20 citations · 100 across the 13 of their papers we have counts for
4 papers · 1 filter
Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo
Krishnakumar Balasubramanian, Sinho Chewi, Murat A. Erdogdu +2
For the task of sampling from a density on , where is possibly non-convex but -gradient Lipschitz, we prove that averaged Langevin Monte Ca…
Heavy-tailed Sampling via Transformed Unadjusted Langevin Algorithm
Ye He, Krishnakumar Balasubramanian, Murat A. Erdogdu
We analyze the oracle complexity of sampling from polynomially decaying heavy-tailed target densities based on running the Unadjusted Langevin Algorithm on certain transformed vers…
On Empirical Risk Minimization with Dependent and Heavy-Tailed Data
Abhishek Roy, Krishnakumar Balasubramanian, Murat A. Erdogdu
In this work, we establish risk bounds for the Empirical Risk Minimization (ERM) with both dependent and heavy-tailed data-generating processes. We do so by extending the seminal w…
Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT
Andreas Anastasiou, Krishnakumar Balasubramanian, Murat A. Erdogdu
We provide non-asymptotic convergence rates of the Polyak-Ruppert averaged stochastic gradient descent (SGD) to a normal random vector for a class of twice-differentiable test func…