Methodology
2026
10
- From LSH to K-Center Greedy: Semantic Embeddings for Deduplication, Cleaning, and Sample Selection
- Why Better Simulators Often Combine Learning and Rules: From PDEs and Ray Tracing to DLSS
- Training with Imbalanced Samples: From Statistical Learning to Long-Tail Learning
- From Bagging to Stacking: Notes on Ensemble Learning
- Spatial Data Analysis
- Shapley and SHAP: State-of-the-Art Tools for Model Interpretability
- Why Data Keeps Fooling You: The Counterintuitive Inspection Paradox
- Zipf's Law: From the Voynich Manuscript to Alien Civilizations
- How to Share Data with a Statistician
- The Computational Revolution in Statistical Inference: Jackknife, Bootstrap, and Subsampling