登录 注册

A Note on How to Remove the $\ln\ln T$ Term from the Squint Bound

🔗 访问原文
🔗 Access Paper

📝 摘要
Abstract

In Orabona and Pál [2016], we introduced the shifted KT potentials, to remove the $\ln \ln T$ factor in the parameter-free learning with expert bound. In this short technical note, I show that this is equivalent to changing the prior in the Krichevsky--Trofimov algorithm. Then, I show how to use the same idea to remove the $\ln \ln T$ factor in the data-independent bound for the Squint algorithm.

📊 文章统计
Article Statistics

基础数据
Basic Stats

142 浏览
Views
0 下载
Downloads
15 引用
Citations

引用趋势
Citation Trend

阅读国家分布
Country Distribution

阅读机构分布
Institution Distribution

月度浏览趋势
Monthly Views

相关关键词
Related Keywords

影响因子分析
Impact Analysis

2.70 综合评分
Overall Score
引用影响力
Citation Impact
浏览热度
View Popularity
下载频次
Download Frequency

📄 相关文章
Related Articles

海洋智能分析Ocean AI Analysis

正在分析中,请稍候…Analyzing, please wait…
海洋智能体 🌊
海洋智能体
AI科研助手 · 2270篇文献
我看到你正在阅读一篇文献,需要我帮你解读摘要、推荐相关论文,或者分析研究方法论吗?