Optimal Sequential Maximization: One Interview is Enough!
Authors: Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati
ICML 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | 4. Experiments In this section, we compare the performance of various sequential maximization algorithms SEQELIMINATE (Falahatgar et al., 2017a), AGNOSTIC-SEQ and OPT-AGNOSTIC-SEQ. |
| Researcher Affiliation | Collaboration | 1Apple Inc. 2University of California, San Diego. |
| Pseudocode | Yes | Algorithm 1 ASYMMETRIC-THRESHOLD (A-T), Algorithm 2 OPTIMAL-SEQUENTIAL (O-S), Algorithm 3 OPT-ANCHOR-UPDATE, Algorithm 4 OPT-AGNOSTIC-SEQ |
| Open Source Code | No | The paper does not provide any specific links to source code repositories or explicit statements indicating the availability of the code for its described methodology. |
| Open Datasets | No | The paper describes generating data based on models (e.g., 'all items are essentially equal i.e., pi,j = 1/2 i, j' and 'pi,j = 0.6 i < j') for its experiments. It does not mention using or providing access information for any publicly available or open dataset. |
| Dataset Splits | No | The paper describes experiments on synthetic data models and does not provide specific train/validation/test dataset splits, percentages, or absolute sample counts required for reproduction. |
| Hardware Specification | No | The paper does not provide any specific details regarding the hardware (e.g., GPU/CPU models, memory) used to conduct the experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers (e.g., Python, PyTorch, CPLEX versions). |
| Experiment Setup | Yes | In all the experiments in this section, we try to find an 0.05-maximum with δ = 0.1. All results are averaged over 100 runs. and We first consider the model where all items are essentially equal i.e., pi,j = 1/2 i, j. and We now consider the model where pi,j = 0.6 i < j |