Clayton Scott
Professor, EECS – Electrical and Computer Engineering
Studies statistical machine learning theory and methods, including learning from noisy labels and domain adaptation.
Clayton Scott's lab at Michigan works on learning theory & optimization. 17 papers since 2023, 9 at top venues, mostly ICML and NeurIPS. 3 PhD students. 21 alumni, most often to Microsoft and Google. Applications close .
At a glance
- papers, 2023–2026
- 4/ year
- at T1 venues
- 53%
- PhD students
- 3
- MS students
- 0
- alumni listed
- 21
Papers by yearfrom the lab homepage and DBLP, 2023–2026
- 4 papers2026 · T1 1 · collecting
- 4 papers2025 · T1 2
- 7 papers2024 · T1 4
- 2 papers2023 · T1 2
T1 venuesOtherVenues: ICML, NeurIPS, COLT, ICLR, JMLR
Research focuspaper titles that use each topic's words
- Learning theory & optimization2 papers
- noisy0 papers
- domain adaptation0 papers
- adaptation0 papers
- domain0 papers
Paper list
From the lab homepage and DBLP.
20264 papers
- ICLR (T1)Flow Straight and Fast in Hilbert Space: Functional Rectified Flow (opens in a new tab)
- —It Takes One to Bias Them All: Breaking Bad with One-Shot GRPO (opens in a new tab)
- —Semantic Editing with Coupled Stochastic Differential Equations (opens in a new tab)
- Performance Guarantees via Selective Classification'', NeurIPSXabier de Juan, Santiago Mazuelas, Yilun Zhu, and Clayton Scott, ``Estimation of the Label-Noise Transition Matrix with
20254 papers
- Neural ComputationEstimating Phase from Observed Trajectories Using the Temporal 1-Form (opens in a new tab)
- ICML (T1)Feasible Action Search for Bandit Linear Programs via Thompson Sampling (opens in a new tab)
- TMLR (T1)Label Embeddeding via Low Coherence Matrices (opens in a new tab)
- Trans. Mach. Learn. Res.Label Embedding via Low-Coherence Matrices (opens in a new tab)
20247 papers
- MLSPJoint Optimization of Piecewise Linear Ensembles (opens in a new tab)
- NeurIPS (T1)Label Noise: Ignorance is Bliss (opens in a new tab)
- Annals of Nuclear EnergyMultilabel Proportion Prediction and Out-of-Distribution Detection on Gamma Spectra of Short-Lived Fission Products (opens in a new tab)
- ICML (T1)Testing the Feasibility of Linear Programs with Bandit Feedback (opens in a new tab)
- NeurIPS (T1)The Implicit Bias of Gradient Descent on Separable Multiclass Data (opens in a new tab)
- JMLR (T1)Unified Binary and Multiclass Margin-Based Classification (opens in a new tab)
- 1--51Yutong Wang and Clayton Scott, ``Unified Binary and Multiclass Margin-Based Classification," Journal of Machine Learning Research, vol
Where alumni went21 listed, 44% to industry
Industry 7Academia 9
Most often to
- Microsoft
- HP Labs
Also to
- Humbolt University
- Princeton University
- Sandia National Lab
Apply to MichiganFall 2027
Michigan CSE Computer Science PhD
- Round
- Single round
- 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 and DBLP
- Members
- Lab homepage
- Alumni
- Lab homepage
Tiers are venue classifications, not lab rankings.
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