locally encod'/> Semisupervised Clustering by Queries and Locally Encodable Source Coding
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE Transactions on Information Theory >Semisupervised Clustering by Queries and Locally Encodable Source Coding
【24h】

Semisupervised Clustering by Queries and Locally Encodable Source Coding

机译：Semupervised Clustering由查询和本地可供选择的源码编码

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Source coding is the canonical problem of data compression in information theory. In a locally encodable source coding, each compressed bit depends on only few bits of the input. In this paper, we show that a recently popular model of semisupervised clustering is equivalent to locally encodable source coding. In this model, the task is to perform multiclass labeling of unlabeled elements. At the beginning, we can ask in parallel a set of simple queries to an oracle who provides (possibly erroneous) binary answers to the queries. The queries cannot involve more than two (or a fixed constant number of) elements. Now the labeling of all the elements (or clustering) must be performed based on the noisy query answers. The goal is to recover all the correct labelings while minimizing the number of such queries. The equivalence to locally encodable source codes leads us to find lower bounds on the number of queries required in variety of scenarios. We provide querying schemes based on pairwise ‘same cluster’ queries - and pairwise AND queries, and show provable performance guarantees for each of the schemes.
机译：源编码是信息理论中数据压缩的规范问题。在<斜体xmlns：mml =“http://www.w3.org/1998/math/mathml”xmlns：xlink =“http://www.w3.org/1999/xlink”>本地可供选择源编码，每个压缩位仅取决于输入的几个位。在本文中，我们表明最近流行的半体群集模型相当于本地可编码源编码。在此模型中，该任务是执行未标记元素的多级标记。在开始时，我们可以并行向Oracle并行向Oracle并行询问Oracle，谁向查询提供（可能是错误）二进制答案。查询不能涉及超过两个（或固定常量数）元素。现在必须基于嘈杂的查询答案来执行所有元素（或群集）的标签。目标是恢复所有正确的贴标，同时最小化此类查询的数量。对本地可编码的等价性导致我们在各种方案所需的查询数上找到下限。我们根据成对的“相同的群集”查询提供查询方案 - 以及成对和查询，并为每个方案显示可提供的可提供性能保证。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号