Publications related to Computational complexity theory

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

A Streamline Upwind Petrov-Galerkin Reduced Order Method for Advection-Dominated Partial Differential Equations Under Optimal Control

Fabio Zoccolan, Gianluigi Rozza

In this paper we will consider distributed Linear-Quadratic Optimal Control Problems dealing with Advection-Diffusion PDEs for high values of the Peclet number. In this situation, computational instabilities occur, both for steady and unsteady cases. A Str ...

Walter De Gruyter Gmbh2024

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

FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems

David Atienza Alonso, Amir Aminifar, Alireza Amirshahi, José Angel Miranda Calero, Jonathan Dan

The rapid development of wearable biomedical systems now enables real-time monitoring of electroencephalography (EEG) signals. Acquisition of these signals relies on electrodes. These systems must meet the design challenge of selecting an optimal set of el ...

2024

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

Aude Billard, Mikhail Koptev, Nadia Barbara Figueroa Fernandez

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

Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistency

Jean-Philippe Thiran, Tobias Kober, Bénédicte Marie Maréchal, Jonas Richiardi

With the rise of open data, identifiability of individuals based on 3D renderings obtained from routine structural magnetic resonance imaging (MRI) scans of the head has become a growing privacy concern. To protect subject privacy, several algorithms have ...

Wiley2024

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

Paul Scharnhorst

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

Hybrid ground-state quantum algorithms based on neural Schrödinger forging

Giuseppe Carleo, Sofia Vallecorsa

Entanglement forging based variational algorithms leverage the bipartition of quantum systems for addressing ground-state problems. The primary limitation of these approaches lies in the exponential summation required over the numerous potential basis stat ...

Amer Physical Soc2024

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

Energy Management of Price-Maker Community Energy Storage by Stochastic Dynamic Programming

Tianshu Yang, Xue Zhang

In this paper, we propose an analytical stochastic dynamic programming (SDP) algorithm to address the optimal management problem of price-maker community energy storage. As a price-maker, energy storage smooths price differences, thus decreasing energy arb ...

China Electric Power Research Inst2024

Computational complexity theory

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

A Streamline Upwind Petrov-Galerkin Reduced Order Method for Advection-Dominated Partial Differential Equations Under Optimal Control

Efficient Continual Finite-Sum Minimization

FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems

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

Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistency

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

Hybrid ground-state quantum algorithms based on neural Schrödinger forging

Inhalation of Microplastics—A Toxicological Complexity

Energy Management of Price-Maker Community Energy Storage by Stochastic Dynamic Programming

Efficient Continual Finite-Sum Minimization

Energy Management of Price-Maker Community Energy Storage by Stochastic Dynamic Programming

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

Inhalation of Microplastics—A Toxicological Complexity

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

A Streamline Upwind Petrov-Galerkin Reduced Order Method for Advection-Dominated Partial Differential Equations Under Optimal Control

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

FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems

Hybrid ground-state quantum algorithms based on neural Schrödinger forging

Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistency