#InfluenceEstimation

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

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0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
2
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 2
0
Avg reactions / post
Mastodon · last 2

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 12:23 UTC
0
07-21
0
07-22
0
07-23
0
07-24
0
07-25
0
07-26
0
07-27

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 2026-07-27 12:23 UTC

No related tags with measured usage found for #influenceestimation.

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 12:23 UTC

Everything below is measured over the latest 2 public posts (spanning ~5016 hours).

Posting hours (UTC)

00:0012:0023:00

Languages: English (2)

Avg boosts / post: 2.5

Top of the latest posts

  • Influence estimation + Tree ensembles + Lots of empirical results = Our new paper in JMLR! My two favorite results: 1. TracIn is easily adapted to trees, and works great. 2. In some settings, approximate influence estimates are much better

    Daniel Lowd@[email protected]012023-06-08 04:55 UTCView post →
  • In #AdversarialML, targeted training set attacks are one of the biggest threats to #MachineLearning -- highly effective and hard to detect! In a #NewPaper at #CCS2022 this week, Zayd Hammoudeh and I show how you can use #InfluenceEstimation

    Daniel Lowd@[email protected]042022-11-11 04:54 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/influenceestimation