Genevera I. Allen

64 papers A 3B 1C 2Misc 4Journal 37Unranked 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Fair Feature Importance Scores via Feature Occlusion and Permutation. CoRR Camille Olivia Little, Madeline Navarro, Santiago Segarra, Genevera I. Allen
2025	J	`jnl`	Are machine learning interpretations reliable? A stability study on global interpretations. CoRR Luqin Gan, Tarek M. Zikry, Genevera I. Allen
2025	Misc	`conf`	Fair MP-BOOST: Fair and Interpretable Minipatch Boosting. ICASSP Camille Olivia Little, Genevera I. Allen
2025	J	`jnl`	Top- CoRR Yuxi Chen, Tiffany Tang, Genevera I. Allen
2025	J	`jnl`	Top-$k$ Feature Importance Ranking. Trans. Mach. Learn. Res. Eric Chen, Tiffany Tang, Genevera I. Allen
2025	J	`jnl`	Unsupervised Machine Learning for Scientific Discovery: Workflow and Best Practices. CoRR Andersen Chang, Tiffany M. Tang, Tarek M. Zikry, Genevera I. Allen
2025	J	`jnl`	iLOCO: Distribution-Free Inference for Feature Interactions. CoRR Camille Olivia Little, Lili Zheng, Genevera I. Allen
2024	Misc	`conf`	Addressing Confounds in Functional Connectivity Analyses of Calcium Imaging. ICASSP Dingding Ye, Charan Santhirasegaran, Ryan Pai, Genevera I. Allen, Joseph Young
2024	Misc	`conf`	Data Augmentation via Subgroup Mixup for Improving Fairness. ICASSP Madeline Navarro, Camille Olivia Little, Genevera I. Allen, Santiago Segarra
2024	C	`conf`	Evaluating Individual Contributions in Teams for Project-Based Learning in Data Science. FIE Arko Barman, Su Chen, Genevera I. Allen
2024	J	`jnl`	Fair Feature Importance Scores for Interpreting Decision Trees. Trans. Mach. Learn. Res. Camille Olivia Little, Debolina Halder Lina, Genevera I. Allen
2024	J	`jnl`	Fair MP-BOOST: Fair and Interpretable Minipatch Boosting. CoRR Camille Olivia Little, Genevera I. Allen
2023	J	`jnl`	Data Augmentation via Subgroup Mixup for Improving Fairness. CoRR Madeline Navarro, Camille Olivia Little, Genevera I. Allen, Santiago Segarra
2023	J	`jnl`	Fair Feature Importance Scores for Interpreting Tree-Based Methods and Surrogates. CoRR Camille Olivia Little, Debolina Halder Lina, Genevera I. Allen
2023	J	`jnl`	Interpretable Machine Learning for Discovery: Statistical Challenges \& Opportunities. CoRR Genevera I. Allen, Luqin Gan, Lili Zheng
2023	J	`jnl`	SPA-STOCSY: an automated tool for identifying annotated and non-annotated metabolites in high-throughput NMR spectra. Bioinform. 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
2022	J	`jnl`	Correlation Imputation for Single-Cell RNA-seq. J. Comput. Biol. Luqin Gan, Giuseppe Vinci, Genevera I. Allen
2022	C	`conf`	Experiential Learning in Data Science Through a Novel Client-Facing Consulting Course. FIE Arko Barman, Su Chen, Andersen Chang, Genevera I. Allen
2022	J	`jnl`	Fast and interpretable consensus clustering via minipatch learning. PLoS Comput. Biol. Luqin Gan, Genevera I. Allen
2022	J	`jnl`	Inference for Interpretable Machine Learning: Fast, Model-Agnostic Confidence Intervals for Feature Importance. CoRR Luqin Gan, Lili Zheng, Genevera I. Allen
2022	Misc	`conf`	Learning Gaussian Graphical Models with Differing Pairwise Sample Sizes. ICASSP Lili Zheng, Genevera I. Allen
2022	J	`jnl`	To the Fairness Frontier and Beyond: Identifying, Quantifying, and Optimizing the Fairness-Accuracy Pareto Frontier. CoRR Camille Olivia Little, Michael Weylandt, Genevera I. Allen
2021	B	`conf`	Detection of Junctional Ectopic Tachycardia by Central Venous Pressure. AIME Xin Tan, Yanwan Dai, Ahmed Imtiaz Humayun, Haoze Chen, Genevera I. Allen, Parag N. Jain
2021	A	`conf`	Experiential Learning in Data Science: Developing an Interdisciplinary, Client-Sponsored Capstone Program. SIGCSE Genevera I. Allen
2021	J	`jnl`	Fast and Interpretable Consensus Clustering via Minipatch Learning. CoRR Luqin Gan, Genevera I. Allen
2021	J	`jnl`	Gaussian Graphical Model Selection for Huge Data via Minipatch Learning. CoRR Tianyi Yao, Minjie Wang, Genevera I. Allen
2021	J	`jnl`	Integrated Principal Components Analysis. J. Mach. Learn. Res. Tiffany M. Tang, Genevera I. Allen
2021	J	`jnl`	Integrative Generalized Convex Clustering Optimization and Feature Selection for Mixed Multi-View Data. J. Mach. Learn. Res. Minjie Wang, Genevera I. Allen
2021	—	`conf`	MP-Boost: Minipatch Boosting via Adaptive Feature and Observation Sampling. BigComp Mohammad Taha Toghani, Genevera I. Allen
2021	—	`conf`	Minipatch Learning as Implicit Ridge-Like Regularization. BigComp Tianyi Yao, Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk, Genevera I. Allen
2021	J	`jnl`	Network Clustering for Latent State and Changepoint Detection. CoRR Madeline Navarro, Genevera I. Allen, Michael Weylandt
2021	J	`jnl`	Thresholded Graphical Lasso Adjusts for Latent Variables: Application to Functional Neural Connectivity. CoRR Minjie Wang, Genevera I. Allen
2020	—	`conf`	Correlation Imputation in Single cell RNA-seq using Auxiliary Information and Ensemble Learning. BCB Luqin Gan, Giuseppe Vinci, Genevera I. Allen
2020	J	`jnl`	Feature Selection for Huge Data via Minipatch Learning. CoRR Tianyi Yao, Genevera I. Allen
2020	—	`conf`	Interpretable Visualization and Higher-Order Dimension Reduction for ECoG Data. IEEE BigData Kelly Geyer, Frederick Campbell, Andersen Chang, John F. Magnotti, Michael S. Beauchamp, Genevera I. Allen
2020	J	`jnl`	Interpretable Visualization and Higher-Order Dimension Reduction for ECoG Data. CoRR Kelly Geyer, Frederick Campbell, Andersen Chang, John F. Magnotti, Michael S. Beauchamp, Genevera I. Allen
2020	J	`jnl`	MP-Boost: Minipatch Boosting via Adaptive Feature and Observation Sampling. CoRR Mohammad Taha Toghani, Genevera I. Allen
2020	J	`jnl`	Simultaneous Grouping and Denoising via Sparse Convex Wavelet Clustering. CoRR Michael Weylandt, T. Mitchell Roddenberry, Genevera I. Allen
2019	—	`conf`	Clustered Gaussian Graphical Model Via Symmetric Convex Clustering. DSW Tianyi Yao, Genevera I. Allen
2019	J	`jnl`	Clustered Gaussian Graphical Model via Symmetric Convex Clustering. CoRR Tianyi Yao, Genevera I. Allen
2019	J	`jnl`	Dynamic Visualization and Fast Computation for Convex Clustering via Algorithmic Regularization. CoRR Michael Weylandt, John Nagorski, Genevera I. Allen
2019	—	`conf`	Graphical Models and Dynamic Latent Factors for Modeling Functional Brain Connectivity. DSW Andersen Chang, Tianyi Yao, Genevera I. Allen
2019	—	`conf`	Sparse and Functional Principal Components Analysis. DSW Genevera I. Allen, Michael Weylandt
2019	J	`jnl`	Tensor network factorizations: Relationships between brain structural connectomes and traits. NeuroImage Zhengwu Zhang, Genevera I. Allen, Hongtu Zhu, David B. Dunson
2018	J	`jnl`	Detecting hidden batch factors through data-adaptive adjustment for biological effects. Bioinform. Haidong Yi, Ayush T. Raman, Han Zhang, Genevera I. Allen, Zhandong Liu
2017	J	`jnl`	The International Conference on Intelligent Biology and Medicine (ICIBM) 2016: from big data to big analytical tools. BMC Bioinform. Zhandong Liu, W. Jim Zheng, Genevera I. Allen, Yin Liu, Jianhua Ruan, Zhongming Zhao
2016	J	`jnl`	TCGA2STAT: simple TCGA data access for integrated statistical analysis in R. Bioinform. Ying-Wooi Wan, Genevera I. Allen, Zhandong Liu
2016	J	`jnl`	XMRF: an R package to fit Markov Networks to high-throughput genetics data. BMC Syst. Biol. Ying-Wooi Wan, Genevera I. Allen, Yulia Baker, Eunho Yang, Pradeep Ravikumar, Matthew Anderson, Zhandong Liu
2015	J	`jnl`	Comments on "visualizing statistical models": Visualizing modern statistical methods for Big Data. Stat. Anal. Data Min. Genevera I. Allen, Frederick Campbell, Yue Hu
2015	J	`jnl`	Graphical models via univariate exponential family distributions. J. Mach. Learn. Res. Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu
2015	—	`conf`	Population Inference for Node Level Differences in Multi-subject Functional Connectivity. PRNI Manjari Narayan, Genevera I. Allen
2014	A	`conf`	Mixed Graphical Models via Exponential Families. AISTATS Eunho Yang, Yulia Baker, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu
2013	—	`conf`	Conditional Random Fields via Univariate Exponential Families. NIPS Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu
2013	—	`conf`	Identifying cancer biomarkers through a network regularized Cox model. GENSiPS Ying-Wooi Wan, John Nagorski, Genevera I. Allen, Zhaohui Li, Zhandong Liu
2013	—	`conf`	Imaging genetics via sparse canonical correlation analysis. ISBI Eric C. Chi, Genevera I. Allen, Hua Zhou, Omid Kohannim, Kenneth Lange, Paul M. Thompson
2013	—	`conf`	Local-Aggregate Modeling for Multi-subject Neuroimage Data via Distributed Optimization. PRNI Yue Hu, Genevera I. Allen
2013	—	`conf`	Multi-way functional principal components analysis. CAMSAP Genevera I. Allen
2013	—	`conf`	On Poisson Graphical Models. NIPS Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu
2013	—	`conf`	Randomized Approach to Differential Inference in Multi-subject Functional Connectivity. PRNI Manjari Narayan, Genevera I. Allen
2013	J	`jnl`	Regularized partial least squares with an application to NMR spectroscopy. Stat. Anal. Data Min. Genevera I. Allen, Christine B. Peterson, Marina Vannucci, Mirjana Maletic-Savatic
2012	—	`conf`	A Log-Linear Graphical Model for inferring genetic networks from high-throughput sequencing data. BIBM Genevera I. Allen, Zhandong Liu
2012	—	`conf`	Graphical Models via Generalized Linear Models. NIPS Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu
2012	A	`conf`	Sparse Higher-Order Principal Components Analysis. AISTATS Genevera I. Allen
2011	J	`jnl`	Sparse non-negative generalized PCA with applications to metabolomics. Bioinform. Genevera I. Allen, Mirjana Maletic-Savatic