Abstract: Sparse Bayesian learning (SBL) is an algorithm for high-dimensional data processing based on Bayesian statistical theory. Its goal is to improve the generalization ability and efficiency of ...

Abstract: Sparse Bayesian Learning (SBL) is recognized for its efficacy in sparse signal recovery, the computational demand escalates significantly with increasing data dimensionality due to the ...

What’s often misunderstood about Google’s incrementality testing and how Bayesian models use probability to guide better decisions.

Wienöbst, M., Bannach, M., & Liśkiewicz, M. (2023). Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs with Applications. Journal of ...

Learn how prior probability informs economic theory and decision-making in Bayesian statistics. Understand its role before collecting new data.

Google DeepMind, a United Kingdom-based artificial intelligence company, is widely regarded as one of the pioneers of modern AI.

Bayesian inference is a statistical method of inductive reasoning based on the reassessment of competing hypotheses in the presence of new evidence. Conceptually similar to the scientific method ...

The paper addresses the AI shutdown problem, a long-standing challenge in AI safety. The shutdown problem asks how to design AI systems that will shut down when instructed, will not try to prevent ...

This important study reports three experiments examining how the subjective experience of task regularities influences perceptual decision-making. Although the evidence linking subjective ratings to ...

Combining microscopy and machine-learning techniques leads to faster, more precise analyses of critical coating materials ...

This article explores the potential of large language models (LLMs) in reliability systems engineering, highlighting their ...

CRO doesn’t stop just because you can’t A/B test. This article breaks down how ecommerce teams can improve conversion rate ...