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ML/Statistics

A collection of 151 issues

The Welfare Costs of Low-Friction Idea Production

Humans are naturally curious, and curiosity often takes us into domains where our understanding is shallow. Large language models (LLMs) have radically lowered the marginal cost of experimentation in such domains. Minutes of prompting can yield a plausible business strategy, technical architecture, or research framework—outputs that look like the

When OLS and SUR Disagree

Under Zellner’s classical SUR assumptions—the same regressors in each equation and a common sample of observations—OLS and SUR produce the same coefficient estimates, but SUR yields smaller standard errors. Differences in coefficients appear in practice for good and bad reasons: Efficient, “good” differences arise from intentional GLS

Take 80 mg Atorvastatin for Myalgia

Here’s a drug pamphlet with a table about side effects The same table can be found here: https://www.rxlist.com/lipitor-drug.htm#side_effects As you can see, for a range of conditions, the rate at which patients experience side effects is greater in the Placebo arm than

A Benchmark For Benchmarks

Benchmark datasets like MNIST, ImageNet, etc., abound in machine learning. Such datasets stimulate work on a problem by providing an agreed-upon mark to beat. Many of the benchmark datasets, however, are constructed in an ad hoc manner. As a result, it is hard to understand why the best-performing models vary

Smallest Loss That Compute Can Buy

With Chris Alexiuk and Atul Dhingra The most expensive portion of model training today is GPU time. Given that, it is useful to ask what is the best way to spend the compute budget. More formally, the optimization problem is: minimize test loss given a FLOPs budget. To achieve the

Out of Network: The Tradeoffs in Using Network Based Targeting

In particular, in 521 villages in Haryana, we provided information on monthly immunization camps to either randomly selected individuals (in some villages) or to individuals nominated by villagers as people who would be good at transmitting information (in other villages). We find that the number of children vaccinated every month

Sampling Domain Knowledge

Say that we want to measure how often people go to risky websites. Let’s assume that the measurement of risk is expensive. We have data on how often people visit each domain on the web from a large sample. The number of unique domains in the data is large,

Homing in on the Home Advantage

A recent piece on ESPNCricinfo analyses the DRS data and argues that cricket should do away with neutral umpires. I reanalyzed the data. If a game is officiated by a home umpire, we expect the following: 1. Hosts will appeal less often as they are likely to be happier with

Nextdoor: Some Finer Points about KNN

The KNN classifier is one of the most intuitive ML algorithms. It predicts class by polling k nearest neighbors. Because it seems so simple, it is easy to miss a couple of the finer points: 1. Sample Splitting: Traditionally, when we split the sample, there is no peeking across samples.

Profit Maximizing Staffing

Say that there is a donation solicitation company. Say that there are 100M potential donors they can reach out to eachyear. Let’s also assume that the company gets paid on a contingency fee basis, getting a fixed percentage of all donations. The company currently follows the following process: it