Vidya K Muthukumar
Assistant Professor
Studies theory of machine learning, including overparameterized models and reinforcement learning.
Vidya K Muthukumar's lab at Georgia Tech works on reinforcement learning and learning theory & optimization. 24 papers since 2023, 15 at top venues, mostly NeurIPS and JMLR. 3 PhD students. 6 alumni, most often to AI startup OuterProduct and Microsoft. Applications close .
At a glance
- papers, 2023–2026
- 6/ year
- at T1 venues
- 63%
- PhD students
- 3
- MS students
- 0
- alumni listed
- 6
Papers by yearfrom the lab homepage, 2023–2026
- 5 papers2026 · T1 3 · collecting
- 5 papers2025 · T1 4
- 10 papers2024 · T1 6
- 4 papers2023 · T1 2
T1 venuesOtherVenues: NeurIPS, JMLR, COLT, ICML, AISTATS
Research focuspaper titles that use each topic's words
- Learning theory & optimization4 papers
- Reinforcement learning2 papers
- overparameterized1 paper
- reinforcement1 paper
- studies theory0 papers
Paper list
From the lab homepage.
20265 papers
- Information and Inference: A Journal of the IMAA general technique for approximating high-dimensional empirical kernel matrices
- COLT (T1)How Does the ReLU Activation Affect the Implicit Bias of Gradient Descent on High-Dimensional Neural Network Regression?
- ALTLast-iterate convergence for symmetric, general-sum, 2×2 games under the exponential weights dynamic
- TMLR (T1)On the Unreasonable Effectiveness of Last-Layer Retraining
- NeurIPS (T1)SGD provably prioritizes a shortcut spurious feature in the XOR model
20255 papers
- COLT (T1)Estimating stationary mass, frequency by frequency
- Mathematical Programming Series BFaster margin maximization rates for generic and adversarially robust optimization methods
- JMLR (T1)General Loss Functions Lead to (Approximate) Interpolation in High Dimensions
- ICML (T1)Improved and oracle-efficient online $\ell_1$-multicalibration
- AISTATS (T1)Task Shift: From Classification to Regression in Overparameterized Linear Models
202410 papers
- ICML (T1)Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance
- Transactions of Machine Learning ResearchEstimating optimal policy value in general linear contextual bandits
- JMLR (T1)Just Wing It: Optimal Estimation of Missing Mass in a Markovian Sequence
- SIAM Journal on Mathematics of Data ScienceNew equivalences between interpolation and SVMs: Kernels and structured features
- Mathematics of Operations ResearchOn the impossibility of convergence of strategies arising from no-regret learning
- UAI (T1)One shot inverse reinforcement learning for stochastic linear bandits
- NeurIPS (T1)Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks
- ISITSharp analysis of out-of-distribution error for “importance-weighted
- JMLR (T1)The good, bad and ugly sides of data augmentation: An implicit spectral regularization perspective
- NeurIPS (T1)The Group Robustness is in the Details: Revisiting Finetuning Under Spurious Correlations
20234 papers
- IEEE Transactions on Information TheoryBenign overfitting in multiclass classification: All roads lead to interpolation
- NeurIPS (T1)Faster margin maximization rates for generic optimization methods
- ITCSThe complexity of infinite-horizon general-sum stochastic games
- NeurIPS (T1)Towards last-layer retraining for group robustness with fewer annotations
Where alumni went6 listed, 67% to industry
Industry 2Academia 1
Most often to
- AI startup OuterProduct
- Microsoft
Also to
- UT Austin
Apply to Georgia TechFall 2027
Georgia Tech Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- optional
- English
- TOEFL/IELTS
- Fee
- See program page
Not yet confirmed for this intake.
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