#lossfunctions

Live, measured metrics for the hashtag #lossfunctions from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.

hashtag.org network · sponsored

Own #lossfunctions

This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.

$5.00/ year · 13-character #name
Claim #lossfunctions$5.00/yrBuy on hashtag.space (web3)
card via hashtag.org · tokens via hashtag.space
0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
4
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 4
0
Avg reactions / post
Mastodon · last 4

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-28 02:14 UTC
0
07-22
0
07-23
0
07-24
0
07-25
0
07-26
0
07-27
0
07-28

0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.

Related hashtags

measured · fosstodon.org (Mastodon public search API) · fetched 2026-07-28 02:14 UTC

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-28 02:14 UTC

Everything below is measured over the latest 4 public posts (spanning ~25049 hours).

Top of the latest posts

  • Rahab-Transformer Remastering Architecture Modern AI Engine * CYEMNET A-I AND THE RESHAPING OF CHRISTIAN MINISTRY ONLINE Actual Intelligence (A-I) – Transforming Faith, Education, and Community in the New Age of AI Interaction COFE Yeshua E

    Circle One Fellowship Exeter (COFE)@exeter4christian2church4devon.wordpress.com@exeter4christian2church4devon.wordpress.com002026-05-19 08:13 UTCView post →
  • 'Localisation of Regularised and Multiview Support Vector Machine Learning', by Aurelian Gheondea, Cankat Tilki. http://jmlr.org/papers/v25/23-0522.html #lossfunctions #kernels #semidefinite

    JMLR@[email protected]002025-01-09 21:01 UTCView post →
  • On the curvature of the loss landscape https://arxiv.org/abs/2307.04719 A main challenge in modern deep learning is to understand why such over-parameterized models perform so well when trained on finite data ... we consider the loss landsc

    Victoria Stuart 🇨🇦 🏳️‍⚧️@[email protected]022023-07-12 15:25 UTCView post →

Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/lossfunctions