Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
1 Electric Power Research Institute, China Southern Power Grid, Guangzhou, China 2 Guangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guangzhou, China In modern power systems, Modular ...
The study, titled Reinforcement Learning for Monetary Policy Under Macroeconomic Uncertainty: Analyzing Tabular and Function ...
What is catastrophic forgetting in foundation models? Foundation models excel in diverse domains but are largely static once deployed. Fine-tuning on new tasks often introduces catastrophic forgetting ...
Forbes contributors publish independent expert analyses and insights. Author, Researcher and Speaker on Technology and Business Innovation. Apr 19, 2025, 03:24am EDT Apr 21, 2025, 10:40am EDT ...
The rapid advancements in quantum computing have opened new avenues for enhancing reinforcementlearning (RL), particularly through the use of parameterized quantum circuits (PQCs) as function ...
In the 1980s, Andrew Barto and Rich Sutton were considered eccentric devotees to an elegant but ultimately doomed idea—having machines learn, as humans and animals do, from experience. Decades on, ...
So far we’ve only looked at action-value methods which learn values of individual actions and derive a policy from them This includes methods like SARSA, Q-Learning, DQN The policies of these methods ...
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