Essays about: "training impact"
Showing result 1 - 5 of 490 essays containing the words training impact.
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1. "The Uphill AI Contract Challenge The Intra-Active Task: Reimagining Contracts"
University essay from Göteborgs universitet/Juridiska institutionenAbstract : The traditional contract theories are insufficient to handle the challenges Artificial Intelligence (AI) is currently causing and will continue to cause to contract law. These challenges involve problems concerning the subject/object divide, agency, the embedding of legal code into interactive programming code, and ethical aspects concerning the transfer of power away from lawyers. READ MORE
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2. 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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3. Effect of training and feeding on saliva concentrations of cartilage oligomeric matrix protein neo-epitope (COMP664) and neuropeptide Substance P in horses
University essay from SLU/Dept. of Biomedical Sciences and Veterinary Public HealthAbstract : Osteoarthritis (OA) is a low-grade inflammatory disease associated with subsequent lameness and chronic joint pain. Lameness caused by degenerative joint disorders is perceived as one of the most common clinical problems for the equine athlete, advocating the severity of OA as a welfare and clinical issue. 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. AI-based image generation: The impact of fine-tuning on fake image detection
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Machine learning-based image generation models such as Stable Diffusion are now capable of generating synthetic images that are difficult to distinguish from real images, which gives rise to a number of legal and ethical concerns. As a potential measure of mitigation, it is possible to train neural networks to detect the digital artifacts present in the images synthesized by many generative models. READ MORE
