Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier

Authors: Jacob Abernethy, Elad Hazan

ICML 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental This mathematical equivalence is demonstrated in figure 3 generated by simulation over a polytope.
Researcher Affiliation Academia Jacob Abernethy JABERNET@UMICH.EDU Computer Science & Engineering, University of Michigan Elad Hazan EHAZAN@PRINCETON.EDU Department of Computer Science, Princeton University
Pseudocode Yes Algorithm 1 HITANDRUN( , OK, N, , X0), Algorithm 2 SIMULATEDANNEALING WITH HITANDRUN Kalai & Vempala (2006), Algorithm 3 ITERATIVENEWTONSTEP
Open Source Code No The paper does not provide any explicit statements or links indicating that the source code for the described methodology is publicly available.
Open Datasets No The paper describes theoretical algorithms and mathematical equivalences, not experiments conducted on specific public datasets. Figure 3 is a simulation for illustration, not based on a publicly accessible training dataset.
Dataset Splits No The paper does not describe any specific training, validation, or test dataset splits, as it focuses on theoretical analysis and algorithmic properties rather than empirical data validation.
Hardware Specification No The paper does not provide any specific details regarding the hardware used for computations or experiments.
Software Dependencies No The paper discusses algorithms and mathematical frameworks but does not specify any software dependencies (e.g., libraries, programming languages, or solvers) with version numbers.
Experiment Setup No The paper describes algorithmic details and theoretical parameters (e.g., temperature schedules) as part of its mathematical analysis, but it does not provide specific experimental setup details such as hyperparameters, optimization settings, or training configurations for an empirical study.