Courtney Paquette
10 papers · 2018–2025 · 4 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+2 more ↓ Show less ↑
🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (18) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Bronze ❓ The Questioner
💎
Century Club · Bronze
🗃️
Keyword Collector
(54)
Venues
Top co-authors
Research topics
Machine Learning
(10)
Optimization & Theory · Machine Learning
(10)
Mathematics & Optimization
(6)
Optimization
(4)
Deep Learning
(3)
Mathematics
(3)
Optimization & Theory · Deep Learning
(2)
Security & Privacy
(1)
Application Areas
(1)
Bayesian & Probabilistic
(1)
Core Methods
(1)
Differential Privacy
(1)
Models
(1)
Keywords
stochastic gradient descent
(5)
random matrix theory
(2)
momentum method
(2)
convergence rate
(2)
convex optimization
(2)
least square
(2)
average-case analysis
(2)
nesterov acceleration
(2)
convergence analysis
(1)
mirror descent
(1)
stochastic gradient
(1)
implicit differentiation
(1)
adaptive learning rate
(1)
mini-batch optimization
(1)
stochastic convex optimization
(1)
high-dimensional analysis
(1)
non-convex optimization
(1)
saddle-point problems
(1)
phase transition
(1)
gradient descent
(1)
Papers
Implicit Diffusion: Efficient optimization through stochastic sampling
AISTATS 2025
4+3 Phases of Compute-Optimal Neural Scaling Laws
NeurIPS 2024
Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems extended abstract
COLT 2024
The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms
NeurIPS 2024
Implicit Regularization or Implicit Conditioning? Exact Risk Trajectories of SGD in High Dimensions
NeurIPS 2022
Only tails matter: Average-Case Universality and Robustness in the Convex Regime
ICML 2022
Trajectory of Mini-Batch Momentum: Batch Size Saturation and Convergence in High Dimensions
NeurIPS 2022
Dynamics of Stochastic Momentum Methods on Large-scale, Quadratic Models
NeurIPS 2021
SGD in the Large: Average-case Analysis, Asymptotics, and Stepsize Criticality
COLT 2021
Catalyst for Gradient-based Nonconvex Optimization
AISTATS 2018