The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...

Nguyen Xuan Long, a globally recognized expert in statistical inference and machine learning currently based in the United ...

Abstract: We investigate the problem of recovering a structured sparse signal from a linear observation model with an uncertain dynamic grid in the sensing matrix. The state-of-the-art expectation ...

Abstract: For drones, robot targets in specific areas may be lost, the location search after losing power. According to the dynamics principle, this paper introduced that the random walk model ...

Google has introduced TurboQuant, a compression algorithm that reduces large language model (LLM) memory usage by at least 6x while boosting performance, targeting one of AI's most persistent ...

The course is structured in four main parts, covering the full Bayesian workflow: from probabilistic reasoning to advanced modeling. BAYESIANLEARNING/ │ ├── PART-I/ │ ├── theory/ │ │ └── ...

Google says its new TurboQuant method could improve how efficiently AI models run by compressing the key-value cache used in LLM inference and supporting more efficient vector search. In tests on ...

If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...

This repository includes theoretical notes, slides, and hands-on R examples for exploring Bayesian Linear Regression. It introduces both classical and Bayesian regression methods, showing how to ...