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Probabilistic Reduced-Dimensional Vector Autoregressive Modeling with Oblique Projections
In this paper, we propose a probabilistic reduced-dimensional vector autoregressive (PredVAR) model to extract low-dimensional dynamics from high-dimensional noisy data.
Latent Dynamic Networked System Identification with High-Dimensional Networked Data
Networked dynamic systems are ubiquitous in various domains, such as industrial processes, social networks, and biological systems.
Optimal $(0,1)$-Matrix Completion with Majorization Ordered Objectives (To the memory of Pravin Varaiya)
We propose and examine two optimal $(0, 1)$-matrix completion problems with majorization ordered objectives.
Optimal Online Algorithms for Peak-Demand Reduction Maximization with Energy Storage
In this paper, we propose an optimal online algorithm that achieves the best competitive ratio, following the idea of maintaining a constant ratio between the online and the optimal offline peak-reduction performance.
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