Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.

Learn the distinctions between simple and stratified random sampling. Understand how researchers use these methods to accurately represent data populations.

Behavioral economics relies heavily on studies of Western, educated people. A recent analysis provides evidence that ignoring racial diversity within the United States has led to flawed ...

Welcome to the repository for our paper: "Rethinking Domain Generalization: Discriminability and Generalizability." You can use the following training command to train DMDA. We provide the sample on ...

This important study describes long-range serial dependence of performance on a visual texture discrimination training task that manipulated conditions to induce differing degrees of location transfer ...

The Feeding Our Future fraud was a serious failure of oversight and accountability. The theft of hundreds of millions of taxpayer dollars is indefensible, and those responsible — regardless of ...

This valuable study shows that combining reactivation-based training with anodal tDCS yields an unusually broad generalization of visual perceptual learning, while preserving robust learning gains and ...

Machine learning models often perform impressively in the lab but struggle in the real world. The main culprit? Domain shift: the difference between the data a model was trained on and the data it ...

Optimization is a crucial tool throughout science and technology. Large datasets and high dimensional problems create unique challenges for standard optimization techniques such as Newton’s method, ...

Language models (LMs) have great capabilities as in-context learners when pretrained on vast internet text corpora, allowing them to generalize effectively from just a few task examples. However, fine ...

Deep neural networks’ seemingly anomalous generalization behaviors, benign overfitting, double descent, and successful overparametrization are neither unique to neural networks nor inherently ...