no code implementations • 13 Mar 2024 • Yicheng Li, Xinghua Sun
The SNL is formulated as an Euclidean Distance Matrix Completion (EDMC) problem under the unit ball sample model.
no code implementations • 3 Jan 2024 • Yicheng Li, Weiye Gan, Zuoqiang Shi, Qian Lin
The generalization error curve of certain kernel regression method aims at determining the exact order of generalization error with various source condition, noise level and choice of the regularization parameter rather than the minimax rate.
no code implementations • 2 Jan 2024 • Haobo Zhang, Yicheng Li, Weihao Lu, Qian Lin
Motivated by the studies of neural networks (e. g., the neural tangent kernel theory), we perform a study on the large-dimensional behavior of kernel ridge regression (KRR) where the sample size $n \asymp d^{\gamma}$ for some $\gamma > 0$.
no code implementations • 17 Dec 2023 • Chenglin Li, Qianglong Chen, Liangyue Li, Caiyu Wang, Yicheng Li, Zulong Chen, Yin Zhang
While large language models (LLMs) have demonstrated exceptional performance in recent natural language processing (NLP) tasks, their deployment poses substantial challenges due to high computational and memory demands in real-world applications.
no code implementations • 8 Sep 2023 • Weihao Lu, Haobo Zhang, Yicheng Li, Manyun Xu, Qian Lin
We perform a study on kernel regression for large-dimensional data (where the sample size $n$ is polynomially depending on the dimension $d$ of the samples, i. e., $n\asymp d^{\gamma}$ for some $\gamma >0$ ).
no code implementations • 12 May 2023 • Haobo Zhang, Yicheng Li, Weihao Lu, Qian Lin
In the misspecified kernel ridge regression problem, researchers usually assume the underground true function $f_{\rho}^{*} \in [\mathcal{H}]^{s}$, a less-smooth interpolation space of a reproducing kernel Hilbert space (RKHS) $\mathcal{H}$ for some $s\in (0, 1)$.
no code implementations • 4 May 2023 • Yicheng Li, Zixiong Yu, Guhan Chen, Qian Lin
In this paper, we provide a strategy to determine the eigenvalue decay rate (EDR) of a large class of kernel functions defined on a general domain rather than $\mathbb S^{d}$.
no code implementations • 28 Mar 2023 • Yicheng Li, Haobo Zhang, Qian Lin
One of the most interesting problems in the recent renaissance of the studies in kernel regression might be whether the kernel interpolation can generalize well, since it may help us understand the `benign overfitting henomenon' reported in the literature on deep networks.
no code implementations • 31 Jan 2023 • Zhelun Chen, Jin Wen, Steven T. Bushby, L. James Lo, Zheng O'Neill, W. Vance Payne, Amanda Pertzborn, Caleb Calfa, Yangyang Fu, Gabriel Grajewski, Yicheng Li, Zhiyao Yang
The development of strategies that exploit these flexibilities could be facilitated by publicly available high-resolution datasets illustrating how control of HVAC systems in commercial buildings can be used in different climate zones to shape the energy use profile of a building for grid needs.
no code implementations • 10 May 2020 • Feifan Lv, Yinqiang Zheng, Yicheng Li, Feng Lu
The current industry practice for 24-hour outdoor imaging is to use a silicon camera supplemented with near-infrared (NIR) illumination.
1 code implementation • ECCV 2018 • Ke Gong, Xiaodan Liang, Yicheng Li, Yimin Chen, Ming Yang, Liang Lin
Instance-level human parsing towards real-world human analysis scenarios is still under-explored due to the absence of sufficient data resources and technical difficulty in parsing multiple instances in a single pass.
Ranked #6 on Human Part Segmentation on CIHP