At Pittcon 2026 in San Antonio, Texas, USA, LCGC International spoke with 2026 LCGC International Emerging Leader Award ...
Supervised learning algorithms learn from labeled data, where the desired output is known. These algorithms aim to build a model that can predict the output for new, unseen input data. Let’s take a ...
When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...
For about a decade, computer engineer Kerem Çamsari employed a novel approach known as probabilistic computing. Based on probabilistic bits (p-bits), it’s used to solve an array of complex ...
This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...
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New memristor design uses built-in oxygen gradient to bring stability to reinforcement learning
In a recent study published in Nature Communications, researchers created a memristor that uses a built-in oxygen gradient to ...
At Pittcon 2026, LCGC International Emerging Leader Award Winner, Bob Pirok, discussed the barriers to fully automated method ...
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