3 papers
stat.ME2024
On an Empirical Likelihood based Solution to the Approximate Bayesian Computation Problem
Sanjay Chaudhuri, Subhroshekhar Ghosh, Kim Cuc Pham
Approximate Bayesian Computation (ABC) methods are applicable to statistical models specified by generative processes with analytically intractable likelihoods. These methods try t…
math.CV2024
Hole event for random holomorphic sections on compact Riemann surfaces
Tien-Cuong Dinh, Subhroshekhar Ghosh, Hao Wu
Let be a compact Riemann surface and be a positive line bundle on it. We study the conditional zero expectation of all the holomorphic sections of w…
stat.ML2021
Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGD
Remi Bardenet, Subhro Ghosh, Meixia Lin
Stochastic gradient descent (SGD) is a cornerstone of machine learning. When the number N of data items is large, SGD relies on constructing an unbiased estimator of the gradient o…