no code implementations • NeurIPS 2011 • Animashree Anandkumar, Vincent Tan, Alan S. Willsky
We consider the problem of Ising and Gaussian graphical model selection given n i. i. d.
no code implementations • 10 Dec 2020 • Vincent Tan, Stefan Zohren
By correcting the biases in the sample eigenvalues and aligning our estimator to more recent risk, we demonstrate that our estimator performs well in large dimensions against existing state-of-the-art static and dynamic covariance shrinkage estimators through simulations and with an empirical application in active portfolio management.
no code implementations • 29 Sep 2021 • Haiyun He, Hanshu Yan, Vincent Tan
We consider iterative semi-supervised learning (SSL) algorithms that iteratively generate pseudo-labels for a large amount unlabelled data to progressively refine the model parameters.
no code implementations • 22 Feb 2022 • Nikan Firoozye, Vincent Tan, Stefan Zohren
This paper presents a novel framework for analyzing the optimal asset and signal combination problem.
no code implementations • 20 Oct 2023 • Ruiquan Huang, Yuan Cheng, Jing Yang, Vincent Tan, Yingbin Liang
To this end, we posit a joint model class for tasks and use the notion of $\eta$-bracketing number to quantify its complexity; this number also serves as a general metric to capture the similarity of tasks and thus determines the benefit of multi-task over single-task RL.