The passive localization system (PLS) is fundamental to many wireless applications. The deployment of the monitoring stations plays a key role in the performance of the PLSes. However, the workflow…
Many massive data sets are assembled through collections of information of a large number of individuals in a population. The analysis of such data, especially in the aspect of individualized infer…
By employing the mode decomposition method to study the relative mode evolution characteristics during the stimulated Raman scattering (SRS) process, a numerical model of the core-pumped Raman effe…
We demonstrate a novel 850 nm high-speed photodetector for simultaneous high-speed data acquisition and electrical power generation from the optical signal. The device is based on GaAs/AlGaAs modif…
Orbital angular momentum (OAM) mode multiplexing provides a promising solution for enlarging communication capacity density. Although various OAM mode multiplexing technologies have been investigat…
We develop provably efficient reinforcement learning algorithms for two-player zero-sum finite-horizon Markov games with simultaneous moves. To incorporate function approximation, we consider a fam…
Fusion learning refers to synthesizing inferences from multiple sources or studies to make a more effective inference and prediction than from any individual source or study alone. Most existing me…
We develop provably efficient reinforcement learning algorithms for two-player zero-sum finite-horizon Markov games with simultaneous moves. To incorporate function approximation, we consider a fam…
In this work, we consider the popular tree-based search strategy within the framework of reinforcement learning, the Monte Carlo tree search (MCTS), in the context of the infinite-horizon discounte…
Reducing the complexity of the pipeline of instance segmentation is crucial for real-world applications. This work addresses this issue by introducing an anchor-box free and single-shot instance se…