activity
20182021
most citedLearning Sparsity and Block Diagonal Structure in Multi-View Mixture Models

1 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

stat.CO2021

yaglm: a Python package for fitting and tuning generalized linear models that supports structured, adaptive and non-convex penalties

Iain Carmichael, Thomas Keefe, Naomi Giertych +1

The yaglm package aims to make the broader ecosystem of modern generalized linear models accessible to data analysts and researchers. This ecosystem encompasses a range of loss fun…

math.ST20211 cited

The folded concave Laplacian spectral penalty learns block diagonal sparsity patterns with the strong oracle property

Iain Carmichael

Structured sparsity is an important part of the modern statistical toolkit. We say a set of model parameters has block diagonal sparsity up to permutations if its elements can be v…

stat.ME20201 cited

Learning Sparsity and Block Diagonal Structure in Multi-View Mixture Models

Iain Carmichael

Scientific studies increasingly collect multiple modalities of data to investigate a phenomenon from several perspectives. In integrative data analysis it is important to understan…

q-bio.QM2019

Joint and individual analysis of breast cancer histologic images and genomic covariates

Iain Carmichael, Benjamin C. Calhoun, Katherine A. Hoadley +8

A key challenge in modern data analysis is understanding connections between complex and differing modalities of data. For example, two of the main approaches to the study of breas…

stat.ME2018

An exposition of the false confidence theorem

Iain Carmichael, Jonathan P Williams

A recent paper presents the "false confidence theorem" (FCT) which has potentially broad implications for statistical inference using Bayesian posterior uncertainty. This theorem s…