Papers

José Vinícius de M. Cardoso, Jiaxi Ying, and Daniel P. Palomar, “Learning Bipartite Graphs: Heavy Tails and Multiple Components,” Advances in Neural Information Processing Systems (NeurIPS), New Orleans, LA, USA, Dec.

Xiwen Wang, Jiaxi Ying, José Vinícius de M. Cardoso, and Daniel P. Palomar, “Efficient Algorithms for General Isotone Optimization,” in The Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI), Feb. 2022.

José Vinícius de M. Cardoso, Jiaxi Ying, and Daniel P. Palomar, “Graphical Models for Heavy-Tailed Markets,” Advances in Neural Information Processing Systems (NeurIPS), Virtual, Dec. 2021. [26% acceptance rate] [video] [supplemental material] [slides] [poster]

🏆 Ying Sun, Prabhu Babu, and Daniel P. Palomar, “Majorization-Minimization Algorithms in Signal Processing, Communications, and Machine Learning,” IEEE Trans. on Signal Processing, vol. 65, no. 3, pp. 794-816, Feb. 2017.

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. [2-min video] [slides] [poster] [R package]