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Policy Gradient Algorithms for Robust MDPs with Non-Rectangular Uncertainty Sets

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A novel approach for robust controller synthesis, which models uncertainty as an elliptical set, is proposed in the paper. Given a set of frequency response functions of linear time-invariant (LTI) multiple-input multiple-output (MIMO) systems, the approac ...

2023

Probabilistic methods for neural combinatorial optimization

Nikolaos Karalias

The monumental progress in the development of machine learning models has led to a plethora of applications with transformative effects in engineering and science. This has also turned the attention of the research community towards the pursuit of construc ...

EPFL2023

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The decentralisation and unpredictability of new renewable energy sources require rethinking our energy system. Data-driven approaches, such as reinforcement learning (RL), have emerged as new control strategies for operating these systems, but they have n ...

2023

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Modern machine learning (ML) models are capable of impressive performances. However, their prowess is not due only to the improvements in their architecture and training algorithms but also to a drastic increase in computational power used to train them.|S ...

New York2023

Predicting in Uncertain Environments: Methods for Robust Machine Learning

Paul Thierry Yves Rolland

One of the main goal of Artificial Intelligence is to develop models capable of providing valuable predictions in real-world environments. In particular, Machine Learning (ML) seeks to design such models by learning from examples coming from this same envi ...

EPFL2022

Auto-tuning deep forest for shear stiffness prediction of headed stud connectors

Xianlin Wang, Yuqing Liu

The shear stiffness of headed stud connector is a critical parameter for the calculation of deflection and inter-facial shear force for steel-concrete composite structure. Thus, this study presented a promising data-driven model auto-tuning Deep Forest (AT ...

2022

Is there a relationship between footstep-impact locations and measured signal characteristics?

Ian Smith, Yves Sylvain Gilles Reuland, Sai Ganesh Sarvotham Pai, Slah Drira

Building utilization can be enhanced by tracking occupants. Non-intrusive tracking of occupants using floor-vibration measurements is beneficial for many smart-building applications such as energy consumption, security enhancement, and care-giving. Also, u ...

ACM2019

Comparison of data interpretation methodologies for geotechnical back analysis

Ian Smith

Rigorous back analysis plays a major role in providing information to engineers for better decision-making. Most research on this topic has focused on optimization techniques. Comparative studies of data interpretation methodologies have seldom been report ...

2019

Scalable Convex Optimization Methods for Semidefinite Programming

Alp Yurtsever

With the ever-growing data sizes along with the increasing complexity of the modern problem formulations, contemporary applications in science and engineering impose heavy computational and storage burdens on the optimization algorithms. As a result, there ...

EPFL2019

Using Uncertainty Data in Chance-Constrained Trajectory Planning

Maryam Kamgarpour

We consider the problem of trajectory planning in an environment comprised of a set of obstacles with uncertain locations. While previous approaches model the uncertainties with a prescribed Gaussian distribution, we consider the realistic case in which th ...

IEEE2019