Mark Herbster
Professor of Machine Learning
Researches online learning theory, including learning on graphs and prediction with expert advice.
Mark Herbster's lab at UCL works on learning theory & optimization. 5 papers since 2023, 3 at top venues, mostly NeurIPS and ALT.
At a glance
- papers, 2023–2026
- 1/ year
- at T1 venues
- 60%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage and DBLP, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 0 papers2025 · T1 0
- 3 papers2024 · T1 2
- 2 papers2023 · T1 1
T1 venuesOtherVenues: NeurIPS, ALT, ICML, Machine Learning
Research focuspaper titles that use each topic's words
- online2 papers
- Learning theory & optimization1 paper
- online learning0 papers
- graphs0 papers
- prediction0 papers
Paper list
From the lab homepage and DBLP.
20243 papers
Where alumni went
Alumni are not listed on the lab homepage.
Apply to UCLFall 2027
Not announced yet
Computer Science MPhil/PhD
- Round
- Main
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
Similar labsnearest by research summary
- CNTsinghua
Jingzhao Zhang
- Learning theory & optimization
- GBEdinburgh
Maithilee Kunda
- Reasoning & agents
- DETUM
Debarghya Ghoshdastidar
- Learning theory & optimization
- HKCUHK
Xiaojun Lin
- Learning theory & optimization
- USNYU
Matus Telgarsky
- Learning theory & optimization
- USStanford
Gregory Valiant
- Learning theory & optimization
Your notes
Save this lab to keep notes.
Data
Some numbers could not be verified:
- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
- Collected
- Verified
- Papers
- The lab homepage and DBLP
- Members
- Not collected
- Alumni
- Not collected
Tiers are venue classifications, not lab rankings.