Genevera I. Allen

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 40

Top Topics

Principal Components Analysis

Functional Connectivity

Experiential Learning

Top Venues

Publications

Camille Olivia Little, Genevera I. Allen
Fair MP-BOOST: Fair and Interpretable Minipatch Boosting. CoRR (2024)
Dingding Ye, Charan Santhirasegaran, Ryan Pai, Genevera I. Allen, Joseph Young
Addressing Confounds in Functional Connectivity Analyses of Calcium Imaging. ICASSP (2024)
Madeline Navarro, Camille Olivia Little, Genevera I. Allen, Santiago Segarra
Data Augmentation via Subgroup Mixup for Improving Fairness. ICASSP (2024)
Camille Olivia Little, Debolina Halder Lina, Genevera I. Allen
Fair Feature Importance Scores for Interpreting Decision Trees. Trans. Mach. Learn. Res. 2024 (2024)
Madeline Navarro, Camille Olivia Little, Genevera I. Allen, Santiago Segarra
Data Augmentation via Subgroup Mixup for Improving Fairness. CoRR (2023)
Camille Olivia Little, Debolina Halder Lina, Genevera I. Allen
Fair Feature Importance Scores for Interpreting Tree-Based Methods and Surrogates. CoRR (2023)
Genevera I. Allen, Luqin Gan, Lili Zheng
Interpretable Machine Learning for Discovery: Statistical Challenges \& Opportunities. CoRR (2023)
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
SPA-STOCSY: an automated tool for identifying annotated and non-annotated metabolites in high-throughput NMR spectra. Bioinform. 39 (10) (2023)
Luqin Gan, Giuseppe Vinci, Genevera I. Allen
Correlation Imputation for Single-Cell RNA-seq. J. Comput. Biol. 29 (5) (2022)
Arko Barman, Su Chen, Andersen Chang, Genevera I. Allen
Experiential Learning in Data Science Through a Novel Client-Facing Consulting Course. FIE (2022)
Luqin Gan, Lili Zheng, Genevera I. Allen
Inference for Interpretable Machine Learning: Fast, Model-Agnostic Confidence Intervals for Feature Importance. CoRR (2022)
Luqin Gan, Genevera I. Allen
Fast and interpretable consensus clustering via minipatch learning. PLoS Comput. Biol. 18 (10) (2022)
Camille Olivia Little, Michael Weylandt, Genevera I. Allen
To the Fairness Frontier and Beyond: Identifying, Quantifying, and Optimizing the Fairness-Accuracy Pareto Frontier. CoRR (2022)
Lili Zheng, Genevera I. Allen
Learning Gaussian Graphical Models with Differing Pairwise Sample Sizes. ICASSP (2022)
Luqin Gan, Genevera I. Allen
Fast and Interpretable Consensus Clustering via Minipatch Learning. CoRR (2021)
Tiffany M. Tang, Genevera I. Allen
Integrated Principal Components Analysis. J. Mach. Learn. Res. 22 (2021)
Tianyi Yao, Minjie Wang, Genevera I. Allen
Gaussian Graphical Model Selection for Huge Data via Minipatch Learning. CoRR (2021)
Tianyi Yao, Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk, Genevera I. Allen
Minipatch Learning as Implicit Ridge-Like Regularization. BigComp (2021)
Genevera I. Allen
Experiential Learning in Data Science: Developing an Interdisciplinary, Client-Sponsored Capstone Program. SIGCSE (2021)
Xin Tan, Yanwan Dai, Ahmed Imtiaz Humayun, Haoze Chen, Genevera I. Allen, Parag N. Jain
Detection of Junctional Ectopic Tachycardia by Central Venous Pressure. AIME (2021)
Minjie Wang, Genevera I. Allen
Thresholded Graphical Lasso Adjusts for Latent Variables: Application to Functional Neural Connectivity. CoRR (2021)
Madeline Navarro, Genevera I. Allen, Michael Weylandt
Network Clustering for Latent State and Changepoint Detection. CoRR (2021)
Minjie Wang, Genevera I. Allen
Integrative Generalized Convex Clustering Optimization and Feature Selection for Mixed Multi-View Data. J. Mach. Learn. Res. 22 (2021)
Mohammad Taha Toghani, Genevera I. Allen
MP-Boost: Minipatch Boosting via Adaptive Feature and Observation Sampling. BigComp (2021)
Kelly Geyer, Frederick Campbell, Andersen Chang, John F. Magnotti, Michael Beauchamp, Genevera I. Allen
Interpretable Visualization and Higher-Order Dimension Reduction for ECoG Data. IEEE BigData (2020)
Tianyi Yao, Genevera I. Allen
Feature Selection for Huge Data via Minipatch Learning. CoRR (2020)
Mohammad Taha Toghani, Genevera I. Allen
MP-Boost: Minipatch Boosting via Adaptive Feature and Observation Sampling. CoRR (2020)
Luqin Gan, Giuseppe Vinci, Genevera I. Allen
Correlation Imputation in Single cell RNA-seq using Auxiliary Information and Ensemble Learning. BCB (2020)
Kelly Geyer, Frederick Campbell, Andersen Chang, John F. Magnotti, Michael Beauchamp, Genevera I. Allen
Interpretable Visualization and Higher-Order Dimension Reduction for ECoG Data. CoRR (2020)
Michael Weylandt, T. Mitchell Roddenberry, Genevera I. Allen
Simultaneous Grouping and Denoising via Sparse Convex Wavelet Clustering. CoRR (2020)
Zhengwu Zhang, Genevera I. Allen, Hongtu Zhu, David B. Dunson
Tensor network factorizations: Relationships between brain structural connectomes and traits. NeuroImage 197 (2019)
Michael Weylandt, John Nagorski, Genevera I. Allen
Dynamic Visualization and Fast Computation for Convex Clustering via Algorithmic Regularization. CoRR (2019)
Genevera I. Allen, Michael Weylandt
Sparse and Functional Principal Components Analysis. DSW (2019)
Andersen Chang, Tianyi Yao, Genevera I. Allen
Graphical Models and Dynamic Latent Factors for Modeling Functional Brain Connectivity. DSW (2019)
Tianyi Yao, Genevera I. Allen
Clustered Gaussian Graphical Model via Symmetric Convex Clustering. CoRR (2019)
Tianyi Yao, Genevera I. Allen
Clustered Gaussian Graphical Model Via Symmetric Convex Clustering. DSW (2019)
Haidong Yi, Ayush T. Raman, Han Zhang, Genevera I. Allen, Zhandong Liu
Detecting hidden batch factors through data-adaptive adjustment for biological effects. Bioinform. 34 (7) (2018)
Zhandong Liu, W. Jim Zheng, Genevera I. Allen, Yin Liu, Jianhua Ruan, Zhongming Zhao
The International Conference on Intelligent Biology and Medicine (ICIBM) 2016: from big data to big analytical tools. BMC Bioinform. 18 (S-11) (2017)
Ying-Wooi Wan, Genevera I. Allen, Yulia Baker, Eunho Yang, Pradeep Ravikumar, Matthew Anderson, Zhandong Liu
XMRF: an R package to fit Markov Networks to high-throughput genetics data. BMC Syst. Biol. 10 (S-3) (2016)
Ying-Wooi Wan, Genevera I. Allen, Zhandong Liu
TCGA2STAT: simple TCGA data access for integrated statistical analysis in R. Bioinform. 32 (6) (2016)
Genevera I. Allen, Frederick Campbell, Yue Hu
Comments on "visualizing statistical models": Visualizing modern statistical methods for Big Data. Stat. Anal. Data Min. 8 (4) (2015)
Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu
Graphical models via univariate exponential family distributions. J. Mach. Learn. Res. 16 (2015)
Manjari Narayan, Genevera I. Allen
Population Inference for Node Level Differences in Multi-subject Functional Connectivity. PRNI (2015)
Eunho Yang, Yulia Baker, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu
Mixed Graphical Models via Exponential Families. AISTATS (2014)
Yue Hu, Genevera I. Allen
Local-Aggregate Modeling for Multi-subject Neuroimage Data via Distributed Optimization. PRNI (2013)
Manjari Narayan, Genevera I. Allen
Randomized Approach to Differential Inference in Multi-subject Functional Connectivity. PRNI (2013)
Genevera I. Allen, Christine B. Peterson, Marina Vannucci, Mirjana Maletic-Savatic
Regularized partial least squares with an application to NMR spectroscopy. Stat. Anal. Data Min. 6 (4) (2013)
Eric C. Chi, Genevera I. Allen, Hua Zhou, Omid Kohannim, Kenneth Lange, Paul M. Thompson
Imaging genetics via sparse canonical correlation analysis. ISBI (2013)
Ying-Wooi Wan, John Nagorski, Genevera I. Allen, Zhaohui Li, Zhandong Liu
Identifying cancer biomarkers through a network regularized Cox model. GENSiPS (2013)
Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu
Conditional Random Fields via Univariate Exponential Families. NIPS (2013)
Genevera I. Allen
Multi-way functional principal components analysis. CAMSAP (2013)
Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu
On Poisson Graphical Models. NIPS (2013)
Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu
Graphical Models via Generalized Linear Models. NIPS (2012)
Genevera I. Allen, Zhandong Liu
A Log-Linear Graphical Model for inferring genetic networks from high-throughput sequencing data. BIBM (2012)
Genevera I. Allen, Mirjana Maletic-Savatic
Sparse non-negative generalized PCA with applications to metabolomics. Bioinform. 27 (21) (2011)