2期

最新文章

• Statistical exploration of the Manifold Hypothesis AI翻译
  作者：He, Yinqiu
  作者单位：University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison
  摘要：The manifold hypothesis is a widely accepted tenet of machine learning which asserts that nominally high-dimensional data are in fact concentrated near a low-dimensional manifold, embedded in high-dimensional space. This phenomenon is observed empirically in many real-world situations, has led to development of a wide range of statistical methods in the last few decades, and has been suggested as a key factor in the success of modern AI technologies. We show that rich and sometimes intricate m...
• Spectral change point estimation for high-dimensional time series by sparse tensor decomposition AI翻译
  作者：Zhang, Xinyu; Chan, Kung-Sik
  作者单位：East China Normal University; East China Normal University; University of Iowa
  摘要：Multivariate time series may be subject to partial structural changes over certain frequency band, for instance, in neuroscience. We study the change point detection problem with high-dimensional time series, within the framework of frequency domain. The overarching goal is to locate all change points and delineate which series are activated by the change, over which frequencies. In practice, the number of activated series per change and frequency could span from a few to full participation. W...
• Statistical exploration of the Manifold Hypothesis AI翻译
  作者：He, Yinqiu
  作者单位：University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison
  摘要：The manifold hypothesis is a widely accepted tenet of machine learning which asserts that nominally high-dimensional data are in fact concentrated near a low-dimensional manifold, embedded in high-dimensional space. This phenomenon is observed empirically in many real-world situations, has led to development of a wide range of statistical methods in the last few decades, and has been suggested as a key factor in the success of modern AI technologies. We show that rich and sometimes intricate m...
• Spectral change point estimation for high-dimensional time series by sparse tensor decomposition AI翻译
  作者：Zhang, Xinyu; Chan, Kung-Sik
  作者单位：East China Normal University; East China Normal University; University of Iowa
  摘要：Multivariate time series may be subject to partial structural changes over certain frequency band, for instance, in neuroscience. We study the change point detection problem with high-dimensional time series, within the framework of frequency domain. The overarching goal is to locate all change points and delineate which series are activated by the change, over which frequencies. In practice, the number of activated series per change and frequency could span from a few to full participation. W...
• Michael Trosset's contribution to the Discussion of 'Statistical exploration of the Manifold Hypothesis' by Whitely et al. AI翻译
  作者：Trosset, Michael W.
  作者单位：Indiana University Bloomington; Indiana University System; Indiana University Bloomington
• Zihao Wen and David L. Dowe's contribution to the Discussion of 'Statistical exploration of the manifold hypothesis' by Whiteley et al. AI翻译
  作者：Wen, Zihao; Dowe, David L.
  作者单位：Monash University; South China Agricultural University
• Joshua Cape's contribution to the Discussion of 'Statistical exploration of the Manifold Hypothesis' by Whiteley et al. AI翻译
  作者：Cape, Joshua
  作者单位：University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison
• Robust detection of watermarks for large language models under human edits AI翻译
  作者：Li, Xiang; Ruan, Feng; Wang, Huiyuan; Long, Qi; Su, Weijie J.
  作者单位：University of Pennsylvania; Pennsylvania Medicine; Northwestern University; University of Pennsylvania
  摘要：Watermarking is an effective approach to distinguishing text generated by large language models (LLMs) from human-written text. However, the pervasive presence of human edits on LLM-generated text dilutes watermark signals, thereby significantly degrading detection performance of existing methods. In this paper, by modelling human edits through mixture model detection, we introduce a new method-a truncated goodness-of-fit test (Tr-GoF) for detecting watermarked text under human edits. We prove...
• Safaa K. Kadhem's contribution to the Discussion on 'Statistical exploration of the manifold hypothesis' by Nick Whiteley, Annie Grayb, and Patrick Rubin-Delanchy AI翻译
  作者：Kadhem, Safaa K.
• Poorbita Kundu's and Johannes Schmidt-Hieber's contribution to the Discussion of 'Statistical exploration of the manifold hypothesis' by Whiteley et al. AI翻译
  作者：Kundu, Poorbita; Schmidt-Hieber, Johannes
  作者单位：Fred Hutchinson Cancer Center; University of Twente