Vidya Muthukumar
20 papers · 2019–2026 · 7 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+8 more ↓ Show less ↑
π Academic Marathon (6) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (6) π Cross-Pollinator (12)
πΊοΈ
Taxonomy Completionist
(28)
π
Interdisciplinary Bridge
π§
Keyword Pioneer
β‘
Prolific Year
(6)
ποΈ
Keyword Collector
(60)
π₯
Unstoppable
(7)
π
Century Club
(19)
β
The Questioner
Conferences
NIPS (6)
AISTATS (5)
JMLR (4)
ICML (2)
ALT (1)
COLT (1)
UAI (1)
Top co-authors
Keywords
support vector machine
(3)
online learning
(2)
worst-group accuracy
(2)
implicit bia
(2)
loss function
(2)
multi-armed bandit
(2)
regret bound
(2)
spurious correlation
(2)
group robustness
(2)
model selection
(2)
binary classification
(1)
continuous optimization
(1)
class imbalance
(1)
empirical risk minimization
(1)
sample complexity
(1)
reinforcement learning
(1)
ridge regression
(1)
spectral regularization
(1)
data augmentation
(1)
gradient descent
(1)
Papers
Last-iterate Convergence for Symmetric, General-sum, $2 \times 2$ Games Under The Exponential Weights Dynamic
ALT 2026
Task Shift: From Classification to Regression in Overparameterized Linear Models
AISTATS 2025
Estimating stationary mass, frequency by frequency
COLT 2025
Improved and Oracle-Efficient Online $\ell_1$-Multicalibration
ICML 2025
General Loss Functions Lead to (Approximate) Interpolation in High Dimensions
JMLR 2025
The Group Robustness is in the Details: Revisiting Finetuning under Spurious Correlations
NIPS 2024
Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance
ICML 2024
One Shot Inverse Reinforcement Learning for Stochastic Linear Bandits
UAI 2024
The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective
JMLR 2024
Just Wing It: Near-Optimal Estimation of Missing Mass in a Markovian Sequence
JMLR 2024
Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks
NIPS 2024
Towards Last-layer Retraining for Group Robustness with Fewer Annotations
NIPS 2023
Faster Margin Maximization Rates for Generic Optimization Methods
NIPS 2023
Adaptive Oracle-Efficient Online Learning
NIPS 2022
Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation
NIPS 2021
Classification vs regression in overparameterized regimes: Does the loss function matter?
JMLR 2021
On the proliferation of support vectors in high dimensions
AISTATS 2021
Online Model Selection for Reinforcement Learning with Function Approximation
AISTATS 2021
OSOM: A simultaneously optimal algorithm for multi-armed and linear contextual bandits
AISTATS 2020
Best of many worlds: Robust model selection for online supervised learning
AISTATS 2019