2 citations · 4 across the 8 of their papers we have counts for
4 papers · 1 filter
Knowledge Cascade: Reverse Knowledge Distillation on Nonparametric Multivariate Functional Estimation
Luyang Fang, Haoran Lu, Yongkai Chen +2
As machine learning models and datasets continue to grow, developing complex models has become increasingly computationally demanding. Knowledge distillation reduces deployment cos…
Multi-Teacher Knowledge Distillation via Teacher-Informed Mixture Priors
Luyang Fang, Yongkai Chen, Jiazhang Cai +2
Knowledge distillation is a powerful method for model compression, enabling the efficient deployment of complex deep learning models (teachers), including large language models. Ho…
Wahkon: A Statistically Principled Deep RKHS Superposition Network
Yongkai Chen, Wenxuan Zhong, Ping Ma
Deep learning excels at prediction but often lacks finite-sample guarantees and calibrated uncertainty; RKHS (Reproducing Kernel Hilbert Space)-based methods provide those guarante…
Best Subset Selection: Statistical Computing Meets Quantum Computing
Wenxuan Zhong, Yuan Ke, Ye Wang +3
With the rapid development of quantum computers, quantum algorithms have been studied extensively. However, quantum algorithms tackling statistical problems are still lacking. In t…