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Deep Non-line-of-sight Imaging from Under-scanning Measurements
Moreover, the proposed method delivers impressive robustness at an extremely low scanning grid (i.e., 8
On Optimal Caching and Model Multiplexing for Large Model Inference
By combining a caching algorithm, namely Greedy Dual Size with Frequency (GDSF) or Least Expected Cost (LEC), with a model multiplexer, we achieve optimal rates in both offline and online settings.
TradeMaster: A Holistic Quantitative Trading Platform Empowered by Reinforcement Learning
Recent explosion of reinforcement learning in financial trading (RLFT) research has shown stellar performance on many quantitative trading tasks.
effres_project (17).pdf
Effective resistances have a broad range of algorithmic implications.
SlowFocus: Enhancing Fine-grained Temporal Understanding in Video LLM
However, current Vid-LLMs struggle to simultaneously retain high-quality frame-level semantic information ( i.e., a sufficient
Online Iterative Reinforcement Learning from Human Feedback with General Preference Model
The second step is reward modeling, which is the origin of the name "reward-based".
