Byol Kim

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All published works

Action	Title	Year	Authors
+ PDF Chat	Black-box tests for algorithmic stability	2023	Byol Kim Rina Foygel Barber
+ PDF Chat	Two-Sample Inference for High-Dimensional Markov Networks	2021	Byol Kim Song Liu Mladen Kolar
+	Black-box tests for algorithmic stability	2021	Byol Kim Rina Foygel Barber
+	Predictive Inference Is Free with the Jackknife+-after-Bootstrap	2020	Byol Kim Xu Chen Rina Foygel Barber
+	Interface Engineering in Hybrid Halide Perovskites Using Lewis Base and Graphene	2019	Chol‐Jun Yu Yun-Hyok Kye Un-Gi Jong Song-Guk Ko Kum-Chol Ri Song-Hyok Choe Jin-Song Kim Gwon-Il Ryu Byol Kim M. Saiful Islam
+	Two-sample inference for high-dimensional Markov networks	2019	Byol Kim Song Liu Mladen Kolar

Common Coauthors

Coauthor	Papers Together
Rina Foygel Barber	3
Mladen Kolar	2
Song-Hyok Choe	1
Kum-Chol Ri	1
Yun-Hyok Kye	1
Song-Guk Ko	1
Song Liu	1
Chol‐Jun Yu	1
Jin-Song Kim	1
Xu Chen	1
Song Liu	1
Un-Gi Jong	1
M. Saiful Islam	1
Gwon-Il Ryu	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Inferring multiple graphical structures	2010	Julien Chiquet Yves Grandvalet Christophe Ambroise	2
+	Confidence intervals and hypothesis testing for high-dimensional regression	2014	Adel Javanmard Andrea Montanari	2
+ PDF Chat	The Joint Graphical Lasso for Inverse Covariance Estimation Across Multiple Classes	2013	Patrick Danaher Pei Wang Daniela Witten	2
+	Model selection and estimation in the Gaussian graphical model	2007	Ming Yuan Yi Lin	2
+	Node-Based Learning of Multiple Gaussian Graphical Models.	2014	Karthik Mohan Palma London Maryam Fazel Daniela Witten Su‐In Lee	2
+ PDF Chat	Estimating Divergence Functionals and the Likelihood Ratio by Convex Risk Minimization	2010	XuanLong Nguyen Martin J. Wainwright Michael I. Jordan	2
+	High Dimensional Inverse Covariance Matrix Estimation via Linear Programming	2010	Ming Yuan	2
+	Sparse inverse covariance estimation with the graphical lasso	2007	Jerome H. Friedman Trevor Hastie R. Tibshirani	2
+	Leave-one-out prediction intervals in linear regression models with many variables	2016	Lukas Steinberger Hannes Leeb	2
+ PDF Chat	Post-Selection Inference for Generalized Linear Models With Many Controls	2016	Alexandre Belloni Victor Chernozhukov Ying Wei	2
+ PDF Chat	High-dimensional simultaneous inference with the bootstrap	2017	Ruben Dezeure Peter Bühlmann Cun-Hui Zhang	2
+ PDF Chat	Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation	2014	Song Liu John A. Quinn Michael U. Gutmann Taiji Suzuki Masashi Sugiyama	2
+	Post-regularization inference for time-varying nonparanormal graphical models	2017	Junwei Lu Mladen Kolar Han Liu	2
+	ROCKET: Robust confidence intervals via Kendall’s tau for transelliptical graphical models	2018	Rina Foygel Barber Mladen Kolar	2
+	Sparse matrix inversion with scaled Lasso	2013	Tingni Sun Cun‐Hui Zhang	2
+	Joint structural estimation of multiple graphical models	2016	Jing Ma George Michailidis	2
+ PDF Chat	A Constrained<i>ℓ</i><sub>1</sub>Minimization Approach to Sparse Precision Matrix Estimation	2011	Tommaso Cai Weidong Liu Xi Luo	2
+ PDF Chat	Honest confidence regions and optimality in high-dimensional precision matrix estimation	2016	Jana Janková Sara van de Geer	2
+ PDF Chat	Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models	2013	Cun‐Hui Zhang Stephanie S. Zhang	2
+	A general theory of hypothesis tests and confidence regions for sparse high dimensional models	2017	Yang Ning Han Liu	2
+ PDF Chat	High-dimensional covariance estimation by minimizing ℓ1-penalized log-determinant divergence	2011	Pradeep Ravikumar Martin J. Wainwright Garvesh Raskutti Bin Yu	2
+ PDF Chat	Gaussian and bootstrap approximations for high-dimensional U-statistics and their applications	2018	Xiaohong Chen	2
+	Markov fields on finite graphs and lattices	1971	J. M. Hammersley Peter Clifford	2
+	Support consistency of direct sparse-change learning in Markov networks	2017	Song Liu Taiji Suzuki Raissa Relator Jun Sese Masashi Sugiyama Kenji Fukumizu	2
+	Differential network analysis: A statistical perspective	2020	Ali Shojaie	2
+	A Least-squares Approach to Direct Importance Estimation	2009	Takafumi Kanamori Shohei Hido Masashi Sugiyama	2
+	Inter-Subject Analysis: Inferring Sparse Interactions with Dense Intra-Graphs	2017	Cong Ma Junwei Lu Han Liu	2
+ PDF Chat	Distribution and correlation-free two-sample test of high-dimensional means	2020	Kaijie Xue Fang Yao	2
+	Structural similarity and difference testing on multiple sparse Gaussian graphical models	2017	Weidong Liu	2
+	On asymptotically optimal confidence regions and tests for high-dimensional models	2014	Sara van de Geer Peter Bühlmann Ya’acov Ritov Ruben Dezeure	2
+	Confidence intervals for high-dimensional inverse covariance estimation	2015	Jana Janková Sara van de Geer	2
+	Least squares after model selection in high-dimensional sparse models	2013	Alexandre Belloni Victor Chernozhukov	2
+ PDF Chat	Group Bound: Confidence Intervals for Groups of Variables in Sparse High Dimensional Regression Without Assumptions on the Design	2014	Nicolai Meinshausen	2
+ PDF Chat	Beyond Gaussian approximation: Bootstrap for maxima of sums of independent random vectors	2020	Hang Deng Cun‐Hui Zhang	2
+	Joint Estimation and Inference for Data Integration Problems based on Multiple Multi-layered Gaussian Graphical Models	2018	Subhabrata Majumdar George Michailidis	2
+ PDF Chat	Predictive inference with the jackknife+	2021	Rina Foygel Barber Emmanuel J. Candès Aaditya Ramdas Ryan J. Tibshirani	2
+	High-dimensional econometrics and regularized GMM	2018	Kengo Kato Christian Hansen Denis Chetverikov Victor Chernozhukov Alexandre Belloni	2
+ PDF Chat	Inference on Treatment Effects after Selection among High-Dimensional Controls	2013	Alexandre Belloni Victor Chernozhukov Christian Hansen	2
+ PDF Chat	Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach	2015	Victor Chernozhukov Christian Hansen Martin Spindler	1
+	A Unified Framework for High-Dimensional Analysis of $M$-Estimators with Decomposable Regularizers	2012	Sahand Negahban Pradeep Ravikumar Martin J. Wainwright Bin Yu	1
+	Node-Based Learning of Multiple Gaussian Graphical Models	2013	Karthik Mohan Palma London Maryam Fazel Daniela Witten Su‐In Lee	1
+	Central limit theorems and bootstrap in high dimensions	2017	Victor Chernozhukov Denis Chetverikov Kengo Kato	1
+	Pivotal estimation via square-root Lasso in nonparametric regression	2014	Alexandre Belloni Victor Chernozhukov Lie Wang	1
+	On Graphical Models via Univariate Exponential Family Distributions	2013	Eunho Yang Pradeep Ravikumar Genevera I. Allen Zhandong Liu	1
+	Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensional random vectors	2013	Victor Chernozhukov Denis Chetverikov Kengo Kato	1
+ PDF Chat	Generalized random forests	2019	Susan Athey Julie Tibshirani Stefan Wager	1
+	Generalized direct change estimation in ising model structure	2016	Farideh Fazayeli Arindam Banerjee	1
+	Almost-everywhere algorithmic stability and generalization error	2002	Samuel Kutin Partha Niyogi	1
+ PDF Chat	Distribution-Free Predictive Inference for Regression	2017	Jing Lei Max G’Sell Alessandro Rinaldo Ryan J. Tibshirani Larry Wasserman	1
+ PDF Chat	Structure Learning in Graphical Modeling	2016	Mathias Drton Marloes H. Maathuis	1