In the digital realm, ensuring the security and reliability of systems and software is of paramount importance. Fuzzing has emerged as one of the most effective testing techniques for uncovering ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Fine-tuning & Reinforcement Learning for LLMs. 🦥 Train OpenAI gpt-oss, DeepSeek-R1, Qwen3, Gemma 3, TTS 2x faster with 70% less VRAM.

In this tutorial, we explore advanced applications of Stable-Baselines3 in reinforcement learning. We design a fully functional, custom trading environment, integrate multiple algorithms such as PPO ...

Download PDF Join the Discussion View in the ACM Digital Library Deep reinforcement learning (DRL) has elevated RL to complex environments by employing neural network representations of policies. 1 It ...

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 hippocampus has historically been recognized as a critical neural substrate for the formation and retrieval of episodic memories. Concurrently, reinforcement learning (RL) has emerged as a ...

Reinforcement learning (RL) has become central to advancing Large Language Models (LLMs), empowering them with improved reasoning capabilities necessary for complex tasks. However, the research ...

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, ...

Andrew Barto and Richard Sutton developed reinforcement learning, a technique vital to chatbots like ChatGPT. By Cade Metz Reporting from San Francisco In 1977, Andrew Barto, as a researcher at the ...