Papers | Daniel P. Palomar

Paper award at Asilomar

Sat, 09 Nov 2024 00:00:00 +0000

Yifan Yu has been awarded the Best Student Paper Award (Bronze) at the Asilomar Conference on Signals, Systems, and Computers! 🎉

Our paper, titled “Robust and Constrained Estimation of State-Space Models: A Majorization-Minimization Approach,” introduces efficient methods for extending the Kalman filter to handle non-Gaussian observations—particularly useful in applications such as financial data analysis.

LinkedIn announcement

Yifan Yu, Shengjie Xiu, and Daniel P. Palomar, “Robust and Constrainted Estimation of State-Space Models: A Majorization-Minimization Approach,” in Proc. of the Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, 2024.

Portfolio Optimization book available online

Thu, 15 Aug 2024 00:00:00 +0000

Daniel P. Palomar. Portfolio Optimization. Cambridge University Press, 2025.

Paper published in Nature Communications

Tue, 07 May 2024 00:00:00 +0000

Syed Awais W. Shah, Daniel P. Palomar, Ian Barr, Leo L. M. Poon, Ahmed Abdul Quadeer, and Matthew R. McKay, “Seasonal antigenic prediction of influenza A H3N2 using machine learning,” Nature Communications, vol. 15, no. 3833, 2024.

Paper on graph learning accepted in IEEE Trans. on Signal Processing

Tue, 23 Jan 2024 00:00:00 +0000

Amirhossein Javaheri, Arash Amini, Farokh Marvasti, and Daniel P. Palomar, “Learning Spatio-Temporal Graphical Models From Incomplete Observations,” IEEE Trans. on Signal Processing, vol. 72, pp. 1361-1374, 2024.

Paper published in NeurIPS

Sun, 10 Dec 2023 00:00:00 +0000

Jian-Feng Cai, José Vinícius de M. Cardoso, Daniel P. Palomar, and Jiaxi Ying, “Fast Projected Newton-like Method for Precision Matrix Estimation under Total Positivity,” Advances in Neural Information Processing Systems (NeurIPS), New Orleans, LA, USA, Dec. 2023. [26.1% acceptance rate] [video] [slides] [poster]

Paper published in NeurIPS

Sun, 10 Dec 2023 00:00:00 +0000

Xiwen Wang, Jiaxi Ying, and Daniel P. Palomar, “Learning Large-Scale MTP2 Gaussian Graphical Models via Bridge-Block Decomposition,” Advances in Neural Information Processing Systems (NeurIPS), New Orleans, LA, USA, Dec. 2023. [26.1% acceptance rate] [video] [slides] [poster]

Paper on high-order portfolios accepted in IEEE Trans. on Signal Processing

Fri, 04 Aug 2023 00:00:00 +0000

Xiwen Wang, Rui Zhou, Jiaxi Ying, and Daniel P. Palomar, “Efficient and Scalable Parametric High-Order Portfolios Design via the Skew-t Distribution,” IEEE Trans. on Signal Processing, vol. 71, pp. 3726-3740, 2023.

Paper published in IEEE Trans. on Signal Processing

Sat, 01 Jul 2023 00:00:00 +0000

Shengjie Xiu, Xiwen Wang, and Daniel P. Palomar, “A Fast Successive QP Algorithm for General Mean-Variance Portfolio Optimization,” IEEE Trans. on Signal Processing, vol. 71, pp. 2713-2727, July 2023.

Paper accepted in NeurIPS!

Thu, 15 Sep 2022 00:00:00 +0000

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. 2022. [25.6% acceptance rate]

Paper accepted in AAAI!

Mon, 01 Nov 2021 00:00:00 +0000

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. [15% acceptance rate]

Paper accepted in NeurIPS!

Wed, 29 Sep 2021 00:00:00 +0000

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]

Our paper has received the 2020 Young Author Best Paper Award by the IEEE Signal Processing Society!!

Sat, 12 Dec 2020 00:00:00 +0000

🏆 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.

News at HKUST

Sun Ying’s webpage: She is an Assistant Professor at Penn State.

Paper accepted in NeurIPS!

Sat, 26 Sep 2020 00:00:00 +0000

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]