Evolutionary algorithms (EAs) have long provided a flexible framework for solving challenging optimisation problems by mimicking natural evolutionary processes. When combined with multitask ...
Constantly "re-rolling the dice", combining and selecting: "Evolutionary algorithms" mimic natural evolution in silico and lead to innovative solutions for complex problems. Constantly “re-rolling the ...
Evolutionary reinforcement learning is an exciting frontier in machine learning, combining the strengths of two distinct approaches: reinforcement learning and evolutionary computation. In ...
Dr. James McCaffrey of Microsoft Research says that when quantum computing becomes generally available, evolutionary algorithms for training huge neural networks could become a very important and ...
Dr. James McCaffrey of Microsoft Research explains stochastic gradient descent (SGD) neural network training, specifically implementing a bio-inspired optimization technique called differential ...
Our research efforts aim to understand the nature of visual perception so that we can create more visually intelligent machines. This is enabled via fundamental concepts in reasoning, prediction, ...
We imagine algorithms as computational formulas with standard and stable rules. They are, but in relation to the processors that process them. If the processors, architectures and operation of ...
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