An introduction to program synthesis (Part II) - Automatically generating features for machine learning
🤖Machine Learning
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DS-STAR: A state-of-the-art versatile data science agent
research.google·14h
📊Data Science
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Towards Humanist Superintelligence
🤖AI
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TIL about Model Collapse. When an AI learns from other AI generated content, errors can accumulate, like making a photocopy of a photocopy over and over again.
🤖Machine Learning
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Essential Chunking Techniques for Building Better LLM Applications
machinelearningmastery.com·21h
📈Optimization
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AI Turns Brain Scans Into Full Sentences and It’s Eerie To Say The Least
zmescience.com·17h
🤖AI
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Building Data Pipelines That Keep GPUs Fed During LLM Training
pub.towardsai.net·10h
🔬Julia Language
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Plush neuron makes AI approachable, simplifies neural networks for middle schoolers
phys.org·7h
🤖AI
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Observer-based neural networks for flow estimation and control
arxiv.org·1d
👁️Computer Vision
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Algorithmic Fairness Auditing via Dynamic Contrastive Learning in Personalized Recommendation Systems
🤖Machine Learning
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Colorectal Cancer Histopathological Grading using Multi-Scale Federated Learning
arxiv.org·1d
🤖Machine Learning
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Alleviating Hyperparameter-Tuning Burden in SVM Classifiers for Pulmonary Nodules Diagnosis with Multi-Task Bayesian Optimization
arxiv.org·1d
👁️Computer Vision
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Generative Artificial Intelligence in Bioinformatics: A Systematic Review of Models, Applications, and Methodological Advances
arxiv.org·1d
🤖AI
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Towards Transparent Stance Detection: A Zero-Shot Approach Using Implicit and Explicit Interpretability
arxiv.org·1d
🤖Machine Learning
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Structural Priors and Modular Adapters in the Composable Fine-Tuning Algorithm of Large-Scale Models
arxiv.org·3h
📈Optimization
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Hemorica: A Comprehensive CT Scan Dataset for Automated Brain Hemorrhage Classification, Segmentation, and Detection
arxiv.org·3h
👁️Computer Vision
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A Quantized VAE-MLP Botnet Detection Model: A Systematic Evaluation of Quantization-Aware Training and Post-Training Quantization Strategies
arxiv.org·1d
🤖Machine Learning
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Beyond Standard LLMs
🤖Machine Learning
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