Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Faster Algorithms for User-Level Private Stochastic Convex Optimization
Authors: Andrew Lowy, Daogao Liu, Hilal Asi
NeurIPS 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | This is a theoretical paper without experiments. |
| Researcher Affiliation | Collaboration | Andrew Lowy Wisconsin Institute for Discovery University of Wisconsin-Madison EMAIL; Daogao Liu Department of Computer Science University of Washington EMAIL; Hilal Asi Apple Machine Learning Research EMAIL |
| Pseudocode | Yes | Algorithm 1: User-Level DP Phased SGD with Outlier Iterate Removal and Output Perturbation; Algorithm 2: User-Level DP Accelerated Minibatch SGD( b Fi, Ti, Ki, xi 1, τ, ε, δ); Algorithm 3: User-Level DP Accelerated Phased ERM with Outlier Gradient Removal |
| Open Source Code | No | This is a theoretical paper without experiments. The paper does not provide any statement about releasing source code for the described methodology. |
| Open Datasets | No | This is a theoretical paper without experiments. The paper does not perform experiments on specific datasets. |
| Dataset Splits | No | This is a theoretical paper without experiments. The paper does not perform experiments, hence no dataset splits are provided. |
| Hardware Specification | No | This is a theoretical paper without experiments. The paper does not describe hardware used for experiments. |
| Software Dependencies | No | This is a theoretical paper without experiments. The paper does not list specific software dependencies with version numbers for experimental replication. |
| Experiment Setup | No | This is a theoretical paper without experiments. The paper does not provide specific experimental setup details such as hyperparameter values. |