3 citations · 10 across the 24 of their papers we have counts for
6 papers · 1 filter
Risk Equivalence between RKHS Regression and Sequence Models for Lipschitz Spectral Algorithms
Yicheng Li, Yuqian Cheng, Zhuo Chen +1
Kernel spectral algorithms are often summarized by convergence rates, which hide how their risk depends jointly on regularization, noise, the population spectrum, target coefficien…
Exact Generalization Error Curves of Kernel Ridge Regression for Functional Moment Estimation
Yinan Ding, Yicheng Li
Kernel ridge regression is a standard method for functional data analysis, but its exact behavior is less understood. We study tensor-product kernel ridge regression for estimating…
AMO: Operator-level Adaptive Muon Orthogonalization
Xinlin Zhuang, Panyi Ouyang, Yichen Li +7
Muon has recently emerged as a competitive alternative to AdamW for large-scale pre-training, with orthogonalization via Newton-Schulz (NS) iteration as its core operation. Standar…
Large Dimensional Kernel Ridge Regression: Extending to Product Kernels
Yang Zhou, Yicheng Li, Yuqian Cheng +1
Recent studies have reported and in large dimensional kernel ridge regression (KRR). However, these findings are…
A Van Trees Lower Bound for Fully Interactive Differentially Private Federated Learning
T. Tony Cai, Yicheng Li
Federated differentially private protocols can communicate over many adaptive rounds and reuse each client's local samples. Existing lower bound arguments for federated DP are ofte…
PanguMotion: Continuous Driving Motion Forecasting with Pangu Transformers
Quanhao Ren, Yicheng Li, Nan Song
Motion forecasting is a core task in autonomous driving systems, aiming to accurately predict the future trajectories of surrounding agents to ensure driving safety. Existing metho…