24 citations · 29 across the 4 of their papers we have counts for
7 papers
The hyperonic star in relativistic mean-field model
Kaixuan Huang, Jinniu Hu, Ying Zhang +1
The neutron star as a supernova remnant is attracting high attention recently due to the gravitation wave detection and precise measurements about its mass and radius. In the inner…
Optimal Gradient-based Algorithms for Non-concave Bandit Optimization
Baihe Huang, Kaixuan Huang, Sham M. Kakade +4
Bandit problems with linear or concave reward have been extensively studied, but relatively few works have studied bandits with non-concave reward. This work considers a large fami…
A Short Note on the Relationship of Information Gain and Eluder Dimension
Kaixuan Huang, Sham M. Kakade, Jason D. Lee +1
Eluder dimension and information gain are two widely used methods of complexity measures in bandit and reinforcement learning. Eluder dimension was originally proposed as a general…
Fast Federated Learning in the Presence of Arbitrary Device Unavailability
Xinran Gu, Kaixuan Huang, Jingzhao Zhang +1
Federated Learning (FL) coordinates with numerous heterogeneous devices to collaboratively train a shared model while preserving user privacy. Despite its multiple advantages, FL f…
The possibility of the secondary object in GW190814 as a neutron star
Kaixuan Huang, Jinniu Hu, Ying Zhang +1
A compact object was observed with a mass by LIGO Scientific and Virgo collaborations (LVC) in GW190814, which provides a great challenge to the investigations…
Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? -- A Neural Tangent Kernel Perspective
Kaixuan Huang, Yuqing Wang, Molei Tao +1
Deep residual networks (ResNets) have demonstrated better generalization performance than deep feedforward networks (FFNets). However, the theory behind such a phenomenon is still…