Matus Telgarsky
Associate Professor of Computer Science
Studies deep learning theory, including representation, optimization and generalization of neural networks.
Matus Telgarsky's lab at NYU works on learning theory & optimization. 7 papers since 2023, 7 at top venues, mostly ICLR and ICML. Applications close .
At a glance
- papers, 2023–2026
- 2/ year
- at T1 venues
- 100%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 1 papers2025 · T1 1
- 3 papers2024 · T1 3
- 3 papers2023 · T1 3
T1 venuesOtherVenues: ICLR, ICML, AISTATS, COLT, NeurIPS
Research focuspaper titles that use each topic's words
- Learning theory & optimization1 paper
- studies deep0 papers
- generalization0 papers
- courant0 papers
- representation0 papers
Paper list
From DBLP.
20251 paper
20243 papers
- COLT (T1)Large Stepsize Gradient Descent for Logistic Loss: Non-Monotonicity of the Loss Improves Optimization Efficiency (opens in a new tab)
- AISTATS (T1)Spectrum Extraction and Clipping for Implicitly Linear Layers (opens in a new tab)
- ICML (T1)Transformers, parallel computation, and logarithmic depth (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to NYUFall 2027
Computer Science PhD (Courant / Tandon)
- Round
- Single round (December)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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Your notes
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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
- DBLP
- Members
- Not collected
- Alumni
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Tiers are venue classifications, not lab rankings.
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