3 papers
cs.LG2025
SPECTra: Scalable Multi-Agent Reinforcement Learning with Permutation-Free Networks
Hyunwoo Park, Baekryun Seong, Sang-Ki Ko
In cooperative multi-agent reinforcement learning (MARL), the permutation problem where the state space grows exponentially with the number of agents reduces sample efficiency. Add…
cs.LG2024
MPruner: Optimizing Neural Network Size with CKA-Based Mutual Information Pruning
Seungbeom Hu, ChanJun Park, Andrew Ferraiuolo +4
Determining the optimal size of a neural network is critical, as it directly impacts runtime performance and memory usage. Pruning is a well-established model compression technique…
cs.AI2024
Towards Efficient Formal Verification of Spiking Neural Network
Baekryun Seong, Jieung Kim, Sang-Ki Ko
Recently, AI research has primarily focused on large language models (LLMs), and increasing accuracy often involves scaling up and consuming more power. The power consumption of AI…