Submodularity in machine learning and artificial intelligence
J Bilmes - arxiv preprint arxiv:2202.00132, 2022 - arxiv.org
In this manuscript, we offer a gentle review of submodularity and supermodularity and their
properties. We offer a plethora of submodular definitions; a full description of a number of …
properties. We offer a plethora of submodular definitions; a full description of a number of …
[HTML][HTML] Massively parallel characterization of transcriptional regulatory elements in three diverse human cell types
The human genome contains millions of candidate cis-regulatory elements (CREs) with cell-
type-specific activities that shape both health and myriad disease states. However, we lack a …
type-specific activities that shape both health and myriad disease states. However, we lack a …
Massively parallel characterization of transcriptional regulatory elements
The human genome contains millions of candidate cis-regulatory elements (cCREs) with cell-
type-specific activities that shape both health and many disease states. However, we lack a …
type-specific activities that shape both health and many disease states. However, we lack a …
PREDICTD parallel epigenomics data imputation with cloud-based tensor decomposition
Abstract The Encyclopedia of DNA Elements (ENCODE) and the Roadmap Epigenomics
Project seek to characterize the epigenome in diverse cell types using assays that identify …
Project seek to characterize the epigenome in diverse cell types using assays that identify …
Regularized submodular maximization at scale
In this paper, we propose scalable methods for maximizing a regularized submodular
function $ f\triangleq g-\ell $ expressed as the difference between a monotone submodular …
function $ f\triangleq g-\ell $ expressed as the difference between a monotone submodular …
Accelerated knowledge discovery from omics data by optimal experimental design
How to design experiments that accelerate knowledge discovery on complex biological
landscapes remains a tantalizing question. We present an optimal experimental design …
landscapes remains a tantalizing question. We present an optimal experimental design …
Enhancer-driven gene regulatory networks inference from single-cell RNA-seq and ATAC-seq data
Deciphering the intricate relationships between transcription factors (TFs), enhancers, and
genes through the inference of enhancer-driven gene regulatory networks (eGRNs) is …
genes through the inference of enhancer-driven gene regulatory networks (eGRNs) is …
Choosing non‐redundant representative subsets of protein sequence data sets using submodular optimization
Selecting a non‐redundant representative subset of sequences is a common step in many
bioinformatics workflows, such as the creation of non‐redundant training sets for sequence …
bioinformatics workflows, such as the creation of non‐redundant training sets for sequence …
Spadis: An algorithm for selecting predictive and diverse snps in gwas
Phenotypic heritability of complex traits and diseases is seldom explained by individual
genetic variants identified in genome-wide association studies (GWAS). Many methods have …
genetic variants identified in genome-wide association studies (GWAS). Many methods have …
Submodular sketches of single-cell RNA-seq measurements
Single-cell RNA-seq (scRNA-seq) datasets now routinely profile tens of thousands to
millions of cells. These data are invaluable for finding important subpopulations of cells and …
millions of cells. These data are invaluable for finding important subpopulations of cells and …