activity
20072026
most citedReading policies for joins: An asymptotic analysis

1 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

math.OC2026

Robust Optimal Portfolio in a Mixture Setting with Partial Ambiguity

N. D. Shyamalkumar, Tianrun Wang

Managing insurance and financial risk when data is limited is a key task in the insurance industry. In this paper, we focus on cases where the risk distribution is modeled as a mix…

math.OC2026

On a Class of Optimal Reinsurance Problems

N. D. Shyamalkumar, Tianrun Wang

De Finetti's optimal reinsurance is a set of contracts, one for each risk in a portfolio, that caps the retained aggregate variance to a pre-specified level while minimizing total…

stat.CO2019

An Algorithm for Distributed Bayesian Inference in Generalized Linear Models

Nariankadu D. Shyamalkumar, Sanvesh Srivastava

Monte Carlo algorithms, such as Markov chain Monte Carlo (MCMC) and Hamiltonian Monte Carlo (HMC), are routinely used for Bayesian inference in generalized linear models; however,…

math.PR2019

On a Tail Bound for Root-Finding in Randomly Growing Trees

Sam Justice, N. D. Shyamalkumar

We re-examine a lower-tail upper bound for the random variable where …

math.ST2019★ 1 cited

On Tail Dependence Matrices -- The Realization Problem for Parametric Families

Nariankadu D. Shyamalkumar, Siyang Tao

Among bivariate tail dependence measures, the tail dependence coefficient has emerged as the popular choice. Akin to the correlation matrix, a multivariate dependence measure is co…

math.PR2007★ 1 cited

Reading policies for joins: An asymptotic analysis

Ralph P. Russo, Nariankadu D. Shyamalkumar

Suppose that observations are made from the distribution and from the distribution . Associate with each pair, from and $…