27 Matching Annotations
  1. Dec 2023
  2. Nov 2023
    1. Cut/Copy/Paste explores the relations between fragments, history, books, and media. It does so by scouting out fringe maker cultures of the seventeenth century, where archives were cut up, “hacked,” and reassembled into new media machines: the Concordance Room at Little Gidding in the 1630s and 1640s, where Mary Collett Ferrar and her family sliced apart printed Bibles and pasted the pieces back together into elaborate collages known as “Harmonies”; the domestic printing atelier of Edward Benlowes, a gentleman poet and Royalist who rode out the Civil Wars by assembling boutique books of poetry; and the nomadic collections of John Bagford, a shoemaker-turned-bookseller who foraged fragments of old manuscripts and title pages from used bookshops to assemble a material history of the book. Working across a century of upheaval, when England was reconsidering its religion and governance, each of these individuals saved the frail, fragile, frangible bits of the past and made from them new constellations of meaning. These fragmented assemblages resist familiar bibliographic and literary categories, slipping between the cracks of disciplines; later institutions like the British Library did not know how to collate or catalogue them, shuffling them between departments of print and manuscript. Yet, brought back together in this hybrid history, their scattered remains witness an emergent early modern poetics of care and curation, grounded in communities of practice. Stitching together new work in book history and media archaeology via digital methods and feminist historiography, Cut/Copy/Paste traces the lives and afterlives of these communities, from their origins in early modern print cultures to the circulation of their work as digital fragments today. In doing so, this project rediscovers the odd book histories of the seventeenth century as a media history with an ethics of material making—one that has much to teach us today.
  3. Oct 2023
    1. Discussion of the paper:

      Ghojogh B, Ghodsi A, Karray F, Crowley M. Theoretical Connection between Locally Linear Embedding, Factor Analysis, and Probabilistic PCA. Proceedings of the Canadian Conference on Artificial Intelligence [Internet]. 2022 May 27; Available from: https://caiac.pubpub.org/pub/7eqtuyyc

  4. Feb 2023
  5. May 2022
    1. Projects like the Open Journal System, Manifold or Scalar are based on a distributed model that allow anyone to download and deploy the software (Maxwell et al., 2019), offering an alternative to the commercial entities that dominate the scholarly communication ecosystem.

      Might Hypothes.is also be included with this list? Though it could go a bit further toward packaging and making it more easily available to self-hosters.

  6. Nov 2021
  7. Sep 2021
    1. One popular theory among machine learning researchers is the manifold hypothesis: MNIST is a low dimensional manifold, sweeping and curving through its high-dimensional embedding space. Another hypothesis, more associated with topological data analysis, is that data like MNIST consists of blobs with tentacle-like protrusions sticking out into the surrounding space.
  8. Apr 2021
    1. I totally want to play around with both of these and host personal versions to play around with. Sadly some of the technical requirements for them always seem just beyond my reach. Perhaps I'll give it another go shortly.

      I do wonder what a Reclaim Cloud instance would end up running over time. I doubt I'd drive much traffic.

    1. Manifold – Building an Open Source Publishing Platform

      Zach Davis and Matthew Gold

      Re-watching after the conference.

      Manifold

      Use case of showing the process of making the book. The book as a start to finish project rather than just the end product.

      They built the platform while eating their own cooking (or at least doing so with nearby communities).

      Use for this as bookclubs. Embedable audio and video possibilities.

      Use case where people have put journals on the platform and they've grown to add meta data and features to work for that.

      They're allowing people to pull in social media pieces into the platform as well. Perhaps an opportunity to use Webmentions?

      They support epub.

      It can pull in Gutenberg texts.

      Jim Groom talks about the idea of almost using Manifold as an LMS in and of itself. Centering the text as the thing around which we're gathering.

      CUNY Editions of standard e-books with additional resources.Critical editions.

      Using simple tools like Google Docs and then ingest them into Manifold using a YAML file.

      TEI, LaTeX formats and strategies for pulling them in. (Are these actually supported? It wasn't clear.)

      Reclaim Cloud has a container that will run Manifold.

      Zach is a big believer in UX and design as the core of their product.

  9. Dec 2018
    1. A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms and Software

      很不错的 Distance Metric Learning 综述性材料,富含概念,如何设计DML算法,DML 算法的数学理论是怎样的(凸优化、矩阵分析、信息论)等等。最后开源了Python 库 pyDML 以方便研究此 paper 中的算法。

  10. Nov 2018
    1. Grassmannian Learning: Embedding Geometry Awareness in Shallow and Deep Learning

      就喜欢这些用微分流形讲机器学习的~!

      应该写个 Paper Summary 表示尊敬~~~

    2. Classification and Geometry of General Perceptual Manifolds

      一篇Physical Review X 上的文章~ 读读看~

      Paper Summary

    3. UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

      此文提供了一个和 t-sne 非常类似的降维可视化算法。效果相当不错!也开源了算法代码。

      按照作者的说法,UMAP 比 T-SNE 算法更好的优点有二:更快!更准!

  11. Apr 2017
    1. We are asking authors to consider, from the very beginning of the research process, developing and sharing their project iteratively. Research materials, filmed images, field notes, ethnographic materials, sketches, maps, audio recordings, interviews, and other forms of research that are used to write the monograph will have a place on Manifold so that scholars can share their work as it is being researched and written.
    1. Our goal is to create a platform that will rival the reading experience of a commercial site like Medium but that is free and open-source.