Christopher Liaw
14 papers · 2017–2025 · 7 venues · across top CS/AI venues
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Research topics
Machine Learning
(14)
Optimization & Theory
(11)
Mathematics & Optimization
(9)
Optimization
(7)
Learning Types
(6)
Artificial Intelligence
(4)
Application Areas
(4)
Core Methods
(4)
Deep Learning
(2)
Security & Privacy
(2)
Architectures
(2)
Bayesian & Probabilistic
(2)
Core AI
(2)
Differential Privacy
(2)
Mathematics
(2)
Keywords
sample complexity
(4)
differential privacy
(4)
learning theory
(3)
distribution learning
(2)
neural network
(2)
density estimation
(2)
gaussian mixture
(2)
online algorithm
(2)
gaussian distribution
(2)
multi-armed bandit
(2)
gaussian mixture model
(2)
mixture of gaussian
(2)
total variation distance
(2)
regret bound
(2)
online learning
(2)
statistical estimation
(1)
piecewise linear
(1)
stochastic gradient descent
(1)
nash equilibrium
(1)
mechanism design
(1)
Papers
Agnostic Private Density Estimation for GMMs via List Global Stability
ALT 2025
Continuous Prediction with Experts' Advice
JMLR 2024
Mixtures of Gaussians are Privately Learnable with a Polynomial Number of Samples
ALT 2024
Improved Online Learning Algorithms for CTR Prediction in Ad Auctions
ICML 2023
Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models
ICML 2023
Private and polynomial time algorithms for learning Gaussians and beyond
COLT 2022
Convergence Analysis of No-Regret Bidding Algorithms in Repeated Auctions
AAAI 2021
Privately Learning Mixtures of Axis-Aligned Gaussians
NeurIPS 2021
Improved Algorithms for Online Submodular Maximization via First-order Regret Bounds
NeurIPS 2020
A new dog learns old tricks: RL finds classic optimization algorithms
ICLR 2019
Nearly-tight VC-dimension and Pseudodimension Bounds for Piecewise Linear Neural Networks
JMLR 2019
Tight analyses for non-smooth stochastic gradient descent
COLT 2019
Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes
NeurIPS 2018
Nearly-tight VC-dimension bounds for piecewise linear neural networks
COLT 2017