MairalInria - Univ. Grenoble AlpesVerified email at inria.fr
Zaid HarchaouiUniversity of WashingtonVerified email at uw.edu
Peter BühlmannProfessor of Statistics and Mathematics, ETH ZurichVerified email at stat.math.ethz.ch
Jack L. GALLANTUniversity of California at BerkeleyVerified email at berkeley.edu
Scott C SchmidlerAssociate Professor of Statistical Science and Computer Science, Duke UniversityVerified email at duke.edu
Khashayar GatmiryGraduate student, Massachusetts Institute of TechnologyVerified email at mit.edu
Ben WillmoreOxford UniversityVerified email at dpag.ox.ac.uk
Wooseok HaUniversity of California, BerkeleyVerified email at berkeley.edu
Armeen TaebUniversity of WashingtonVerified email at uw.edu

Yuansi Chen

Seminar for Statistics, D-MATH, ETH Zurich

Verified email at stat.math.ethz.ch - Homepage

MCMC Statistical Learning Optimization Computational neuroscience


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Log-concave sampling: Metropolis-Hastings algorithms are fast! R Dwivedi, Y Chen, MJ Wainwright, B Yu The Journal of Machine Learning Research 20 (183), 1-42, 2019	307	2019
Sampling can be faster than optimization YA Ma, Y Chen, C Jin, N Flammarion, MI Jordan Proceedings of the National Academy of Sciences 116 (42), 20881-20885, 2019	235	2019
An almost constant lower bound of the isoperimetric coefficient in the KLS conjecture Y Chen Geometric and Functional Analysis 31, 34-61, 2021	156	2021
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients Y Chen, R Dwivedi, MJ Wainwright, B Yu Journal of Machine Learning Research 21 (92), 1-71, 2020	117	2020
Fast and robust archetypal analysis for representation learning Y Chen, J Mairal, Z Harchaoui Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014	115	2014
Fast MCMC sampling algorithms on polytopes Y Chen, R Dwivedi, MJ Wainwright, B Yu Journal of Machine Learning Research 19 (55), 1-86, 2018	102	2018
Localization schemes: A framework for proving mixing bounds for Markov chains Y Chen, R Eldan 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS …, 2022	88	2022
Minimax mixing time of the Metropolis-adjusted Langevin algorithm for log-concave sampling K Wu, S Schmidler, Y Chen Journal of Machine Learning Research 23 (270), 1-63, 2022	66	2022
Stability and convergence trade-off of iterative optimization algorithms Y Chen, C Jin, B Yu arXiv preprint arXiv:1804.01619, 2018	53	2018
The DeepTune framework for modeling and characterizing neurons in visual cortex area V4 R Abbasi-Asl, Y Chen, A Bloniarz, M Oliver, BDB Willmore, JL Gallant, ... bioRxiv, 465534, 2018	46*	2018
Domain adaptation under structural causal models Y Chen, P Bühlmann Journal of Machine Learning Research 22 (261), 1-80, 2021	44	2021
Vaidya walk: A sampling algorithm based on the volumetric barrier Y Chen, R Dwivedi, MJ Wainwright, B Yu 2017 55th Annual Allerton Conference on Communication, Control, and …, 2017	22	2017
When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm? Y Chen, K Gatmiry arXiv preprint arXiv:2304.04724, 2023	18	2023
Hit-and-run mixing via localization schemes Y Chen, R Eldan arXiv preprint arXiv:2212.00297, 2022	4	2022
A Simple Proof of the Mixing of Metropolis-Adjusted Langevin Algorithm under Smoothness and Isoperimetry Y Chen, K Gatmiry arXiv preprint arXiv:2304.04095, 2023	3	2023
Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms K Wu, Y Chen, W Ha, B Yu arXiv preprint arXiv:2309.10301, 2023		2023
A Look at Robustness and Stability of 𝓁 1-versus 𝓁 0-Regularization Y Chen, A Taeb, P Bühlmann Statistical Science 35 (4), 614-622, 2020		2020
Log-concave sampling: Metropolis-Hastings algorithms are fast! R Dwivedi, Y Chen, MJ Wainwright, B Yu Conference on Learning Theory, 793-797, 2018		2018
Artificial neurons meet real neurons: pattern selectivity in V4 R Abbasi-Asl, Y Chen, A Bloniarz, JL Gallant, B Yu

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