Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond
Authors: Maria-Florina F. Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik
NeurIPS 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | These papers are applied, whereas we focus on providing theoretical guarantees. |
| Researcher Affiliation | Collaboration | Maria-Florina Balcan School of Computer Science Carnegie Mellon University ninamf@cs.cmu.edu Siddharth Prasad Computer Science Department Carnegie Mellon University sprasad2@cs.cmu.edu Tuomas Sandholm Computer Science Department Carnegie Mellon University Optimized Markets, Inc. Strategic Machine, Inc. Strategy Robot, Inc. sandholm@cs.cmu.edu Ellen Vitercik EECS Department UC Berkeley vitercik@berkeley.edu |
| Pseudocode | Yes | Algorithm 1 Tree search |
| Open Source Code | No | The paper does not provide any links to or explicit statements about the availability of open-source code for the methodology or work described in this paper. |
| Open Datasets | No | The paper mentions examples like "Combinatorial Auctions Test Suite [30]" used for illustration in Figure 1. It also refers to "a distribution over IPs" for theoretical analysis. However, it does not provide concrete access information (link, DOI, repository, or formal citation with authors/year) to a publicly available dataset used for empirical training or evaluation. |
| Dataset Splits | No | As this is a theoretical paper, it does not describe empirical experiments involving dataset splits for training, validation, or testing. |
| Hardware Specification | No | As this is a theoretical paper focusing on mathematical proofs and bounds, it does not describe any experimental setup that would require hardware specifications. |
| Software Dependencies | No | The paper mentions SCIP [16] as an example of a leading open-source IP solver, but it does not list it as a specific software dependency with a version number for the paper's own theoretical work or any described experiments. |
| Experiment Setup | No | As this is a theoretical paper, it does not describe an empirical experimental setup with hyperparameters, training configurations, or system-level settings. |