The Machine Learning “Advent Calendar” Day 13: LASSO and Ridge Regression in Excel
Ridge and Lasso regression are often perceived as more complex versions of linear regression. In reality, the prediction model remains exactly the same. What ch...
Ridge and Lasso regression are often perceived as more complex versions of linear regression. In reality, the prediction model remains exactly the same. What ch...
Article URL: https://www.wbur.org/hereandnow/2025/12/09/nuclear-power-ai Comments URL: https://news.ycombinator.com/item?id=46254276 Points: 4 Comments: 0...
Accurate volatility forecasting is essential in banking, investment, and risk management, because expectations about future market movements directly influence ...
We present Particulate, a feed-forward approach that, given a single static 3D mesh of an everyday object, directly infers all attributes of the underlying arti...
Many systems exhibit complex interactions between their components: some features or actions amplify each other's effects, others provide redundant information,...
Small Wins Woke up at 11 AM instead of my usual 12. An hour earlier. Yeah, I'm counting that as progress because when you're trying to fix your sleep schedule,...
Softmax attention is a central component of transformer architectures, yet its nonlinear structure poses significant challenges for theoretical analysis. We dev...
Small Wins - Woke up at 11 AM instead of my usual 12 AM. An hour earlier—counting that as progress while fixing my sleep schedule. - Did a revision problem on...
The rapid deployment of Large Language Models (LLMs) has created an urgent need for enhanced security and privacy measures in Machine Learning (ML). LLMs are in...
Through multi-agent competition and the sparse high-level objective of winning a race, we find that both agile flight (e.g., high-speed motion pushing the platf...
Evaluating conditional coverage remains one of the most persistent challenges in assessing the reliability of predictive systems. Although conformal methods can...
Coordinate-based neural networks have emerged as a powerful tool for representing continuous physical fields, yet they face two fundamental pathologies: spectra...