3 papers
math.MG2026
Digesting the proof of the sharp thin-shell inequality
Yuansi Chen, Boaz Klartag
We present a proof that determines the optimal value of the universal constant in the thin-shell theorem for log-concave distributions in high dimensions. We prove that for any log…
stat.CO2026
When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm?
Yuansi Chen, Khashayar Gatmiry, Minhui Jiang
We analyze the mixing time of Metropolized Hamiltonian Monte Carlo (HMC) with the leapfrog integrator to sample from a distribution on whose log-density is smooth, h…
stat.ML2025
Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms
Keru Wu, Yuansi Chen, Wooseok Ha +1
Domain adaptation (DA) is a statistical learning problem that arises when the distribution of the source data used to train a model differs from that of the target data used to eva…