4 papers
Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning
Zhao Yang, Yuxuan Jiang, Ting-Chih Chen +18
Reinforcement learning (RL) has become central to LLM post-training, yet the methods that dominate current pipelines, PPO and GRPO, represent only a narrow slice of what RL offers.…
Relative Phase Equivariant Deep Neural Systems for Physical Layer Communications
Arwin Gansekoele, Sandjai Bhulai, Mark Hoogendoorn +1
In the era of telecommunications, the increasing demand for complex and specialized communication systems has led to a focus on improving physical layer communications. Artificial…
A Machine Learning Approach for Simultaneous Demapping of QAM and APSK Constellations
Arwin Gansekoele, Alexios Balatsoukas-Stimming, Tom Brusse +3
As telecommunication systems evolve to meet increasing demands, integrating deep neural networks (DNNs) has shown promise in enhancing performance. However, the trade-off between a…
Unveiling the Potential: Harnessing Deep Metric Learning to Circumvent Video Streaming Encryption
Arwin Gansekoele, Tycho Bot, Rob van der Mei +2
Encryption on the internet with the shift to HTTPS has been an important step to improve the privacy of internet users. However, there is an increasing body of work about extractin…