Frank Nussbaum

Generating author description...

All published works

Action	Title	Year	Authors
+	Mixed membership Gaussians	2022	Joachim Giesen Paul Kahlmeyer Sören Laue Matthias Mitterreiter Frank Nussbaum Christoph Staudt
+	Method of Moments for Topic Models with Mixed Discrete and Continuous Features	2021	Joachim Giesen Paul Kahlmeyer Sören Laue Matthias Mitterreiter Frank Nussbaum Christoph Staudt Sina Zarrieß
+	Models with low-rank and group-sparse components and their recovery via convex optimization	2021	Frank Nussbaum
+	Pairwise sparse + low-rank models for variables of mixed type	2020	Frank Nussbaum Joachim Giesen
+	Efficient Regularization Parameter Selection for Latent Variable Graphical Models via Bi-Level Optimization	2019	Joachim Giesen Frank Nussbaum Christopher Schneider
+	Ising Models with Latent Conditional Gaussian Variables	2019	Frank Nussbaum Joachim Giesen
+	Ising Models with Latent Conditional Gaussian Variables	2019	Frank Nussbaum Joachim Giesen

Common Coauthors

Coauthor	Papers Together
Joachim Giesen	6
Matthias Mitterreiter	2
Paul Kahlmeyer	2
Christoph Staudt	2
Sören Laue	2
Christopher Schneider	1
Sina Zarrieß	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Latent variable graphical model selection via convex optimization	2012	Venkat Chandrasekaran Pablo A. Parrilo Alan S. Willsky	3
+ PDF Chat	On model selection consistency of regularized M-estimators	2015	Jason D. Lee Yuekai Sun Jonathan Taylor	2
+	A theoretical basis for the reduction of polynomials to canonical forms	1976	Bruno Buchberger	2
+ PDF Chat	Most Tensor Problems Are NP-Hard	2013	Christopher J. Hillar Lek‐Heng Lim	2
+ PDF Chat	A Spectral Algorithm for Latent Dirichlet Allocation	2014	Anima Anandkumar Dean P. Foster Daniel Hsu Sham M. Kakade Yi-Kai Liu	2
+ PDF Chat	Learning the Structure of Mixed Graphical Models	2014	Jason D. Lee Trevor Hastie	2
+	High-dimensional graphs and variable selection with the Lasso	2006	Nicolai Meinshausen Peter Bühlmann	2
+	High-dimensional Ising model selection using ℓ1-regularized logistic regression	2010	Pradeep Ravikumar Martin J. Wainwright John Lafferty	2
+	Performance Guarantees for Regularized Maximum Entropy Density Estimation	2004	Miroslav Dudı́k Steven J. Phillips Robert E. Schapire	2
+	A Tensor Approach to Learning Mixed Membership Community Models	2013	Anima Anandkumar Rong Ge Daniel Hsu Sham M. Kakade	2
+	Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)	2009	Martin J. Wainwright	2
+ PDF Chat	Rank-Sparsity Incoherence for Matrix Decomposition	2011	Venkat Chandrasekaran Sujay Sanghavi Pablo A. Parrilo Alan S. Willsky	2
+	Introduction to the non-asymptotic analysis of random matrices	2010	Roman Vershynin	2
+	Three-way arrays: rank and uniqueness of trilinear decompositions, with application to arithmetic complexity and statistics	1977	Joseph B. Kruskal	2
+	Characterization of the subdifferential of some matrix norms	1992	G. A. Watson	2
+	Learning mixtures of spherical Gaussians: moment methods and spectral decompositions	2012	Daniel Hsu Sham M. Kakade	2
+ PDF Chat	High-dimensional covariance estimation by minimizing ℓ1-penalized log-determinant divergence	2011	Pradeep Ravikumar Martin J. Wainwright Garvesh Raskutti Bin Yu	1
+ PDF Chat	Alternating Direction Methods for Latent Variable Gaussian Graphical Model Selection	2013	Shiqian Ma Lingzhou Xue Hui Zou	1
+	Scikit-learn: Machine Learning in Python	2012	Fabián Pedregosa Gaël Varoquaux Alexandre Gramfort Vincent Michel Bertrand Thirion Olivier Grisel Mathieu Blondel Peter Prettenhofer Ron J. Weiss Vincent Dubourg	1
+	Tensor decompositions for learning latent variable models	2014	Animashree Anandkumar Rong Ge Daniel Hsu Sham M. Kakade Matus Telgarsky	1
+	Factor analysis with (mixed) observed and latent variables in the exponential family	2001	Michel Wedel Wagner A. Kamakura	1
+ PDF Chat	Robust principal component analysis?	2011	Emmanuel J. Candès Xiaodong Li Yi Ma John Wright	1
+ PDF Chat	Latent Variable Models for Mixed Discrete and Continuous Outcomes	1997	Mary D. Sammel Louise Ryan Julie Legler	1
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	1
+	On Learning Discrete Graphical Models using Group-Sparse Regularization	2011	Ali Jalali Pradeep Ravikumar Vishvas Vasuki Sujay Sanghavi	1
+	A Fused Latent and Graphical Model for Multivariate Binary Data	2016	Yunxiao Chen Xiaoou Li Jingchen Liu Zhiliang Ying	1
+	Analysis of an algorithm for approximating convex bodies	1994	G. K. Kamenev	1
+ PDF Chat	A Hierarchical Approach for Generating Descriptive Image Paragraphs	2017	Jonathan Krause Justin Johnson Ranjay Krishna Li Fei-Fei	1
+ PDF Chat	Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction	2017	Richard Zhang Phillip Isola Alexei A. Efros	1
+ PDF Chat	Deep Clustering for Unsupervised Learning of Visual Features	2018	Mathilde Caron Piotr Bojanowski Armand Joulin Matthijs Douze	1
+ PDF Chat	Tensor Decompositions for Learning Latent Variable Models	2012	Anima Anandkumar Rong Ge Daniel Hsu Sham M. Kakade Matus Telgarsky	1
+	Ising Models with Latent Conditional Gaussian Variables	2019	Frank Nussbaum Joachim Giesen	1
+	Efficient Regularization Parameter Selection for Latent Variable Graphical Models via Bi-Level Optimization	2019	Joachim Giesen Frank Nussbaum Christopher Schneider	1
+ PDF Chat	Spectral Learning on Matrices and Tensors	2019	Majid Janzamin Rong Ge Jean Kossaifi Anima Anandkumar	1
+	Self-Supervised Visual Feature Learning With Deep Neural Networks: A Survey	2020	Longlong Jing Yingli Tian	1
+	Discussion: Latent variable graphical model selection via convex optimization	2012	Emmanuel J. Candès Mahdi Soltanolkotabi	1
+ PDF Chat	Quantitative estimates of the convergence of the empirical covariance matrix in log-concave ensembles	2009	Radosław Adamczak Alexander E. Litvak Alain Pajor Nicole Tomczak-Jaegermann	1
+ PDF Chat	Spectral Learning on Matrices and Tensors	2019	Majid Janzamin Rong Ge Jean Kossaifi Anima Anandkumar	1
+	Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses	2013	Po‐Ling Loh Martin J. Wainwright	1
+	Discussion: Latent variable graphical model selection via convex optimization	2012	Ming Yuan	1
+	Discussion: Latent variable graphical model selection via convex optimization	2012	Steffen L. Lauritzen Nicolai Meinshausen	1
+ PDF Chat	Exploring Simple Siamese Representation Learning	2021	Xinlei Chen Kaiming He	1
+ PDF Chat	High-Dimensional Mixed Graphical Models	2016	Jie Cheng Tianxi Li Elizaveta Levina Ji Zhu	1
+	Method of Moments for Topic Models with Mixed Discrete and Continuous Features	2021	Joachim Giesen Paul Kahlmeyer Sören Laue Matthias Mitterreiter Frank Nussbaum Christoph Staudt Sina Zarrieß	1
+	Discussion: Latent variable graphical model selection via convex optimization	2012	Martin J. Wainwright	1
+	Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition	2015	Rong Ge Furong Huang Chi Jin Yuan Yang	1
+	Tracking Approximate Solutions of Parameterized Optimization Problems over Multi-Dimensional (Hyper-)Parameter Domains	2015	Katharina Blechschmidt Joachim Giesen Soeren Laue	1
+ PDF Chat	Graph Selection with GGMselect	2012	Christophe Giraud Sylvie Huet Nicolas Verzélen	1
+ PDF Chat	Singular Wishart and multivariate beta distributions	2003	Muni S. Srivastava	1
+ PDF Chat	Learning mixtures of spherical gaussians	2013	Daniel Hsu Sham M. Kakade	1