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20132023
most citedConsistency Analysis of the Simplified Refined Instrumental Variable Method for Continuous-time Systems

3 citations · 11 across the 19 of their papers we have counts for

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Showing 2023Show all

7 papers · 1 filter

cs.LG2023

DRCFS: Doubly Robust Causal Feature Selection

Francesco Quinzan, Ashkan Soleymani, Patrick Jaillet +2

Knowing the features of a complex system that are highly relevant to a particular target variable is of fundamental interest in many areas of science. Existing approaches are often…

eess.SY2023

On the Relation between Discrete and Continuous-time Refined Instrumental Variable Methods

Rodrigo A. González, Cristian R. Rojas, Siqi Pan +1

The Refined Instrumental Variable method for discrete-time systems (RIV) and its variant for continuous-time systems (RIVC) are popular methods for the identification of linear sys…

stat.ML2023

Decentralized diffusion-based learning under non-parametric limited prior knowledge

Paweł Wachel, Krzysztof Kowalczyk, Cristian R. Rojas

We study the problem of diffusion-based network learning of a nonlinear phenomenon, , from local agents' measurements collected in a noisy environment. For a decentralized netwo…

cs.RO2023

Diagnosing and Augmenting Feature Representations in Correctional Inverse Reinforcement Learning

Inês Lourenço, Andreea Bobu, Cristian R. Rojas +1

Robots have been increasingly better at doing tasks for humans by learning from their feedback, but still often suffer from model misalignment due to missing or incorrectly learned…

eess.SY2023

An EM Algorithm for Lebesgue-sampled State-space Continuous-time System Identification

Rodrigo A. González, Angel L. Cedeño, María Coronel +2

This paper concerns the identification of continuous-time systems in state-space form that are subject to Lebesgue sampling. Contrary to equidistant (Riemann) sampling, Lebesgue sa…

eess.SY20231 cited

Parsimonious Identification of Continuous-Time Systems: A Block-Coordinate Descent Approach

Rodrigo A. González, Cristian R. Rojas, Siqi Pan +1

The identification of electrical, mechanical, and biological systems using data can benefit greatly from prior knowledge extracted from physical modeling. Parametric continuous-tim…