Paul Valiant
9 papers · 2013–2026 · 3 venues · across top CS/AI venues
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Achievements
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π Conference Polyglot Β· Bronze π Academic Marathon Β· Half π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (18) π£ Hot Topic Early Bird
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Research topics
Machine Learning
(7)
Mathematics & Optimization
(7)
Mathematics
(7)
Optimization & Theory Β· Machine Learning
(7)
Deep Learning
(3)
Architectures
(3)
Optimization & Theory Β· Deep Learning
(2)
Computer Science
(1)
Core Methods
(1)
Foundations
(1)
Learning Types
(1)
Optimization
(1)
Probability
(1)
Statistics
(1)
Keywords
statistical estimation
(3)
worst-case analysis
(2)
location estimation
(2)
minimax optimality
(2)
asymptotic normality
(2)
outlier robustness
(1)
sample complexity
(1)
parameter estimation
(1)
maximum likelihood
(1)
cramer-rao bound
(1)
fisher information
(1)
robust statistics
(1)
contamination model
(1)
linear regression
(1)
approximation error
(1)
maximum likelihood estimation
(1)
mean estimation
(1)
entropy estimation
(1)
function approximation
(1)
conformal prediction
(1)
Papers
The Median is Easier than it Looks: Approximation with a Constant-Depth, Linear-Width ReLU Network
COLT 2026
All-Purpose Mean Estimation over R: Optimal Sub-Gaussianity with Outlier Robustness and Low Moments Performance
ICML 2025
Depth Separations in Neural Networks: Separating the Dimension from the Accuracy
COLT 2025
Minimax-Optimal Location Estimation
NeurIPS 2023
Optimality in Mean Estimation: Beyond Worst-Case, Beyond Sub-Gaussian, and Beyond 1+Ξ± Moments
NeurIPS 2023
Finite-Sample Maximum Likelihood Estimation of Location
NeurIPS 2022
Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process
COLT 2020
Worst-Case Analysis for Randomly Collected Data
NeurIPS 2020
Estimating the Unseen: Improved Estimators for Entropy and other Properties
NeurIPS 2013