1 citations · 3 across the 6 of their papers we have counts for
6 papers
Can Transformers Learn Optimal Filtering for Unknown Systems?
Haldun Balim, Zhe Du, Samet Oymak +1
Transformer models have shown great success in natural language processing; however, their potential remains mostly unexplored for dynamical systems. In this work, we investigate t…
Mode Reduction for Markov Jump Systems
Zhe Du, Laura Balzano, Necmiye Ozay
Switched systems are capable of modeling processes with underlying dynamics that may change abruptly over time. To achieve accurate modeling in practice, one may need a large numbe…
Identification and Adaptive Control of Markov Jump Systems: Sample Complexity and Regret Bounds
Yahya Sattar, Zhe Du, Davoud Ataee Tarzanagh +3
Learning how to effectively control unknown dynamical systems is crucial for intelligent autonomous systems. This task becomes a significant challenge when the underlying dynamics…
Certainty Equivalent Quadratic Control for Markov Jump Systems
Zhe Du, Yahya Sattar, Davoud Ataee Tarzanagh +3
Real-world control applications often involve complex dynamics subject to abrupt changes or variations. Markov jump linear systems (MJS) provide a rich framework for modeling such…
Mode Clustering for Markov Jump Systems
Zhe Du, Necmiye Ozay, Laura Balzano
In this work, we consider the problem of mode clustering in Markov jump models. This model class consists of multiple dynamical modes with a switching sequence that determines how…
A Robust Algorithm for Online Switched System Identification
Zhe Du, Necmiye Ozay, Laura Balzano
In this paper, we consider the problem of online identification of Switched AutoRegressive eXogenous (SARX) systems, where the goal is to estimate the parameters of each subsystem…