Oracle Complexity of Second-Order Methods for Finite-Sum Problems

Authors: Yossi Arjevani, Ohad Shamir

ICML 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical In this paper, we consider the opposite direction, and study lower bounds on the number of iterations required by algorithms using second-order (or possibly even higher-order) information, focusing on finite-sum problems which are strongly-convex and smooth.
Researcher Affiliation Academia 1Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.
Pseudocode No The paper describes algorithmic concepts and constructions but does not provide any pseudocode or clearly labeled algorithm blocks.
Open Source Code No The paper does not contain any statement about releasing source code or a link to a code repository for the methodology described.
Open Datasets No The paper is theoretical, analyzing oracle complexity and lower bounds using constructed functions (e.g., quadratic functions in Theorem 2). It does not use real-world datasets for training or experimentation.
Dataset Splits No As a theoretical paper, it does not involve empirical evaluation on datasets with training, validation, or test splits.
Hardware Specification No The paper is theoretical and does not mention any specific hardware used for computations or experiments.
Software Dependencies No The paper is theoretical and does not mention any specific software dependencies or version numbers.
Experiment Setup No The paper is theoretical and does not describe an experimental setup, including hyperparameters or system-level training settings.