Essays about: "on training importance"
Showing result 1 - 5 of 369 essays containing the words on training importance.
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1. Cross project Just-In-Time bug detection
University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)Abstract : Software is present in almost all aspects of our lives, and with more parts of life beingdriven by code, the importance of limiting bugs is critical. Studies have shown that thelonger a bug is present in a system increases the complexity of finding and handlingthe bug. READ MORE
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2. Using Synthetic Data For Object Detection on the edge in Hazardous Environments
University essay from Lunds universitet/Institutionen för reglerteknikAbstract : This thesis aims to evaluate which aspects are important when generating synthetic data with the purpose of running on a lightweight object detection model on an edge device. The task we constructed was to detect Canisters and whether they feature a protective valve called a Cap or not (called a No-Cap). READ MORE
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3. Attack Strategies in Federated Learning for Regression Models : A Comparative Analysis with Classification Models
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : Federated Learning (FL) has emerged as a promising approach for decentralized model training across multiple devices, while still preserving data privacy. Previous research has predominantly concentrated on classification tasks in FL settings, leaving a noticeable gap in FL research specifically for regression models. READ MORE
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4. Self-Supervised Learning for Tabular Data: Analysing VIME and introducing Mix Encoder
University essay from Lunds universitet/Fysiska institutionenAbstract : We introduce Mix Encoder, a novel self-supervised learning framework for deep tabular data models based on Mixup [1]. Mix Encoder uses linear interpolations of samples with associated pretext tasks to form useful pre-trained representations. READ MORE
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5. Measuring the Utility of Synthetic Data : An Empirical Evaluation of Population Fidelity Measures as Indicators of Synthetic Data Utility in Classification Tasks
University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)Abstract : In the era of data-driven decision-making and innovation, synthetic data serves as a promising tool that bridges the need for vast datasets in machine learning (ML) and the imperative necessity of data privacy. By simulating real-world data while preserving privacy, synthetic data generators have become more prevalent instruments in AI and ML development. READ MORE
