今天在看证明的时候看到一个细节，$d$维球面$S^{d-1}$上均匀分布的点$\mathbf{x}$，向任意一个自然基$\mathbf{e_i}=(0,0,…,1,…,0)$做投影$\mathbf{x}^{\top}\mathbf{e_i}$，问投影绝对值的期望$\mathbb{E}_{\mathbf{x}\sim \mathbf{U}(S^{d-1})}(

\mathbf{x}^{\top}\mathbf{e_i}

)$是多少。

基于Domain Scatter的领域自适应/领域泛化理论上界

1 minute read

Published: September 05, 2022

大家好，今天我们再来看一个bound的证明。（没错我就是bound收集狂人，笑）今天这个bound来自于一篇15年的TPAMI文章，名字叫做《Scatter Component Analysis: A Unifified Framework for Domain Adaptation and Domain Generalization》。

portfolio

Portfolio item number 1

Short description of portfolio item number 1

Portfolio item number 2

Short description of portfolio item number 2

publications

Deep into The Domain Shift: Transfer Learning through Dependence Regularization

Published in SSRN, 2022

In this papaer, we develop a novel domain adaptation method that can flexibly model the correspondence strength between source distributions and target distributions.

Download here

Network Vector Autoregressive Moving Average Model

Published in Statistics and Its Interface, 2022

In this paper, we propose a NARMA model that integrates both the autoregressive and moving average components into the network models.

Download here

A Unified Domain Adaptation Framework with Distinctive Divergence Analysis

Published in Transactions on Machine Learning Research, 2022

In this paper, we propose a unified framework that provides a shared understanding of both domain adaptation problems, including classification and regression, from the same perspective.

Download here

On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective

Published in arxiv, 2023

We systematically study and evaluate the adversarial robustness and out-of-distribution generalization of ChatGPT and other large language models in this article.

Download here

Biography

Sitemap

Pages

Posts

引子

portfolio

publications

talks

teaching