IEEE

Task-Driven Priority-Aware Computation Offloading Using Deep Reinforcement Learning

Abstract: Computation offloading is an effective method for reducing the pressure put on networks and improving the service experience. However, most existing research on computation offloading is ...
northpennnow

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
GitHub

SQL-R1: Training Natural Language to SQL Reasoning Model By Reinforcement Learning

Natural Language to SQL (NL2SQL) enables intuitive interactions with databases by transforming natural language queries into structured SQL statements. Despite recent advancements in enhancing ...
GitHub

InftyThink+: Effective and Efficient Infinite-Horizon Reasoning via Reinforcement Learning

Building upon our previous work InftyThink, we introduce InftyThink+, an end-to-end reinforcement learning framework that directly optimizes the complete iterative reasoning trajectory. Building on ...
IEEE

Encoding High-Level Knowledge in Offline Multi-Agent Reinforcement Learning Using Reward Machines

Abstract: Offline reinforcement learning (RL) learns policies from fixed-size datasets without interacting with the environment, while multi-agent reinforcement learning (MARL) faces challenges from ...