Tag: stat_ml
Self-study and thoughts on statistics and machine learning
- What FDR control doesn't do (20 Apr 2023)
- Neural Network Checklist (09 Feb 2023)
- Differential expression for newcomers (14 Aug 2022)
- You can't construct confidence intervals near a region of non-identifiability (20 Jun 2022)
- You can't test for independence conditional on a quantitative random variable. (20 Jun 2022)
- You can't estimate the mean. (20 Jun 2022)
- You can't satisfy three simple desiderata for a clustering algorithm. (20 Jun 2022)
- You can't achieve optimal inference and optimal prediction simultaneously. (20 Jun 2022)
- Five disturbing impossibility theorems (20 Jun 2022)
- A third miracle of modern frequentist statistics (15 Jun 2022)
- A second miracle of modern frequentist statistics (15 Jun 2022)
- A miracle of modern frequentist statistics (15 Jun 2022)
- A fourth miracle of modern frequentist statistics (15 Jun 2022)
- Lazy matrix evaluation saves RAM in common analyses (28 Nov 2020)
- Kalman Filter Cheat Sheet (30 Aug 2020)
- Experiments with one control and $k$ treatments have highest power when the control arm is $\sqrt k$ times bigger than each individual treatment arm (21 Aug 2020)
- Favorite machine learning papers (resnets) (21 Jul 2019)
- I don't want to be afraid of neural networks anymore (06 Jul 2019)
- We want R functions for gradients and hessians (12 Jan 2019)