Genevera I. Allen

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All published works

Action	Title	Year	Authors
+ PDF Chat	Cluster Quilting: Spectral Clustering for Patchwork Learning	2024	Lili Zheng Andersen Chang Genevera I. Allen
+ PDF Chat	Fair MP-BOOST: Fair and Interpretable Minipatch Boosting	2024	Camille Olivia Little Genevera I. Allen
+	Data Augmentation via Subgroup Mixup for Improving Fairness	2024	Madeline Navarro Camille Little Genevera I. Allen Santiago Segarra
+ PDF Chat	Graphical Model Inference with Erosely Measured Data	2023	Lili Zheng Genevera I. Allen
+ PDF Chat	Subbotin graphical models for extreme value dependencies with applications to functional neuronal connectivity	2023	Andersen Chang Genevera I. Allen
+ PDF Chat	Supervised Convex Clustering	2023	Minjie Wang Tianyi Yao Genevera I. Allen
+	Nonparanormal Graph Quilting with Applications to Calcium Imaging	2023	Andersen Chang Lili Zheng Gautam Dasarthy Genevera I. Allen
+	Interpretable Machine Learning for Discovery: Statistical Challenges \& Opportunities	2023	Genevera I. Allen Luqin Gan Lili Zheng
+	Data Augmentation via Subgroup Mixup for Improving Fairness	2023	Madeline Navarro Camille Little Genevera I. Allen Santiago Segarra
+ PDF Chat	Nonparanormal graph quilting with applications to calcium imaging	2023	Andersen Chang Lili Zheng Gautam Dasarathy Genevera I. Allen
+	Joint Semi-Symmetric Tensor PCA for Integrating Multi-modal Populations of Networks	2023	Jiaming Liu Lili Zheng Zhengwu Zhang Genevera I. Allen
+	Fair Feature Importance Scores for Interpreting Tree-Based Methods and Surrogates	2023	Camille Olivia Little Debolina Halder Lina Genevera I. Allen
+	Thresholded graphical lasso adjusts for latent variables	2022	Minjie Wang Genevera I. Allen
+ PDF Chat	Fast and interpretable consensus clustering via minipatch learning	2022	Luqin Gan Genevera I. Allen
+	A Low-Rank Tensor Completion Approach for Imputing Functional Neuronal Data from Multiple Recordings	2022	Lili Zheng Zachary T. Rewolinski Genevera I. Allen
+	Correlation Imputation for Single-Cell RNA-seq	2022	Luqin Gan Giuseppe Vinci Genevera I. Allen
+	Model-Agnostic Confidence Intervals for Feature Importance: A Fast and Powerful Approach Using Minipatch Ensembles	2022	Luqin Gan Lili Zheng Genevera I. Allen
+	To the Fairness Frontier and Beyond: Identifying, Quantifying, and Optimizing the Fairness-Accuracy Pareto Frontier	2022	Camille Olivia Little Michael Weylandt Genevera I. Allen
+	Low-Rank Covariance Completion for Graph Quilting with Applications to Functional Connectivity	2022	Andersen Chang Lili Zheng Genevera I. Allen
+	Graphical Model Inference with Erosely Measured Data	2022	Lili Zheng Genevera I. Allen
+	Network Clustering for Latent State and Changepoint Detection.	2021	Madeline Navarro Genevera I. Allen Michael Weylandt
+	Extreme Graphical Models with Applications to Functional Neuronal Connectivity	2021	Andersen Chang Genevera I. Allen
+ PDF Chat	Simultaneous Grouping and Denoising via Sparse Convex Wavelet Clustering	2021	Michael Weylandt T. Mitchell Roddenberry Genevera I. Allen
+ PDF Chat	MP-Boost: Minipatch Boosting via Adaptive Feature and Observation Sampling	2021	Mohammad Taha Toghani Genevera I. Allen
+	Thresholded Graphical Lasso Adjusts for Latent Variables: Application to Functional Neural Connectivity	2021	Minjie Wang Genevera I. Allen
+	Integrated Principal Components Analysis	2021	Tiffany M. Tang Genevera I. Allen
+	Fast and Accurate Graph Learning for Huge Data via Minipatch Ensembles	2021	Tianyi Yao Minjie Wang Genevera I. Allen
+ PDF Chat	Sparse regression for extreme values	2021	Andersen Chang Minjie Wang Genevera I. Allen
+	Network Clustering for Latent State and Changepoint Detection	2021	Madeline Navarro Genevera I. Allen Michael Weylandt
+	Subbotin Graphical Models for Extreme Value Dependencies with Applications to Functional Neuronal Connectivity	2021	Andersen Chang Genevera I. Allen
+ PDF Chat	Interpretable Visualization and Higher-Order Dimension Reduction for ECoG Data	2020	Kelly Geyer Frederick Campbell Andersen Chang John F. Magnotti Michael S. Beauchamp Genevera I. Allen
+	Simultaneous Grouping and Denoising via Sparse Convex Wavelet Clustering	2020	Michael Weylandt T. Mitchell Roddenberry Genevera I. Allen
+ PDF Chat	Feature selection for data integration with mixed multiview data	2020	Yulia Baker Tiffany M. Tang Genevera I. Allen
+	Interpretable Visualization and Higher-Order Dimension Reduction for ECoG Data	2020	Kelly Geyer Frederick Campbell Andersen Chang John F. Magnotti Michael S. Beauchamp Genevera I. Allen
+	Supervised Convex Clustering	2020	Minjie Wang Tianyi Yao Genevera I. Allen
+	Sparse Regression for Extreme Values	2020	Andersen Chang Minjie Wang Genevera I. Allen
+	Feature Selection for Huge Data via Minipatch Learning	2020	Tianyi Yao Genevera I. Allen
+	Interpretable Visualization and Higher-Order Dimension Reduction for ECoG Data	2020	Kelly Geyer Frederick Campbell Andersen Chang John F. Magnotti Michael S. Beauchamp Genevera I. Allen
+	Graph quilting: graphical model selection from partially observed covariances.	2019	Giuseppe Vinci Gautam Dasarathy Genevera I. Allen
+ PDF Chat	Integrative Generalized Convex Clustering Optimization and Feature Selection for Mixed Multi-View Data	2019	Minjie Wang Genevera I. Allen
+ PDF Chat	Dynamic Visualization and Fast Computation for Convex Clustering via Algorithmic Regularization	2019	Michael Weylandt John Nagorski Genevera I. Allen
+ PDF Chat	Sparse and Functional Principal Components Analysis	2019	Genevera I. Allen Michael Weylandt
+ PDF Chat	Clustered Gaussian Graphical Model Via Symmetric Convex Clustering	2019	Tianyi Yao Genevera I. Allen
+ PDF Chat	Tensor network factorizations: Relationships between brain structural connectomes and traits	2019	Zhengwu Zhang Genevera I. Allen Hongtu Zhu David B. Dunson
+	Feature Selection for Data Integration with Mixed Multi-view Data.	2019	Yulia Baker Tiffany M. Tang Genevera I. Allen
+	Dynamic Visualization and Fast Computation for Convex Clustering and Bi-Clustering	2019	Michael Weylandt John Nagorski Genevera I. Allen
+	Clustered Gaussian Graphical Model via Symmetric Convex Clustering	2019	Tianyi Yao Genevera I. Allen
+	Integrative Generalized Convex Clustering Optimization and Feature Selection for Mixed Multi-View Data	2019	Minjie Wang Genevera I. Allen
+	Feature Selection for Data Integration with Mixed Multi-view Data	2019	Yulia Baker Tiffany M. Tang Genevera I. Allen
+	Graph quilting: graphical model selection from partially observed covariances	2019	Giuseppe Vinci Gautam Dasarathy Genevera I. Allen
+	Integrated Principal Components Analysis	2018	Tiffany M. Tang Genevera I. Allen
+ PDF Chat	Genomic region detection via Spatial Convex Clustering	2018	John Nagorski Genevera I. Allen
+	Tensor network factorizations: Relationships between brain structural connectomes and traits	2018	Zhengwu Zhang Genevera I. Allen Hongtu Zhu David B. Dunson
+	Integrated Principal Components Analysis	2018	Tiffany M. Tang Genevera I. Allen
+	Statistical data integration: Challenges and opportunities	2017	Genevera I. Allen
+ PDF Chat	A review of multivariate distributions for count data derived from the Poisson distribution	2017	David I. Inouye Eunho Yang Genevera I. Allen Pradeep Ravikumar
+ PDF Chat	Convex biclustering: Convex Biclustering	2017	C. Eric Genevera I. Allen Richard G. Baraniuk
+	Within group variable selection through the Exclusive Lasso	2017	Frederick Campbell Genevera I. Allen
+	Genomic Region Detection via Spatial Convex Clustering	2016	John Nagorski Genevera I. Allen
+	A Review of Multivariate Distributions for Count Data Derived from the Poisson Distribution	2016	David I. Inouye Eunho Yang Genevera I. Allen Pradeep Ravikumar
+ PDF Chat	Convex Biclustering	2016	C. Eric Genevera I. Allen Richard G. Baraniuk
+	A Review of Multivariate Distributions for Count Data Derived from the Poisson Distribution	2016	David I. Inouye Eunho Yang Genevera I. Allen Pradeep Ravikumar
+	Genomic Region Detection via Spatial Convex Clustering	2016	John Nagorski Genevera I. Allen
+ PDF Chat	ADMM Algorithmic Regularization Paths for Sparse Statistical Machine Learning	2016	Yue Hu C. Eric Genevera I. Allen
+ PDF Chat	Local-aggregate Modeling for Big Data via Distributed Optimization: Applications to Neuroimaging	2015	Yue Hu Genevera I. Allen
+	Comments on “visualizing statistical models”: Visualizing modern statistical methods for Big Data	2015	Genevera I. Allen Frederick Campbell Yue Hu
+	Within Group Variable Selection through the Exclusive Lasso	2015	Frederick Campbell Genevera I. Allen
+	Two Sample Inference for Populations of Graphical Models with Applications to Functional Connectivity	2015	Manjari Narayan Genevera I. Allen Tomson Steffie
+	ADMM Algorithmic Regularization Paths for Sparse Statistical Machine Learning	2015	Yue Hu C. Eric Genevera I. Allen
+	Within Group Variable Selection through the Exclusive Lasso	2015	Frederick Campbell Genevera I. Allen
+	Two Sample Inference for Populations of Graphical Models with Applications to Functional Connectivity	2015	Manjari Narayan Genevera I. Allen Steffie Tomson
+	Singular Value Decomposition and High Dimensional Data	2014	Genevera I. Allen Patrick O. Perry
+ PDF Chat	On the Reproducibility of TCGA Ovarian Cancer MicroRNA Profiles	2014	Ying‐Wooi Wan Claire M. Mach Genevera I. Allen Matthew L. Anderson Zhandong Liu
+	A General Framework for Mixed Graphical Models	2014	Eunho Yang Pradeep Ravikumar Genevera I. Allen Yulia Baker Ying‐Wooi Wan Zhandong Liu
+	Local-Aggregate Modeling for Big-Data via Distributed Optimization: Applications to Neuroimaging	2014	Yue Hu Genevera I. Allen
+	On Poisson Graphical Models	2013	Eunho Yang Pradeep Ravikumar Genevera I. Allen Zhandong Liu
+	Conditional Random Fields via Univariate Exponential Families	2013	Eunho Yang Pradeep Ravikumar Genevera I. Allen Zhandong Liu
+	Multi-way functional principal components analysis	2013	Genevera I. Allen
+ PDF Chat	A Generalized Least-Square Matrix Decomposition	2013	Genevera I. Allen Logan Grosenick Jonathan Taylor
+	On Graphical Models via Univariate Exponential Family Distributions	2013	Eunho Yang Pradeep Ravikumar Genevera I. Allen Zhandong Liu
+ PDF Chat	Regularized partial least squares with an application to NMR spectroscopy	2012	Genevera I. Allen Christine B. Peterson Marina Vannucci Mirjana Maletić‐Savatić
+ PDF Chat	A Log-Linear Graphical Model for inferring genetic networks from high-throughput sequencing data	2012	Genevera I. Allen Zhandong Liu
+	Singular Value Decomposition and High Dimensional Data	2012	Genevera I. Allen Patrick O. Perry
+	Sparse Higher-Order Principal Components Analysis	2012	Genevera I. Allen
+	Regularized Tensor Factorizations and Higher-Order Principal Components Analysis	2012	Genevera I. Allen
+	A Log-Linear Graphical Model for Inferring Genetic Networks from High-Throughput Sequencing Data	2012	Genevera I. Allen Zhandong Liu
+	Regularized Partial Least Squares with an Application to NMR Spectroscopy	2012	Genevera I. Allen Christine B. Peterson Marina Vannucci Mirjana Maletić‐Savatić
+	A Generalized Least Squares Matrix Decomposition	2011	Genevera I. Allen Logan Grosenick Jonathan Taylor
+	A Generalized Least Squares Matrix Decomposition	2011	Genevera I. Allen Logan Grosenick Jonathan Taylor
+ PDF Chat	Transposable regularized covariance models with an application to missing data imputation	2010	Genevera I. Allen Robert Tibshirani
+	Inference with Transposable Data: Modeling the Effects of Row and Column Correlations	2010	Genevera I. Allen Robert Tibshirani
+	Inference with Transposable Data: Modeling the Effects of Row and Column Correlations	2010	Genevera I. Allen Robert Tibshirani
+	KNIFE: Kernel Iterative Feature Extraction	2009	Genevera I. Allen

Common Coauthors

Coauthor	Papers Together
Andersen Chang	12
Michael Weylandt	8
Minjie Wang	8
Frederick Campbell	7
Zhandong Liu	7
Eunho Yang	7
Tiffany M. Tang	6
Lili Zheng	6
Tianyi Yao	6
John Nagorski	5
C. Eric	4
Luqin Gan	4
Yulia Baker	4
Pradeep Ravikumar	4
Madeline Navarro	4
Lili Zheng	4
Logan Grosenick	3
Gautam Dasarathy	3
Robert Tibshirani	3
Yue Hu	3
Giuseppe Vinci	3
David I. Inouye	3
Camille Olivia Little	3
Zhengwu Zhang	3
Pradeep Ravikumar	3
Michael S. Beauchamp	3
Kelly Geyer	3
John F. Magnotti	3
Ying‐Wooi Wan	2
Marina Vannucci	2
David B. Dunson	2
Richard G. Baraniuk	2
Hongtu Zhu	2
Camille Little	2
Santiago Segarra	2
Christine B. Peterson	2
Patrick O. Perry	2
T. Mitchell Roddenberry	2
Jonathan Taylor	2
Mirjana Maletić‐Savatić	2
Manjari Narayan	2
Mohammad Taha Toghani	1
Yue Hu	1
Claire M. Mach	1
Minjie Wang	1
Zachary T. Rewolinski	1
Steffie Tomson	1
Matthew L. Anderson	1
Gautam Dasarthy	1
Jonathan Taylor	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	High-dimensional graphs and variable selection with the Lasso	2006	Nicolai Meinshausen Peter Bühlmann	15
+	Regression Shrinkage and Selection Via the Lasso	1996	Robert Tibshirani	14
+	Model selection and estimation in the Gaussian graphical model	2007	Ming Yuan Yi Lin	14
+ PDF Chat	Splitting Methods for Convex Clustering	2014	C. Eric Kenneth Lange	14
+ PDF Chat	Sparsity and Smoothness Via the Fused Lasso	2004	Robert Tibshirani Michael A. Saunders Saharon Rosset Ji Zhu Keith Knight	13
+	Biclustering via Sparse Singular Value Decomposition	2010	Mihee Lee Haipeng Shen Jianhua Z. Huang J. S. Marron	12
+	Convergence of a Block Coordinate Descent Method for Nondifferentiable Minimization	2001	P. Tseng	11
+	Sparse inverse covariance estimation with the graphical lasso	2007	Jerome H. Friedman Trevor Hastie R. Tibshirani	11
+ PDF Chat	Clusterpath An Algorithm for Clustering using Convex Fusion Penalties	2011	Toby Dylan Hocking Armand Joulin Francis Bach Jean‐Philippe Vert	11
+ PDF Chat	Model Selection and Estimation in Regression with Grouped Variables	2005	Ming Yuan Yi Lin	11
+	High-dimensional Ising model selection using ℓ1-regularized logistic regression	2010	Pradeep Ravikumar Martin J. Wainwright John Lafferty	10
+	Spatial Interaction and the Statistical Analysis of Lattice Systems	1974	Julian Besag	10
+ PDF Chat	The Adaptive Lasso and Its Oracle Properties	2006	Hui Zou	9
+	Regularization Paths for Generalized Linear Models via Coordinate Descent.	2010	Jerome H. Friedman Trevor Hastie Rob Tibshirani	8
+	High-dimensional semiparametric Gaussian copula graphical models	2012	Han Liu Fang Han Ming Yuan John Lafferty Larry Wasserman	7
+	The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs	2009	Han Liu John Lafferty Larry Wasserman	7
+ PDF Chat	Least angle regression	2004	Bradley Efron Trevor Hastie Iain M. Johnstone Robert Tibshirani	7
+ PDF Chat	High-dimensional covariance estimation by minimizing ℓ1-penalized log-determinant divergence	2011	Pradeep Ravikumar Martin J. Wainwright Garvesh Raskutti Bin Yu	7
+	Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties	2001	Jianqing Fan Runze Li	7
+ PDF Chat	The Analysis of Two-Way Functional Data Using Two-Way Regularized Singular Value Decompositions	2009	Jianhua Z. Huang Haipeng Shen Andreas Buja	7
+	Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models	2010	Han Liu Kathryn Roeder Larry Wasserman	7
+	Sparse Higher-Order Principal Components Analysis	2012	Genevera I. Allen	7
+ PDF Chat	Statistical properties of convex clustering	2015	Kean Ming Tan Daniela Witten	7
+ PDF Chat	Sparse Convex Clustering	2017	Binhuan Wang Yilong Zhang Will Wei Sun Yixin Fang	7
+ PDF Chat	High-dimensional analysis of semidefinite relaxations for sparse principal components	2009	Arash Amini Martin J. Wainwright	7
+ PDF Chat	A Generalized Least-Square Matrix Decomposition	2013	Genevera I. Allen Logan Grosenick Jonathan Taylor	7
+	Functional Data Analysis	2005	J. O. Ramsay	6
+ PDF Chat	Convex Biclustering	2016	C. Eric Genevera I. Allen Richard G. Baraniuk	6
+ PDF Chat	On model selection consistency of regularized M-estimators	2015	Jason D. Lee Yuekai Sun Jonathan Taylor	6
+	Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)	2009	Martin J. Wainwright	6
+ PDF Chat	A Constrained<i>ℓ</i><sub>1</sub>Minimization Approach to Sparse Precision Matrix Estimation	2011	Tommaso Cai Weidong Liu Xi Luo	6
+	On Graphical Models via Univariate Exponential Family Distributions	2013	Eunho Yang Pradeep Ravikumar Genevera I. Allen Zhandong Liu	6
+ PDF Chat	Dynamic Visualization and Fast Computation for Convex Clustering via Algorithmic Regularization	2019	Michael Weylandt John Nagorski Genevera I. Allen	6
+ PDF Chat	A Modified Principal Component Technique Based on the LASSO	2003	Ian T. Jolliffe Nickolay T. Trendafilov Mudassir Uddin	6
+ PDF Chat	Lasso-type recovery of sparse representations for high-dimensional data	2009	Nicolai Meinshausen Bin Yu	6
+	A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems	2009	Amir Beck Marc Teboulle	6
+ PDF Chat	Stability Selection	2010	Nicolai Meinshausen Peter Bühlmann	6
+ PDF Chat	Bi-cross-validation of the SVD and the nonnegative matrix factorization	2009	Art B. Owen Patrick O. Perry	6
+	Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing	1995	Yoav Benjamini Yosef Hochberg	6
+	Tensor Decompositions and Applications	2009	Tamara G. Kolda Brett W. Bader	6
+	Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data	2008	Onureena Banerjee Laurent El Ghaoui Alexandre d’Aspremont	5
+	Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition	1970	J. Douglas Carroll Jih-Jie Chang	5
+	Cross-Validatory Estimation of the Number of Components in Factor and Principal Components Models	1978	Svante Wold	5
+	Convex Clustering via <i>l</i> 1 Fusion Penalization	2017	Peter Radchenko Gourab Mukherjee	5
+ PDF Chat	Smoothed functional principal components analysis by choice of norm	1996	Bernard W. Silverman	5
+ PDF Chat	Pathwise coordinate optimization	2007	Jerome H. Friedman Trevor Hastie Holger Höfling Robert Tibshirani	5
+ PDF Chat	A Log-Linear Graphical Model for inferring genetic networks from high-throughput sequencing data	2012	Genevera I. Allen Zhandong Liu	5
+	Sparse inverse covariance estimation with the lasso	2007	Jerome H. Friedman Trevor Hastie Robert Tibshirani	5
+	Foundations of the PARAFAC procedure: Models and conditions for an "explanatory" multi-model factor analysis	1970	Richard A. Harshman	5
+	An EM algorithm for multivariate Poisson distribution and related models	2003	Dimitris Karlis	5