Palomar, Daniel

7 publications

NeurIPS 2023 Fast Projected Newton-like Method for Precision Matrix Estimation Under Total Positivity Jian-Feng Cai, José Vinícius de Miranda Cardoso, Daniel Palomar, Jiaxi Ying

NeurIPS 2023 Learning Large-Scale MTP$_2$ Gaussian Graphical Models via Bridge-Block Decomposition Xiwen Wang, Jiaxi Ying, Daniel Palomar

NeurIPS 2022 Learning Bipartite Graphs: Heavy Tails and Multiple Components José Vinícius de Miranda Cardoso, Jiaxi Ying, Daniel Palomar

AISTATS 2021 Minimax Estimation of Laplacian Constrained Precision Matrices Jiaxi Ying, José Miranda Cardoso, Daniel Palomar

NeurIPS 2021 Graphical Models in Heavy-Tailed Markets Jose Vinicius de Miranda Cardoso, Jiaxi Ying, Daniel Palomar

NeurIPS 2020 Nonconvex Sparse Graph Learning Under Laplacian Constrained Graphical Model Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel Palomar

NeurIPS 2019 Structured Graph Learning via Laplacian Spectral Constraints Sandeep Kumar, Jiaxi Ying, Jose Vinicius de Miranda Cardoso, Daniel Palomar