Search Results - Computing methodologies Machine learning Machine learning approaches Kernel methods*

A Kernel-based Machine Learning Approach to Computing Quasiparticle Energies within Many-Body Green's Functions Theory by Tirimbó, Gianluca, Çaylak, Onur, Baumeier, Björn

“…We present a Kernel Ridge Regression (KRR) based supervised learning method combined with Genetic Algorithms (GAs…”
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MAGIKA: AI-Powered Content-Type Detection by Fratantonio, Yanick, Invernizzi, Luca, Farah, Loua, Thomas, Kurt, Zhang, Marina, Albertini, Ange, Galilee, Francois, Metitieri, Giancarlo, Cretin, Julien, Petit-Bianco, Alex, Tao, David, Bursztein, Elie

“… Under the hood, Magika employs a deep learning model that can execute on a single CPU with just 1MB of memory to store the model's weights…”
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Finding Ethereum Smart Contracts Security Issues by Comparing History Versions by Chen, Jiachi

“… In this paper, we propose a deep learning-based method to find security issues of Ethereum smart contracts by finding the updated version of a destructed contract…”
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When Less is Enough: Positive and Unlabeled Learning Model for Vulnerability Detection by Wen, Xin-Cheng, Wang, Xinchen, Gao, Cuiyun, Wang, Shaohua, Liu, Yang, Gu, Zhaoquan

“…Automated code vulnerability detection has gained increasing attention in recent years. The deep learning (DL…”
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LA-MTL: Latency-Aware Automated Multi-Task Learning by Sampath, Shambhavi Balamuthu, Sawani, Sami, Thoma, Moritz, Frickenstein, Lukas, Mori, Pierpaolo, Fasfous, Nael, Vemparala, Manoj Rohit, Frickenstein, Alexander, Schlichtmann, Ulf, Passerone, Claudio, Stechele, Walter

“…Multi-Task Learning (MTL) aims to unify a variety of tasks into a single network for improved training and inference efficiency…”
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Application of Support Vector Machine Classification Model to Identification of Vascular Endothelial Growth Factor Receptor Inhibitors by Arabi, Nooshin, Torabi, Mohammad Reza, Ghasemi, Fahimeh

“… In order to apply the machine learning model, biological compounds were extracted from the BindingDB database…”
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Function-Level Vulnerability Detection Through Fusing Multi-Modal Knowledge by Ni, Chao, Guo, Xinrong, Zhu, Yan, Xu, Xiaodan, Yang, Xiaohu

“…Software vulnerabilities damage the functionality of software systems. Recently, many deep learning-based approaches have been proposed to detect vulnerabilities at the function level by using one or a few different modalities (e.g…”
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Scalable Industrial Control System Analysis via XAI-Based Gray-Box Fuzzing by Kur, Justin, Chen, Jingshu, Huang, Jun

“… To address these limitations, we propose XAI-based gray-box fuzzing, a novel approach that leverages explainable AI and machine learning modeling of ICS to accurately identify a small set…”
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Semantic Segmentation of Geometric Primitives in Dense 3D Point Clouds by Stanescu, Ana, Fleck, Philipp, Schmalstieg, Dieter, Arth, Clemens

“… The core contribution is an efficient method for fitting of geometric primitives based on machine learning…”
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Combining heterogeneous data sources for neuroimaging based diagnosis: re-weighting and selecting what is important by Donini, Michele, Monteiro, João M., Pontil, Massimiliano, Hahn, Tim, Fallgatter, Andreas J., Shawe-Taylor, John, Mourão-Miranda, Janaina

“… In this paper, we proposed a framework based on a recent multiple kernel learning algorithm called EasyMKL and we investigated the benefits of this approach for diagnosing two different mental health diseases…”
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MCBound: An Online Framework to Characterize and Classify Memory/Compute-bound HPC Jobs by Antici, Francesco, Bartolini, Andrea, Kiziltan, Zeynep, Babaoglu, Ozalp, Kodama, Yuetsu

“…Modern High-Performance Computing (HPC) systems play a fundamental role in driving scientific research, as they execute computationally intensive jobs originating from diverse domains…”
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Optimizing Uncertainty Estimation on Scientific Visualizations Using Learning Models by Almeida, Clara J., Guerrero-Pantoja, David, Pautsch, Erik, Rizzi, Silvio, Thiruvathukal, George K., Pantoja, Maria

“… In recent years, machine learning, particularly Deep Learning (DL), has driven significant advancements in SciVis…”
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Using Static Analysis to Aid Monolith to Microservice System Transformation: Tuning Fuzzy c-Means in a VAE-Based GNN Approach by Sooksatra, Korn, Hossain Chy, Md Showkat, Arju, Md Ashfakur Rahman, Cerny, Tomas, Rivas, Pablo

“… This paper explores a machine learning-driven approach to decompose monolithic systems into microservices, targeting maintainability and modularization…”
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hws: A Tool for Monitoring Hardware Metrics Across Diverse Vendors: A Case Study on Hyperparameter Optimization Algorithms by Breyer, Marcel, Van Craen, Alexander, Domanski, Peter, Pfluger, Dirk

“…Due to modern hardware's constantly growing energy demands, it is important to consider energy efficiency and power consumption. Especially in the age of AI,…”
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Geometry-oblivious FMM for compressing dense SPD matrices by Yu, Chenhan D., Levitt, James, Reiz, Severin, Biros, George

“…We present GOFMM (geometry-oblivious FMM), a novel method that creates a hierarchical low-rank approximation, or "compression," of an arbitrary dense symmetric…”
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Identifying On-time Reward Delivery Projects with Estimating Delivery Duration on Kickstarter by Tran, Thanh, Lee, Kyumin, Vo, Nguyen, Choi, Hongkyu

“…In Crowdfunding platforms, people turn their prototype ideas into real products by raising money from the crowd, or invest in someone else's projects. In…”
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On Multiscale and Statistical Numerical Methods for PDEs and Inverse Problems by Chen, Yifan

“…This thesis is about numerical methods for scientific computing and scientific machine learning, with a focus on solving partial differential equations (PDEs…”
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