Talk by Vini on "Learning Graphs in Financial Markets"

“Learning Graphs in Financial Markets” presented by PhD student Jose Vinicius de M. Cardoso.

Talk (virtually) delivered at the Hong Kong Machine Learning Meetup, Hong Kong, Jan. 2021. https://www.meetup.com/Hong-Kong-Mach...


  • José Vinícius de M. Cardoso, Jiaxi Ying, and Daniel P. Palomar, “Algorithms for Learning Graphs in Financial Markets,” Dec, 2020. (https://arxiv.org/pdf/2012.15410)

  • José Vinícius de M. Cardoso and Daniel P. Palomar, “Learning Undirected Graphs in Financial Markets,” in Proc. of the 54th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA, 2020. (https://arxiv.org/pdf/2005.09958)

  • Jiaxi Ying, José Vinícius de M. Cardoso, and Daniel P. Palomar, “Minimax Estimation of Laplacian Constrained Precision Matrices,” in Proc. of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS), vol. 130, pp. 3736-3744, April 2021.

  • Jiaxi Ying, José Vinícius de M. Cardoso, and Daniel P. Palomar, “Nonconvex Sparse Graph Learning under Laplacian Constrained Graphical Model,” Advances in Neural Information Processing Systems (NeurIPS), Dec. 2020.

  • Sandeep Kumar, Jiaxi Ying, José Vinícius de M. Cardoso, and Daniel P. Palomar, “A Unified Framework For Structured Graph Learning Via Spectral Constraints,” Journal of Machine Learning Research (JMLR), 21(22): 1-60, Jan. 2020.

  • Sandeep Kumar, Jiaxi Ying, José Vinícius de M. Cardoso, and Daniel P. Palomar, “Structured Graph Learning Via Laplacian Spectral Constraints,” Advances in Neural Information Processing Systems (NeurIPS), Dec. 2019.