Publications related to Classification of chaotic sequences with open-loop estimator - Optimal design for noisy environments

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Efficient Continual Finite-Sum Minimization

Volkan Cevher, Efstratios Panteleimon Skoulakis, Leello Tadesse Dadi

Given a sequence of functions

f_1,\ldots,f_n

with

f_i:\mathcal{D}\mapsto \mathbb{R}

, finite-sum minimization seeks a point

{x}^\star \in \mathcal{D}

minimizing

\sum_{j=1}^nf_j(x)/n

. In this work, we propose a key twist into the finite-sum minimizat ...

2024

Additive and geometric transversality of fractal sets in the integers

Florian Karl Richter

By juxtaposing ideas from fractal geometry and dynamical systems, Furstenberg proposed a series of conjectures in the late 1960's that explore the relationship between digit expansions with respect to multiplicatively independent bases. In this work, we in ...

2024

Inhalation of Microplastics—A Toxicological Complexity

Florian Frédéric Vincent Breider, Myriam Borgatta

Humans are chronically exposed to airborne microplastics (MPs) by inhalation. Various types of polymer particles have been detected in lung samples, which could pose a threat to human health. Inhalation toxicological studies are crucial for assessing the e ...

2024

Reactive collision-free motion generation in joint space via dynamical systems and sampling-based MPC

Aude Billard, Nadia Barbara Figueroa Fernandez, Mikhail Koptev

Dynamical system (DS) based motion planning offers collision-free motion, with closed-loop reactivity thanks to their analytical expression. It ensures that obstacles are not penetrated by reshaping a nominal DS through matrix modulation, which is construc ...

Sage Publications Ltd2024

Energy-Efficient Frequency Selection Method for Bio-Signal Acquisition in AI/ML Wearables

David Atienza Alonso, Miguel Peon Quiros, José Angel Miranda Calero, Hossein Taji

In wearable sensors, energy efficiency is crucial, particularly during phases where devices are not processing, but rather acquiring biosignals for subsequent analysis. This study focuses on improving the power consumption of wearables during these acquisi ...

2024

On-Chip Fully Reconfigurable Artificial Neural Network in 16 nm FinFET for Positron Emission Tomography

Edoardo Charbon, Claudio Bruschini, Emanuele Ripiccini, Andrada Alexandra Muntean

Smarty is a fully-reconfigurable on-chip feed-forward artificial neural network (ANN) with ten integrated time-to-digital converters (TDCs) designed in a 16 nm FinFET CMOS technology node. The integration of TDCs together with an ANN aims to reduce system ...

Piscataway2024

Graph generative deep learning models with an application to circuit topologies

Igor Krawczuk

Modern integrated circuits are tiny yet incredibly complex technological artifacts, composed of millions and billions of individual structures working in unison.Managing their complexity and facilitating their design drove part of the co-evolution of moder ...

EPFL2024

Reliable data-driven decision-making through optimal transport

Bahar Taskesen

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks the ...

EPFL2024

A Comparative Analysis of Tools & Task Types for Measuring Computational Problem-Solving

Richard Lee Davis, Engin Walter Bumbacher, Jérôme Guillaume Brender

How to measure students' Computational Problem-Solving (CPS) competencies is an ongoing research topic. Prevalent approaches vary by measurement tools (e.g., interactive programming, multiple-choice tests, or programming-independent tests) and task types ( ...

Association for Computing Machinery2024

Classification of chaotic sequences with open-loop estimator - Optimal design for noisy environments

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Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Efficient Continual Finite-Sum Minimization

Additive and geometric transversality of fractal sets in the integers

Inhalation of Microplastics—A Toxicological Complexity

Reactive collision-free motion generation in joint space via dynamical systems and sampling-based MPC

Energy-Efficient Frequency Selection Method for Bio-Signal Acquisition in AI/ML Wearables

On-Chip Fully Reconfigurable Artificial Neural Network in 16 nm FinFET for Positron Emission Tomography

Graph generative deep learning models with an application to circuit topologies

Reliable data-driven decision-making through optimal transport

A Comparative Analysis of Tools & Task Types for Measuring Computational Problem-Solving

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Efficient Continual Finite-Sum Minimization

Reactive collision-free motion generation in joint space via dynamical systems and sampling-based MPC

Energy-Efficient Frequency Selection Method for Bio-Signal Acquisition in AI/ML Wearables

Graph generative deep learning models with an application to circuit topologies

Reliable data-driven decision-making through optimal transport

Additive and geometric transversality of fractal sets in the integers

Inhalation of Microplastics—A Toxicological Complexity

On-Chip Fully Reconfigurable Artificial Neural Network in 16 nm FinFET for Positron Emission Tomography

A Comparative Analysis of Tools & Task Types for Measuring Computational Problem-Solving