Online k-means Clustering on Arbitrary Data Streams - Lecture

Online k-means Clustering on Arbitrary Data Streams - Lecture

USC Probability and Statistics Seminar via YouTube Direct link

The Lemma Revisited

13 of 16

13 of 16

The Lemma Revisited

Class Central Classrooms beta

YouTube videos curated by Class Central.

Classroom Contents

Online k-means Clustering on Arbitrary Data Streams - Lecture

Automatically move to the next video in the Classroom when playback concludes

  1. 1 Intro
  2. 2 k-means clustering
  3. 3 The online setting
  4. 4 The Goal(s) Cohen-Addad et. al. 2021
  5. 5 A troubling example
  6. 6 Lower Bound
  7. 7 A natural starting point: streaming
  8. 8 A difficult case for streaming
  9. 9 Idea 1: don't remove centers
  10. 10 Proof Sketch
  11. 11 We still have problems on pathological examples.
  12. 12 Idea 2: Using the scale to delete points.
  13. 13 The Lemma Revisited
  14. 14 Our Algorithm's Performance
  15. 15 Proof idea
  16. 16 Future Directions

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.