معرفی
Raghav Bongole is a doctoral researcher at the Division of Information Science and Engineering within the School of Electrical Engineering and Computer Science at Kungliga Tekniska Högskolan (KTH). His work focuses on theoretical foundations of reinforcement learning through the lens of information theory, supervised by Professors Mikael Skoglund and Tobias Oechtering under the Wallenberg AI, Autonomous Systems and Software Program (WASP).
Research Interests:
- Information-theoretic bounds for RL algorithms
- Duality between entropy and learning performance
- Theoretical optimization in autonomous systems
Recent Work (2024): Co-authored a paper on arXiv addressing duality-based bounds for reinforcement learning, with implications for algorithm design and sample efficiency. The work intersects computer science, machine learning theory, and optimization.
Contact: bongole@kth.se
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