7 papers
BLOC: A Global Optimization Framework for Sparse Covariance Estimation with Non-Convex Penalties
Priyam Das, Trambak Banerjee, Prajamitra Bhuyan
We introduce BLOC (Black-box Optimization over Correlation matrices), a general framework for sparse covariance estimation with non-convex penalties. BLOC operates on the manifold…
Nonparametric Empirical Bayes Estimation on Heterogeneous Data
Trambak Banerjee, Luella J. Fu, Gareth M. James +2
The simultaneous estimation of many parameters based on data collected from corresponding studies is a key research problem that has received renewed attention in the high-dimensio…
Multiple Testing of Partial Conjunction Hypotheses for Assessing Replicability Across Dependent Studies
Monitirtha Dey, Trambak Banerjee, Prajamitra Bhuyan +1
Replicability is central to scientific progress, and the partial conjunction (PC) hypothesis testing framework provides an objective tool to quantify it across disciplines. Existin…
Harnessing The Collective Wisdom: Fusion Learning Using Decision Sequences From Diverse Sources
Trambak Banerjee, Bowen Gang, Jianliang He
We introduce an Integrative Ranking and Thresholding (IRT) framework for fusing evidence from multiple testing procedures. The key innovation is a method that transforms binary tes…
Empirical Bayes Estimation with Side Information: A Nonparametric Integrative Tweedie Approach
Jiajun Luo, Trambak Banerjee, Gourab Mukherjee +1
We investigate the problem of compound estimation of normal means while accounting for the presence of side information. Leveraging the empirical Bayes framework, we develop a nonp…
Large-Scale Multiple Testing of Composite Null Hypotheses Under Heteroskedasticity
Bowen Gang, Trambak Banerjee
Heteroskedasticity poses several methodological challenges in designing valid and powerful procedures for simultaneous testing of composite null hypotheses. In particular, the conv…