Yuansi Chen

According to our database, Yuansi Chen authored at least 20 papers between 2014 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Hit-and-Run Mixing via Localization Schemes.

Yuansi Chen, Ronen Eldan

Discret. Comput. Geom., April, 2026

2025

Talagrand's convolution conjecture up to loglog via perturbed reverse heat.

Yuansi Chen

CoRR, November, 2025

PolytopeWalk: Sparse MCMC Sampling over Polytopes.

Benny Sun, Yuansi Chen

J. Open Source Softw., August, 2025

When few labeled target data suffice: a theory of semi-supervised domain adaptation via fine-tuning from multiple adaptive starts.

Wooseok Ha, Yuansi Chen

CoRR, July, 2025

Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms.

Keru Wu, Yuansi Chen, Wooseok Ha, Bin Yu

J. Mach. Learn. Res., 2025

Regularized Dikin Walks for Sampling Truncated Logconcave Measures, Mixed Isoperimetry and Beyond Worst-Case Analysis.

Minhui Jiang, Yuansi Chen

Proceedings of the Thirty Eighth Annual Conference on Learning Theory, 2025

2023

When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm?

Yuansi Chen, Khashayar Gatmiry

CoRR, 2023

A Simple Proof of the Mixing of Metropolis-Adjusted Langevin Algorithm under Smoothness and Isoperimetry.

Yuansi Chen, Khashayar Gatmiry

CoRR, 2023

2022

Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling.

Keru Wu, Scott C. Schmidler, Yuansi Chen

J. Mach. Learn. Res., 2022

Localization Schemes: A Framework for Proving Mixing Bounds for Markov Chains.

Yuansi Chen, Ronen Eldan

CoRR, 2022

Localization Schemes: A Framework for Proving Mixing Bounds for Markov Chains (extended abstract).

Yuansi Chen, Ronen Eldan

Proceedings of the 63rd IEEE Annual Symposium on Foundations of Computer Science, 2022

2021

Domain adaptation under structural causal models.

Yuansi Chen, Peter Bühlmann

J. Mach. Learn. Res., 2021

2020

Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients.

Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu

J. Mach. Learn. Res., 2020

2018

Fast MCMC Sampling Algorithms on Polytopes.

Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu

J. Mach. Learn. Res., 2018

Sampling Can Be Faster Than Optimization.

Yi-An Ma, Yuansi Chen, Chi Jin, Nicolas Flammarion, Michael I. Jordan

CoRR, 2018

Stability and Convergence Trade-off of Iterative Optimization Algorithms.

Yuansi Chen, Chi Jin, Bin Yu

CoRR, 2018

Log-concave sampling: Metropolis-Hastings algorithms are fast!

Raaz Dwivedi, Yuansi Chen, Martin J. Wainwright, Bin Yu

Proceedings of the Conference On Learning Theory, 2018

2017

Vaidya walk: A sampling algorithm based on the volumetric barrier.

Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu

Proceedings of the 55th Annual Allerton Conference on Communication, 2017

2016

Self-calibrating neural networks for dimensionality reduction.

Yuansi Chen, Cengiz Pehlevan, Dmitri B. Chklovskii

Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2014

Fast and Robust Archetypal Analysis for Representation Learning.

Yuansi Chen, Julien Mairal, Zaïd Harchaoui

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014