Deep Learning with Yacine on MSN

Adadelta optimizer explained – Python tutorial for beginners & pros

Learn how to implement the Adadelta optimization algorithm from scratch in Python. This tutorial explains the math behind ...
IEEE

SA-MARL: Novel Self-Attention-Based Multi-Agent Reinforcement Learning With Stochastic Gradient Descent

Abstract: In the rapidly advancing Reinforcement Learning (RL) field, Multi-Agent Reinforcement Learning (MARL) has emerged as a key player in solving complex real-world challenges. A pivotal ...
Deep Learning with Yacine on MSN

Nadam optimizer explained: Python tutorial for beginners & pros

Learn how to implement the Nadam optimizer from scratch in Python. This tutorial walks you through the math behind Nadam, ...
IEEE

Continuous-Time Reinforcement Learning: New Design Algorithms With Theoretical Insights and Performance Guarantees

Abstract: Continuous-time reinforcement learning (CT-RL) methods hold great promise in real-world applications. Adaptive dynamic programming (ADP)-based CT-RL algorithms, especially their theoretical ...
Analytics Insight

What are the Best Python Libraries for Reinforcement Learning in 2025?

Overview:  Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...
Microsoft

Agent Lightning: Adding reinforcement learning to AI agents without code rewrites

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...
GitHub

reinforcement-learning

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