Keith Ross
Professor
Researches deep reinforcement learning, including sample-efficient off-policy algorithms, after earlier work on networking and internet privacy.
Keith Ross's lab at NYU works on reinforcement learning, trustworthy & safe ML and efficient training & inference. 7 papers since 2023, 4 at top venues, mostly EMNLP and ICLR. 1 PhD student. 31 alumni. Applications close .
At a glance
- papers, 2023–2026
- 2/ year
- at T1 venues
- 57%
- PhD students
- 1
- MS students
- 0
- alumni listed
- 31
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 5 papers2025 · T1 2
- 2 papers2024 · T1 2
- 0 papers2023 · T1 0
T1 venuesOtherVenues: EMNLP, ICLR, NeurIPS, TMLR
Research focuspaper titles that use each topic's words
- Reinforcement learning2 papers
- Efficient training & inference2 papers
- Trustworthy & safe ML0 papers
- sample-efficient0 papers
- earlier0 papers
Paper list
From the lab homepage.
20255 papers
- TMLR (T1)Cross-Entropy versus Label Smoothing: A Neural Collapse Perspective
- Math_AI Workshop, NeurIPSLayer Importance for Mathematical Reasoning is Forged in Pre-Training and Invariant after Post-Training
- Math_AI Workshop, NeurIPSReinforcement Learning vs. Distillation: Understanding Accuracy and Capability in LLM Reasoning
- Ingredients for Developing Generalist Agents WorkshopShould We Ever Prefer Decision Transformer
- EMNLP (T1)Warm UP Before You Train: Unlocking General Reasoning in Resource-Constrained Settings
20242 papers
- ICLR (T1)Pre-training with Synthetic Data Helps Offline Reinforcement Learning
- NeurIPS (T1)The Prevalence of Neural Collapse in Neural Multivariate Regression
Where alumni went31 listed
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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Data
Checked against the lab homepage.
- Collected
- Verified
- Papers
- The lab homepage
- Members
- Lab homepage
- Alumni
- Lab homepage
Tiers are venue classifications, not lab rankings.
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