Dario Piga

Orcid: 0000-0001-7691-4886

According to our database1, Dario Piga authored at least 121 papers between 2009 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Integrating Reinforcement Learning with Foundation Models for Autonomous Robotics: Methods and Perspectives.
CoRR, 2024

Enhanced Transformer architecture for in-context learning of dynamical systems.
CoRR, 2024

LightCPPgen: An Explainable Machine Learning Pipeline for Rational Design of Cell Penetrating Peptides.
CoRR, 2024

Model order reduction of deep structured state-space models: A system-theoretic approach.
CoRR, 2024

Synthetic data generation for system identification: leveraging knowledge transfer from similar systems.
CoRR, 2024

BenchCloudVision: A Benchmark Analysis of Deep Learning Approaches for Cloud Detection and Segmentation in Remote Sensing Imagery.
CoRR, 2024

RoboMorph: In-Context Meta-Learning for Robot Dynamics Modeling.
Proceedings of the 21st International Conference on Informatics in Control, 2024

2023
On the adaptation of recurrent neural networks for system identification.
Autom., September, 2023

Data-Driven Computation of Robust Invariant Sets and Gain-Scheduled Controllers for Linear Parameter-Varying Systems.
IEEE Control. Syst. Lett., 2023

From System Models to Class Models: An In-Context Learning Paradigm.
IEEE Control. Syst. Lett., 2023

Multi-Agent Active Learning for Distributed Black-Box Optimization.
IEEE Control. Syst. Lett., 2023

In-context learning of state estimators.
CoRR, 2023

On the adaptation of in-context learners for system identification.
CoRR, 2023

Gradient-based bilevel optimization for multi-penalty Ridge regression through matrix differential calculus.
CoRR, 2023

Shedding Light on the Ageing of Extra Virgin Olive Oil: Probing the Impact of Temperature with Fluorescence Spectroscopy and Machine Learning Techniques.
CoRR, 2023

Split-Boost Neural Networks.
CoRR, 2023

In-context learning for model-free system identification.
CoRR, 2023

Neural State-Space Models: Empirical Evaluation of Uncertainty Quantification.
CoRR, 2023

Experience in Engineering Complex Systems: Active Preference Learning with Multiple Outcomes and Certainty Levels.
CoRR, 2023

Computation of parameter dependent robust invariant sets for LPV models with guaranteed performance.
Autom., 2023

Learning Choice Functions with Gaussian Processes.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Q-Learning-Based Model Predictive Variable Impedance Control for Physical Human-Robot Collaboration (Extended Abstract).
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Bayesian Optimization For Choice Data.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

2022
C-GLISp: Preference-Based Global Optimization Under Unknown Constraints With Applications to Controller Calibration.
IEEE Trans. Control. Syst. Technol., 2022

Sensorless Optimal Interaction Control Exploiting Environment Stiffness Estimation.
IEEE Trans. Control. Syst. Technol., 2022

Learning Dynamical Systems From Quantized Observations: A Bayesian Perspective.
IEEE Trans. Autom. Control., 2022

Robot End-Effector Mounted Camera Pose Optimization in Object Detection-Based Tasks.
J. Intell. Robotic Syst., 2022

Active preference-based optimization for human-in-the-loop feature selection.
Eur. J. Control, 2022

Direct identification of continuous-time linear switched state-space models.
CoRR, 2022

Learning neural state-space models: do we need a state estimator?
CoRR, 2022

Direct identification of continuous-time LPV state-space models via an integral architecture.
Autom., 2022

Continuous control actions learning and adaptation for robotic manipulation through reinforcement learning.
Auton. Robots, 2022

Q-Learning-based model predictive variable impedance control for physical human-robot collaboration.
Artif. Intell., 2022

Visual Servoing with Geometrically Interpretable Neural Perception.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

2021
Human-robot collaboration in sensorless assembly task learning enhanced by uncertainties adaptation via Bayesian Optimization.
Robotics Auton. Syst., 2021

Pairwise Preferences-Based Optimization of a Path-Based Velocity Planner in Robotic Sealing Tasks.
IEEE Robotics Autom. Lett., 2021

A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian Processes.
Mach. Learn., 2021

Global optimization based on active preference learning with radial basis functions.
Mach. Learn., 2021

Optimal direct data-driven control with stability guarantees.
Eur. J. Control, 2021

Continuous-time system identification with neural networks: Model structures and fitting criteria.
Eur. J. Control, 2021

Choice functions based multi-objective Bayesian optimisation.
CoRR, 2021

Deep learning with transfer functions: new applications in system identification.
CoRR, 2021

Model structure selection for switched NARX system identification: A randomized approach.
Autom., 2021

Sensorless environment stiffness and interaction force estimation for impedance control tuning in robotized interaction tasks.
Auton. Robots, 2021

A Model-Agnostic Algorithm for Bayes Error Determination in Binary Classification.
Algorithms, 2021

Sensorless Optimal Switching Impact/Force Controller.
IEEE Access, 2021

External Joint Torques Estimation for a Position-Controlled Manipulator Employing an Extended Kalman Filter.
Proceedings of the 18th International Conference on Ubiquitous Robots, 2021

Enhancing Object Detection Performance Through Sensor Pose Definition with Bayesian Optimization.
Proceedings of the IEEE International Workshop on Metrology for Industry 4.0 & IoT, 2021

Preferential Bayesian optimisation with skew gaussian processes.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Preference-based MPC calibration.
Proceedings of the 2021 European Control Conference, 2021

2020
Skew Gaussian processes for classification.
Mach. Learn., 2020

Robust state dependent Riccati equation variable impedance control for robotic force-tracking tasks.
Int. J. Intell. Robotics Appl., 2020

Finite-horizon integration for continuous-time identification: bias analysis and application to variable stiffness actuators.
Int. J. Control, 2020

Recursive Bias-Correction Method for Identification of Piecewise Affine Output-Error Models.
IEEE Control. Syst. Lett., 2020

Integrated Neural Networks for Nonlinear Continuous-Time System Identification.
IEEE Control. Syst. Lett., 2020

Torque Vectoring for High-Performance Electric Vehicles: An Efficient MPC Calibration.
IEEE Control. Syst. Lett., 2020

dynoNet: a neural network architecture for learning dynamical systems.
CoRR, 2020

Estimation of jump Box-Jenkins models.
Autom., 2020

Rao-Blackwellized sampling for batch and recursive Bayesian inference of Piecewise Affine models.
Autom., 2020

Sparse RKHS estimation via globally convex optimization and its application in LPV-IO identification.
Autom., 2020

One-Stage Auto-Tuning Procedure of Robot Dynamics and Control Parameters for Trajectory Tracking Applications.
Proceedings of the 17th International Conference on Ubiquitous Robots, 2020

Learning Continuous Control Actions for Robotic Grasping with Reinforcement Learning.
Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

Assembly Task Learning and Optimization through Human's Demonstration and Machine Learning.
Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

Interaction Force Computation Exploiting Environment Stiffness Estimation for Sensorless Robot Applications.
Proceedings of the 2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT, 2020

2019
Sum-of-squares for bounded rationality.
Int. J. Approx. Reason., 2019

An optimisation-based energy disaggregation algorithm for low frequency smart meter data.
Energy Inform., 2019

Performance-Oriented Model Learning for Data-Driven MPC Design.
IEEE Control. Syst. Lett., 2019

Model structures and fitting criteria for system identification with neural networks.
CoRR, 2019

Efficient Calibration of Embedded MPC.
CoRR, 2019

Active preference learning based on radial basis functions.
CoRR, 2019

Fostering the creation of a Digital Ecosystem by a distributed IEC-61499 based automation platform.
Proceedings of the 17th IEEE International Conference on Industrial Informatics, 2019

Semialgebraic Outer Approximations for Set-Valued Nonlinear Filtering.
Proceedings of the 17th European Control Conference, 2019

Kernelized Identification of Linear Parameter-Varying Models with Linear Fractional Representation.
Proceedings of the 17th European Control Conference, 2019

Maximum-a-posteriori estimation of jump Box-Jenkins models.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018
Direct Data-Driven Control of Constrained Systems.
IEEE Trans. Control. Syst. Technol., 2018

A bias-correction method for closed-loop identification of Linear Parameter-Varying systems.
Autom., 2018

Fitting jump models.
Autom., 2018

Towards direct data-driven model-free design of optimal controllers.
Proceedings of the 16th European Control Conference, 2018

Energy Disaggregation using Piecewise Affine Regression and Binary Quadratic Programming.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Prediction error methods in learning jump ARMAX models.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017
A Unified Framework for Deterministic and Probabilistic $\mathscr {D}$-Stability Analysis of Uncertain Polynomial Matrices.
IEEE Trans. Autom. Control., 2017

Regularized moving-horizon piecewise affine regression using mixed-integer quadratic programming.
Proceedings of the 25th Mediterranean Conference on Control and Automation, 2017

SOS for Bounded Rationality.
Proceedings of the Tenth International Symposium on Imprecise Probability: Theories and Applications, 2017

2016
Sparse Optimization for Automated Energy End Use Disaggregation.
IEEE Trans. Control. Syst. Technol., 2016

Computation of the Structured Singular Value via Moment LMI Relaxations.
IEEE Trans. Autom. Control., 2016

Direct learning of LPV controllers from data.
Autom., 2016

Piecewise affine regression via recursive multiple least squares and multicategory discrimination.
Autom., 2016

A probabilistic interpretation of set-membership filtering: Application to polynomial systems through polytopic bounding.
Autom., 2016

Regularized least square support vector machines for order and structure selection of LPV-ARX models.
Proceedings of the 15th European Control Conference, 2016

Identification of hybrid and linear parameter varying models via recursive piecewise affine regression and discrimination.
Proceedings of the 15th European Control Conference, 2016

Learning hybrid models with logical and continuous dynamics via multiclass linear separation.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

2015
Benefits and challenges of using smart meters for advancing residential water demand modeling and management: A review.
Environ. Model. Softw., 2015

A stochastic interpretation of set-membership filtering: application to polynomial systems through polytopic bounding.
CoRR, 2015

LPV system identification under noise corrupted scheduling and output signal observations.
Autom., 2015

An instrumental least squares support vector machine for nonlinear system identification.
Autom., 2015

2014
A Unified Framework for Solving a General Class of Conditional and Robust Set-Membership Estimation Problems.
IEEE Trans. Autom. Control., 2014

A bias-corrected estimator for nonlinear systems with output-error type model structures.
Autom., 2014

Shrinking complexity of scheduling dependencies in LS-SVM based LPV system identification.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

2013
Computational Load Reduction in Bounded Error Identification of Hammerstein Systems.
IEEE Trans. Autom. Control., 2013

Fixed-order FIR approximation of linear systems from quantized input and output data.
Syst. Control. Lett., 2013

An SDP approach for l<sub>0</sub>-minimization: Application to ARX model segmentation.
Autom., 2013

A convex relaxation approach to set-membership identification of LPV systems.
Autom., 2013

LPV model order selection in an LS-SVM setting.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Direct data-driven control of linear parameter-varying systems.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

2012
A convex relaxation approach to set-membership identification.
PhD thesis, 2012

Set-Membership Error-in-Variables Identification Through Convex Relaxation Techniques.
IEEE Trans. Autom. Control., 2012

Bounded error identification of Hammerstein systems through sparse polynomial optimization.
Autom., 2012

Fixed order LPV controller design for LPV models in input-output form.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

Polytopic outer approximations of semialgebraic sets.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

Minimal LPV state-space realization driven set-membership identification.
Proceedings of the American Control Conference, 2012

Robust pole placement for plants with semialgebraic parametric uncertainty.
Proceedings of the American Control Conference, 2012

2011
Enforcing stability constraints in set-membership identification of linear dynamic systems.
Autom., 2011

Set-membership LPV model identification of vehicle lateral dynamics.
Autom., 2011

Set-membership identification of Hammerstein-Wiener systems.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

Fast implementation of model predictive control with guaranteed performance.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

Hammerstein systems parameters bounding through sparse polynomial optimization.
Proceedings of the American Control Conference, 2011

Convex relaxation techniques for set-membership identification of LPV systems.
Proceedings of the American Control Conference, 2011

2010
Control as a key technology for a radical innovation in wind energy generation.
Proceedings of the American Control Conference, 2010

Set-membership EIV identification through LMI relaxation techniques.
Proceedings of the American Control Conference, 2010

Bounding the parameters of linear systems with stability constraints.
Proceedings of the American Control Conference, 2010

2009
Set-membership identification of block-structured nonlinear feedback systems.
Proceedings of the 48th IEEE Conference on Decision and Control, 2009


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