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 [1].
Optimal Rates for Random Order Online Optimization
Authors: Uri Sherman, Tomer Koren, Yishay Mansour
NeurIPS 2021 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We present and analyze two algorithms for random order online optimization, the first of which obtains the optimal regret up to additive factors. Our analysis relies on novel connections between algorithmic stability and generalization for sampling without-replacement analogous to those studied in the with-replacement i.i.d. setting, as well as on a refined average stability analysis of stochastic gradient descent. |
| Researcher Affiliation | Collaboration | Uri Sherman Blavatnik School of Computer Science Tel Aviv University EMAIL. Tomer Koren Blavatnik School of Computer Science Tel Aviv University, and Google Research EMAIL. Yishay Mansour Blavatnik School of Computer Science Tel Aviv University, and Google Research EMAIL. |
| Pseudocode | Yes | Algorithm 1 Reservoir SGD |
| Open Source Code | No | The paper does not provide any statement or link regarding the public availability of its source code. |
| Open Datasets | No | The paper is theoretical and discusses a set of datapoints Z= {ζ1, . . . , ζT} without referring to a specific, publicly available dataset used for training or empirical evaluation. |
| Dataset Splits | No | The paper is theoretical and does not describe any specific training, validation, or test dataset splits. |
| Hardware Specification | No | The paper does not provide specific details about the hardware used for experiments, as it is a theoretical work. |
| Software Dependencies | No | The paper is theoretical and does not list any specific software dependencies with version numbers required to replicate experiments. |
| Experiment Setup | No | The paper is theoretical and does not provide specific details about experimental setup, hyperparameters, or training configurations. |