In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...
The presentation below, “Using Bayesian Optimization to Tune Machine Learning Models” by Scott Clark of SigOpt is from MLconf. The talk briefly introduces Bayesian Global Optimization as an efficient ...
As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...
This is where Collective Adaptive Intelligence (CAI) comes in. CAI is a form of collective intelligence in which the ...
Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...
When choosing a large language model (LLM) for use in a particular task, one of the first things that people often look at is the model's parameter count. A vendor might offer several different ...
A research team has developed a new way to measure and predict how plant leaves scatter and reflect light, revealing that ...
From SOCs to smart cameras, AI-driven systems are transforming security from a reactive to a predictive approach. This ...
In contrast to machine learning (ML), machine unlearning is the process of removing certain data or influences from models as the need arises.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback