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Optimization of the MOVA Undeniable Signature Scheme

Publications associées (30)

Quality-Constrained Encoding Optimization for Omnidirectional Video Streaming

Pascal Frossard, Roberto Gerson De Albuquerque Azevedo, Chaofan He

Omnidirectional video streaming is usually implemented based on the representations of tiles, where the tiles are obtained by splitting the video frame into several rectangular areas and each tile is converted into multiple representations with different r ...

Ieee-Inst Electrical Electronics Engineers Inc2023

Power Transformer Fault Diagnosis Using Neural Network Optimization Techniques

Dimitrios Kaminaris

Artificial Intelligence (AI) techniques are considered the most advanced approaches for diagnosing faults in power transformers. Dissolved Gas Analysis (DGA) is the conventional approach widely adopted for diagnosing incipient faults in power transformers. ...

MDPI2023

Computational conceptual design — typological exploration of spatial truss systems through optimization

Corentin Jean Dominique Fivet, Jonas Warmuth, Pierluigi D'Acunto

Exploring a wide range of design options is crucial for every sound conceptual design process. In the conventional structural design workflow, optimization techniques are generally employed to generate well-performing design options. However, focusing only ...

International Association for Shell and Spatial Structures (IASS)2023

Robust Design of Herringbone Grooved Journal Bearings using Multi-Objective Optimization with Artificial Neural Networks

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Herringbone grooved journal bearings (HGJBs) are widely used in micro-turbocompressor applications due to their high load-carrying capacity, low friction, and oil-free solution. However, the performance of these bearings is sensitive to manufacturing devia ...

Amer Soc Mechanical Engineers2023

Robust Design of Herringbone Grooved Journal Bearings using Multi-Objective Optimization with Artificial Neural Networks

Jürg Alexander Schiffmann, Soheyl Massoudi

2023

MOD2IR: High-Performance Code Generation for a Biophysically Detailed Neuronal Simulation DSL

Felix Schürmann, Pramod Shivaji Kumbhar, Snehal Pramod Kumbhar, Omar Awile, Ioannis Magkanaris

Advances in computational capabilities and large volumes of experimental data have established computer simulations of brain tissue models as an important pillar in modern neuroscience. Alongside, a variety of domain specific languages (DSLs) have been dev ...

ACM2023

Novel Ordering-based Approaches for Causal Structure Learning in the Presence of Unobserved Variables

We propose ordering-based approaches for learning the maximal ancestral graph (MAG) of a structural equation model (SEM) up to its Markov equivalence class (MEC) in the presence of unobserved variables. Existing ordering-based methods in the literature rec ...

Association for the Advancement of Artificial Intelligence (AAAI)2023

Universal and adaptive methods for robust stochastic optimization

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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

Beyond Spectral Gap: The Role of the Topology in Decentralized Learning

Thijs Vogels, Hadrien Hendrikx, Martin Jaggi

In data-parallel optimization of machine learning models, workers collaborate to improve their estimates of the model: more accurate gradients allow them to use larger learning rates and optimize faster. In the decentralized setting, in which workers commu ...

Microtome Publishing2023

Learning and optimization of anticipatory feedback controllers for robot manipulation

Hakan Girgin

Programming intelligent robots requires robust controllers that can achieve desired tasks while adapting to the changes in the task and the environment. In this thesis, we address the challenges in designing such adaptive and anticipatory feedback controll ...

EPFL2023