| AdaBlock: SGD with Practical Block Diagonal Matrix Adaptation for Deep Learning | 0 | 0.34 | 2022 |
| A graph Laplacian prior for Bayesian variable selection and grouping. | 0 | 0.34 | 2019 |
| Stochastic Gradient Methods with Block Diagonal Matrix Adaptation. | 0 | 0.34 | 2019 |
| Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning. | 0 | 0.34 | 2019 |
| On Extensions of CLEVER: A Neural Network Robustness Evaluation Algorithm. | 0 | 0.34 | 2018 |
| Simultaneous Parameter Learning and Bi-Clustering for Multi-Response Models. | 0 | 0.34 | 2018 |
| How to foster innovation: A data-driven approach to measuring economic competitiveness. | 0 | 0.34 | 2017 |
| Generalized Kalman smoothing: Modeling and algorithms. | 7 | 0.50 | 2017 |
| Learning Task Clusters via Sparsity Grouped Multitask Learning. | 1 | 0.35 | 2017 |
| Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. | 0 | 0.34 | 2017 |
| Sparse + Group-Sparse Dirty Models: Statistical Guarantees without Unreasonable Conditions and a Case for Non-Convexity. | 0 | 0.34 | 2017 |
| Understanding Innovation to Drive Sustainable Development. | 0 | 0.34 | 2016 |
| Removing Clouds And Recovering Ground Observations In Satellite Image Sequences Via Temporally Contiguous Robust Matrix Completion | 1 | 0.38 | 2016 |
| Stable Estimation Of Granger-Causal Factors Of Country-Level Innovation | 0 | 0.34 | 2016 |
| Closed-form Estimators for High-dimensional Generalized Linear Models | 1 | 0.35 | 2015 |
| Robust Gaussian Graphical Modeling with the Trimmed Graphical Lasso | 4 | 0.44 | 2015 |
| Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger Causality. | 3 | 0.41 | 2014 |
| Elementary Estimators for Graphical Models. | 3 | 0.44 | 2014 |
| Elementary Estimators for High-Dimensional Linear Regression. | 1 | 0.40 | 2014 |
| Orthogonal Matching Pursuit for Sparse Quantile Regression | 4 | 0.42 | 2014 |
| Sparse Quantile Huber Regression for Efficient and Robust Estimation. | 1 | 0.42 | 2014 |
| Elementary Estimators for Sparse Covariance Matrices and other Structured Moments. | 3 | 0.44 | 2014 |
| A Parallel, Block Greedy Method for Sparse Inverse Covariance Estimation for Ultra-high Dimensions. | 3 | 0.48 | 2013 |
| Robust sparse estimation of multiresponse regression and inverse covariance matrix via the L2 distance | 3 | 0.39 | 2013 |
| Scalable Matrix-valued Kernel Learning and High-dimensional Nonlinear Causal Inference | 1 | 0.36 | 2012 |
| A Bayesian Markov-switching Model for Sparse Dynamic Network Estimation. | 0 | 0.34 | 2012 |
| Multi-level Lasso for Sparse Multi-task Regression. | 0 | 0.34 | 2012 |
| Group Orthogonal Matching Pursuit for Logistic Regression | 0 | 0.34 | 2011 |
| Group Orthogonal Matching Pursuit for Logistic Regression. | 0 | 0.34 | 2011 |
| Temporal graphical models for cross-species gene regulatory network discovery. | 7 | 0.57 | 2011 |
| Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels. | 8 | 0.62 | 2011 |
| Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference. | 0 | 0.34 | 2010 |
| Learning Temporal Causal Graphs for Relational Time-Series Analysis | 19 | 1.06 | 2010 |
| A data modeling approach to climate change attribution | 0 | 0.34 | 2009 |
| Spatial-temporal causal modeling for climate change attribution | 36 | 2.28 | 2009 |
| Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction. | 0 | 0.34 | 2009 |
| Grouped graphical Granger modeling methods for temporal causal modeling | 10 | 0.82 | 2009 |
| Proximity-Based Anomaly Detection Using Sparse Structure Learning | 19 | 1.14 | 2009 |
| Throughput scaling in wireless networks with restricted mobility | 7 | 0.58 | 2007 |
| Convergence And Consisitency Of Recursive Boosting | 0 | 0.34 | 2006 |
| Convergence and Consistency of Regularized Boosting Algorithms with Stationary B-Mixing Observations | 3 | 0.59 | 2005 |
| A Wireless Network Can Achieve Maximum Throughput Without Each Node Meeting All Others | 0 | 0.34 | 2005 |
