Martin Wainwright
Ford Professor of Engineering; Professor of Mathematics
Studies high-dimensional statistics, statistical machine learning, information theory, and optimization, including data-efficient reinforcement learning.
Martin Wainwright's lab at MIT works on learning theory & optimization, reinforcement learning and efficient training & inference. 13 papers since 2023, 3 at top venues, mostly JMLR. 41 alumni. Applications close .
At a glance
- papers, 2023–2026
- 3/ year
- at T1 venues
- 23%
- PhD students
- 0
- MS students
- 0
- alumni listed
- 41
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 0 papers2025 · T1 0
- 8 papers2024 · T1 1
- 5 papers2023 · T1 2
T1 venuesOtherVenues: JMLR
Research focuspaper titles that use each topic's words
- Learning theory & optimization2 papers
- Reinforcement learning2 papers
- Efficient training & inference2 papers
- studies high-dimensional0 papers
- data-efficient0 papers
Paper list
From the lab homepage.
20248 papers
- SIAM Journal on Math. Data Sci."A diffusion process perspective on posterior contraction rates for parameters"
- JMLR (T1)"Instability, Computational Efficiency and Statistical Accuracy"
- IEEE Trans. Info. Theory"Instance-optimality in optimal value estimation: Adaptivity via variance-reduced Q-learning"
- Annals of Statistics"Near-optimal inference in adaptive linear regression"
- Annals of Statistics"Noisy recovery from random linear observations: Sharp minimax rates under elliptical constraints"
- Mathematical Statistics and Learning"Optimal and instance-dependent guarantees for Markovian linear stochastic approximation"
- Annals of Statistics"Optimal value estimation using kernel-based temporal difference methods"
- Annals of Statistics"Semi-parametric inference based on adaptively collected data"
20235 papers
- JMLR (T1)"Instance-dependent confidence and early stopping in reinforcement learning"
- Conference on Artificial Intellgence and Statistics"Krylov-Bellman boosting: Super-linear policy evaluation in general state spaces"
- Mathematics of Operations Research"Optimal oracle inequalities for solving projected fixed-point equations"
- Annals of Statistics"Optimally tackling covariate shift in RKHS-based nonparametric regression"
- JMLR (T1)"Revisiting minimum description length complexity in overparameterized models"
Where alumni went41 listed
Apply to MITFall 2027
MIT EECS Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- See program page
- English
- TOEFL/IELTS
- Fee
- USD 90
Confirmed on the program page.
Similar labsnearest by research summary
- USMichigan
Richard Lewis
- Reinforcement learning
- CNPeking
Yinjun Wu
- Data management & big data
- USCMU
Kun Zhang
- Probabilistic & causal inference
- USCMU
Albert Gu
- Generative & foundation models
- SGNUS
Roger Zimmermann
- Time series, anomaly & spatio-temporal data
- CNZhejiang
Lei Cheng
- Learning theory & optimization
Your notes
Save this lab to keep notes.
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.
MITcloses