Publications related to Optimization Methodology of Dynamic Data Structures Based on Genetic Algorithms for Multimedia Embedded Systems

Related publications (34)

SideDRAM: Integrating SoftSIMD Datapaths near DRAM Banks for Energy-Efficient Variable Precision Computation

David Atienza Alonso, Giovanni Ansaloni, Marina Zapater Sancho, Alexandre Sébastien Julien Levisse, Rafael Medina Morillas, Pengbo Yu

By interfacing computing logic directly to the DRAM banks, bank-level Compute-near-Memory (CnM) architectures promise to mitigate the bottleneck at the memory interconnect. While this computation paradigm heavily reduces the energy requirements for data mo ...

ACM2025

From Preprocessing to Evaluation: The Role of External Knowledge in Advancing Language Models and Machine Translation

Georgios Vernikos

Machine translation (MT) systems and language models (LMs) have demonstrated impressive performance in recent years, driven by advances in architecture, algorithms, and the scaling of parameters and training data. Despite the ability of these models to int ...

EPFL2025

Scaling the Modalities in Multimodal Foundation Models

Oguzhan Fatih Kar

Having a single neural network to handle a wide and varied range of tasks and modalities has been a long-standing goal. Such a model brings notable advantages, such as test-time computational efficiency, modality fusion, and reduced model size. Our goal in ...

EPFL2025

Automated Formal Verification of Software Network Functions

Solal Vincenzo Pirelli

Formally verifying the correctness of software is necessary to merit the trust people put in software systems. Currently, formal verification requires human effort to prove that a piece of code matches its specification and code changes to improve verifiab ...

EPFL2024

A ride time-oriented scheduling algorithm for dial-a-ride problems

Nikolaos Geroliminis, Claudia Bongiovanni, Mor Kaspi

This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). The scheduling heuristic, based on linear programming theor ...

Pergamon-Elsevier Science Ltd2024

Data from: Optimal blade pitch control for enhanced vertical-axis wind turbine performance

Karen Ann J Mulleners, Sébastien Le Fouest

This directory contains open-source data obtained using a single-bladed H-type vertical-axis wind turbine prototype with individual blade pitching. This data results from the optimisation of the blade's pitching kinematics using a genetic algorithm at two ...

Zenodo2024

On the Effect of Initialization: The Scaling Path of 2-Layer Neural Networks

Michaël Unser, Sebastian Jonas Neumayer, Lénaïc Chizat

In supervised learning, the regularization path is sometimes used as a convenient theoretical proxy for the optimization path of gradient descent initialized from zero. In this paper, we study a modification of the regularization path for infinite-width 2- ...

2024

Scalable constrained optimization

Maria-Luiza Vladarean

Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

EPFL2024

Contemporary Logic Synthesis: with an Application to AQFP Circuit Optimization

Siang-Yun Lee

Electronic devices play an irreplaceable role in our lives. With the tightening time to market, exploding demand for computing power, and continuous desire for smaller, faster, less energy-consuming, and lower-cost chips, computer-aided design for electron ...

EPFL2024

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

Philippe Schwaller, Jeff Guo

Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy a desired objective under minimal calls to oracles (computational property predictors). This problem becomes more apparen ...

Amer Chemical Soc2024

DiffAirfoil: An Efficient Novel Airfoil Sampler Based on Latent Space Diffusion Model for Aerodynamic Shape Optimization

Edouard Robert Albert Patrick Dufour, Colin Pelletier, Pascal Fua, Zhen Wei

Surrogate-based optimization is widely used for aerodynamic shape optimization, and its effectiveness depends on representative sampling of the design space. However, traditional sampling methods are hard-pressed to effectively sample high-dimensional desi ...

2024

Design and in vitro Characterization of a Wearable Multisensing System for Hydration Monitoring

Ali Meimandi, Sandro Carrara, Ata Jedari Golparvar, Sarah Tonello

Dehydration is a frequent condition in the elderly and can lead to serious health complications if not compensated timely. Early diagnosis can be problematic, as medical examinations in the hospital would be needed. Fully wearable low-cost multisensing dev ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Mesh-based topology, shape and sizing optimization of ribbed plates

Ahmad Abdulrahman Ahmad Majdouba

In this paper, we present a new parameterization and optimization procedure for minimizing the weight of ribbed plates. The primary goal is to reduce embodied CO2 in concrete floors as part of the effort to diminish the carbon footprint of the construction ...

Springer2024

COMMUNICATION LOWER BOUNDS AND OPTIMAL ALGORITHMS FOR MULTIPLE TENSOR-TIMES-MATRIX COMPUTATION

Laura Grigori

Multiple tensor-times-matrix (Multi-TTM) is a key computation in algorithms for computing and operating with the Tucker tensor decomposition, which is frequently used in multidimensional data analysis. We establish communication lower bounds that determine ...

Siam Publications2024

Creating the conditions for Western European petroculture: The Marshall Plan, the politics of the OEEC, and the transition from coal to oil

Nicolas Christophe Chachereau

In the postwar years, petroleum products pervaded more and more aspects of Western European life. In this article, we study the origins of this pervasive petroculture through the lens of the Marshall Plan/European Recovery Program (ERP), its Refinery Expan ...

2023

A combined genetic algorithm and active learning approach to build and test surrogate models in Process Systems Engineering

François Maréchal, Julia Granacher

In Process Systems Engineering, computationally-demanding models are frequent and plentiful. Handling such complexity in an optimization framework in a fast and reliable way is essential, not only for generating meaningful solutions but also for providing ...

Pergamon-Elsevier Science Ltd2023

Universal and adaptive methods for robust stochastic optimization

Ali Kavis

Within the context of contemporary machine learning problems, efficiency of optimization process depends on the properties of the model and the nature of the data available, which poses a significant problem as the complexity of either increases ad infinit ...

EPFL2023

Genetic Algorithms for the Discovery of Homogeneous Catalysts

Anne-Clémence Corminboeuf, Rubén Laplaza Solanas, Simone Gallarati, Puck Elisabeth van Gerwen, Alexandre Alain Schöpfer

In this account, we discuss the use of genetic algorithms in the inverse design process of homogeneous catalysts for chemical transformations. We describe the main components of evolutionary experiments, specifically the nature of the fitness function to o ...

2023

The importance of young professionals for dam engineering in Switzerland

Valentina Favero, Samuel Luke Vorlet

In Switzerland, hydropower is the main energy source and contributes to about 58.3% of the total production. The 2050 energy strategy aims to increase this share in the coming decades. This increase is a challenge for hydropower plants. The maintenance and ...

CRC Press/Balkema2023

Fast correlation function calculator A high-performance pair-counting toolkit

Cheng Zhao

Context. A novel high-performance exact pair-counting toolkit called fast correlation function calculator (FCFC) is presented.Aims. With the rapid growth of modern cosmological datasets, the evaluation of correlation functions with observational and simula ...

EDP SCIENCES S A2023