Genevera I. Allen

According to our database, Genevera I. Allen authored at least 48 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

SPA-STOCSY: an automated tool for identifying annotated and non-annotated metabolites in high-throughput NMR spectra.

Xu Han, Wanli Wang, Li-Hua Ma, Ismael Ai-Ramahi, Juan Botas, Kevin Mackenzie, Genevera I. Allen, Damian W. Young, Zhandong Liu, Mirjana Maletic-Savatic

Bioinform., October, 2023

Fair Feature Importance Scores for Interpreting Tree-Based Methods and Surrogates.

Camille Olivia Little, Debolina Halder Lina, Genevera I. Allen

CoRR, 2023

Data Augmentation via Subgroup Mixup for Improving Fairness.

Madeline Navarro, Camille Olivia Little, Genevera I. Allen, Santiago Segarra

CoRR, 2023

Interpretable Machine Learning for Discovery: Statistical Challenges \& Opportunities.

Genevera I. Allen, Luqin Gan, Lili Zheng

CoRR, 2023

2022

Fast and interpretable consensus clustering via minipatch learning.

Luqin Gan, Genevera I. Allen

PLoS Comput. Biol., October, 2022

Correlation Imputation for Single-Cell RNA-seq.

Luqin Gan, Giuseppe Vinci, Genevera I. Allen

J. Comput. Biol., 2022

Inference for Interpretable Machine Learning: Fast, Model-Agnostic Confidence Intervals for Feature Importance.

Luqin Gan, Lili Zheng, Genevera I. Allen

CoRR, 2022

To the Fairness Frontier and Beyond: Identifying, Quantifying, and Optimizing the Fairness-Accuracy Pareto Frontier.

Camille Olivia Little, Michael Weylandt, Genevera I. Allen

CoRR, 2022

Learning Gaussian Graphical Models with Differing Pairwise Sample Sizes.

Lili Zheng, Genevera I. Allen

Proceedings of the IEEE International Conference on Acoustics, 2022

Experiential Learning in Data Science Through a Novel Client-Facing Consulting Course.

Arko Barman, Su Chen, Andersen Chang, Genevera I. Allen

Proceedings of the IEEE Frontiers in Education Conference, 2022

2021

Integrative Generalized Convex Clustering Optimization and Feature Selection for Mixed Multi-View Data.

Minjie Wang, Genevera I. Allen

J. Mach. Learn. Res., 2021

Integrated Principal Components Analysis.

Tiffany M. Tang, Genevera I. Allen

J. Mach. Learn. Res., 2021

Network Clustering for Latent State and Changepoint Detection.

Madeline Navarro, Genevera I. Allen, Michael Weylandt

CoRR, 2021

Gaussian Graphical Model Selection for Huge Data via Minipatch Learning.

Tianyi Yao, Minjie Wang, Genevera I. Allen

CoRR, 2021

Thresholded Graphical Lasso Adjusts for Latent Variables: Application to Functional Neural Connectivity.

Minjie Wang, Genevera I. Allen

CoRR, 2021

Experiential Learning in Data Science: Developing an Interdisciplinary, Client-Sponsored Capstone Program.

Genevera I. Allen

Proceedings of the SIGCSE '21: The 52nd ACM Technical Symposium on Computer Science Education, 2021

Minipatch Learning as Implicit Ridge-Like Regularization.

Tianyi Yao, Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk, Genevera I. Allen

Proceedings of the IEEE International Conference on Big Data and Smart Computing, 2021

MP-Boost: Minipatch Boosting via Adaptive Feature and Observation Sampling.

Mohammad Taha Toghani, Genevera I. Allen

Proceedings of the IEEE International Conference on Big Data and Smart Computing, 2021

Detection of Junctional Ectopic Tachycardia by Central Venous Pressure.

Xin Tan, Yanwan Dai, Ahmed Imtiaz Humayun, Haoze Chen, Genevera I. Allen, Parag N. Jain

Proceedings of the Artificial Intelligence in Medicine, 2021

2020

Simultaneous Grouping and Denoising via Sparse Convex Wavelet Clustering.

Michael Weylandt, T. Mitchell Roddenberry, Genevera I. Allen

CoRR, 2020

Feature Selection for Huge Data via Minipatch Learning.

Tianyi Yao, Genevera I. Allen

CoRR, 2020

Interpretable Visualization and Higher-Order Dimension Reduction for ECoG Data.

Kelly Geyer, Frederick Campbell, Andersen Chang, John F. Magnotti, Michael S. Beauchamp, Genevera I. Allen

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Correlation Imputation in Single cell RNA-seq using Auxiliary Information and Ensemble Learning.

Luqin Gan, Giuseppe Vinci, Genevera I. Allen

Proceedings of the BCB '20: 11th ACM International Conference on Bioinformatics, 2020

2019

Tensor network factorizations: Relationships between brain structural connectomes and traits.

Zhengwu Zhang, Genevera I. Allen, Hongtu Zhu, David B. Dunson

NeuroImage, 2019

Dynamic Visualization and Fast Computation for Convex Clustering via Algorithmic Regularization.

Michael Weylandt, John Nagorski, Genevera I. Allen

CoRR, 2019

Clustered Gaussian Graphical Model Via Symmetric Convex Clustering.

Tianyi Yao, Genevera I. Allen

Proceedings of the IEEE Data Science Workshop, 2019

Graphical Models and Dynamic Latent Factors for Modeling Functional Brain Connectivity.

Andersen Chang, Tianyi Yao, Genevera I. Allen

Proceedings of the IEEE Data Science Workshop, 2019

Sparse and Functional Principal Components Analysis.

Genevera I. Allen, Michael Weylandt

Proceedings of the IEEE Data Science Workshop, 2019

2018

Detecting hidden batch factors through data-adaptive adjustment for biological effects.

Haidong Yi, Ayush T. Raman, Han Zhang, Genevera I. Allen, Zhandong Liu

Bioinform., 2018

2017

The International Conference on Intelligent Biology and Medicine (ICIBM) 2016: from big data to big analytical tools.

Zhandong Liu, W. Jim Zheng, Genevera I. Allen, Yin Liu, Jianhua Ruan, Zhongming Zhao

BMC Bioinform., 2017

2016

XMRF: an R package to fit Markov Networks to high-throughput genetics data.

Ying-Wooi Wan, Genevera I. Allen, Yulia Baker, Eunho Yang, Pradeep Ravikumar, Matthew Anderson, Zhandong Liu

BMC Syst. Biol., 2016

TCGA2STAT: simple TCGA data access for integrated statistical analysis in R.

Ying-Wooi Wan, Genevera I. Allen, Zhandong Liu

Bioinform., 2016

2015

Comments on "visualizing statistical models": Visualizing modern statistical methods for Big Data.

Genevera I. Allen, Frederick Campbell, Yue Hu

Stat. Anal. Data Min., 2015

Graphical models via univariate exponential family distributions.

Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu

J. Mach. Learn. Res., 2015

Population Inference for Node Level Differences in Multi-subject Functional Connectivity.

Manjari Narayan, Genevera I. Allen

Proceedings of the 2015 International Workshop on Pattern Recognition in NeuroImaging, 2015

2014

Mixed Graphical Models via Exponential Families.

Eunho Yang, Yulia Baker, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013

Regularized partial least squares with an application to NMR spectroscopy.

Genevera I. Allen, Christine B. Peterson, Marina Vannucci, Mirjana Maletic-Savatic

Stat. Anal. Data Min., 2013

Randomized Approach to Differential Inference in Multi-subject Functional Connectivity.

Manjari Narayan, Genevera I. Allen

Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

Local-Aggregate Modeling for Multi-subject Neuroimage Data via Distributed Optimization.

Yue Hu, Genevera I. Allen

Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

On Poisson Graphical Models.

Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Conditional Random Fields via Univariate Exponential Families.

Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Imaging genetics via sparse canonical correlation analysis.

Eric C. Chi, Genevera I. Allen, Hua Zhou, Omid Kohannim, Kenneth Lange, Paul M. Thompson

Proceedings of the 10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2013

Identifying cancer biomarkers through a network regularized Cox model.

Ying-Wooi Wan, John Nagorski, Genevera I. Allen, Zhaohui Li, Zhandong Liu

Proceedings of the 2013 IEEE International Workshop on Genomic Signal Processing and Statistics, 2013

Multi-way functional principal components analysis.

Genevera I. Allen

Proceedings of the 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2013

2012

Sparse Higher-Order Principal Components Analysis.

Genevera I. Allen

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Graphical Models via Generalized Linear Models.

Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

A Log-Linear Graphical Model for inferring genetic networks from high-throughput sequencing data.

Genevera I. Allen, Zhandong Liu

Proceedings of the 2012 IEEE International Conference on Bioinformatics and Biomedicine, 2012

2011

Sparse non-negative generalized PCA with applications to metabolomics.

Genevera I. Allen, Mirjana Maletic-Savatic

Bioinform., 2011