Research

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Recent papers by topic

Domain adaptation/Transfer learning

• When few labeled target data suffice: a theory of semi-supervised domain adaptation via fine-tuning from multiple adaptive starts, [arXiv], Wooseok Ha, Yuansi Chen
• Prominent roles of conditionally invariant components in domain adaptation: Theory and algorithms, [JMLR][arXiv], Keru Wu, Yuansi Chen, Wooseok Ha, Bin Yu. JMLR 2024
• Domain adaptation under structural causal models, [JMLR][arXiv], Yuansi Chen, Peter Bühlmann. JMLR 2021

Markov chain Monte Carlo methods/convergence analysis

• Regularized Dikin Walks for Sampling Truncated Logconcave Measures, Mixed Isoperimetry and Beyond Worst-Case Analysis, [arXiv], Minhui Jiang, Yuansi Chen. COLT 2025
• When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm?, [arXiv], Yuansi Chen, Khashayar Gatmiry
• Hit-and-run mixing via localization schemes, [arXiv], Yuansi Chen, Ronen Eldan
• Localization Schemes: A Framework for Proving Mixing Bounds for Markov Chains, [DMJ][arXiv], Yuansi Chen, Ronen Eldan. Duke Math. J. 2025
• Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling, [JMLR][arXiv], Keru Wu, Scott Schmidler, Yuansi Chen. Journal of Machine Learning Research (JMLR) 2022

Papers with code

• Log-concave sampling: Metropolis-Hastings algorithms are fast, [JMLR][arXiv][Code on Github], Yuansi Chen, Raaz Dwivedi, Martin Wainwright, Bin Yu. Journal of Machine Learning Research (JMLR) 2019
• Fast MCMC Algorithms on Polytopes, [JMLR][arXiv][C++ Implementation on Github], Yuansi Chen, Raaz Dwivedi, Martin Wainwright, Bin Yu. Journal of Machine Learning Research (JMLR) 2018
• Fast and Robust Archetypal Analysis for Representation Learning, [CVPR][arXiv][Code&Demo], Yuansi Chen, Julien Mairal and Zaid Harchaoui. IEEE Computer Vision and Pattern Recognition (CVPR) 2014