Barzilai--Borwein (BB) method has shown strong practical performance in continuous optimization, yet its convergence dynamics remains poorly understood. In particular, a central unresolved question is whether BB converges superlinearly for almost every strictly convex quadratic p…
Reinforcement learning (RL) has become a central component of post-training large language models (LLMs), yet little is understood about how RL adaptation is distributed across transformer layers. Existing approaches typically update all model parameters uniformly, implicitly ass…
Predicting how people choose their travel modes accurately is important in the transportation field. Machine learning (ML) and neural networks (NNs) have gradually become popular in recent years. However, which is better is seldom discussed in previous studies. Therefore, we coll…