134 citations · 304 across the 14 of their papers we have counts for
15 papers
Closed-Form Formulas for Designing Ultra-Low Phase-Noise Cross-Coupled Dynamically Body-Biased Only-NMOS LCVCOs
Naser Khatti Dizabadi, Peter LoPresti
This paper presents a system-level analytical framework for modeling and minimizing phase noise in body-biased cross-coupled LC-tank voltage-controlled oscillators (LC-VCOs). Build…
Large Scale Partial Correlation Screening with Uncertainty Quantification
Emily Neo, Peter Radchenko, Bala Rajaratnam
Identifying multivariate dependencies in high-dimensional data is an important problem in large-scale inference. This problem has motivated recent advances in mining (partial) corr…
Ask for More Than Bayes Optimal: A Theory of Indecisions for Selective Hypothesis Testing
Mohamed Ndaoud, Peter Radchenko, Bradley Rava
Selective classification is a powerful tool for automated decision-making in high-risk scenarios, allowing classifiers to act only when confident and abstain when uncertainty is hi…
Change-Point Detection in Time Series Using Mixed Integer Programming
Artem Prokhorov, Peter Radchenko, Alexander Semenov +1
We use cutting-edge mixed integer optimization (MIO) methods to develop a framework for detection and estimation of structural breaks in time series regression models. The framewor…
Predicting Census Survey Response Rates With Parsimonious Additive Models and Structured Interactions
Shibal Ibrahim, Peter Radchenko, Emanuel Ben-David +1
In this paper, we consider the problem of predicting survey response rates using a family of flexible and interpretable nonparametric models. The study is motivated by the US Censu…
Grouped Variable Selection with Discrete Optimization: Computational and Statistical Perspectives
Hussein Hazimeh, Rahul Mazumder, Peter Radchenko
We present a new algorithmic framework for grouped variable selection that is based on discrete mathematical optimization. While there exist several appealing approaches based on c…