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].
Near-Optimal Design of Experiments via Regret Minimization
Authors: Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang
ICML 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Numerical results on synthetic and real-world design problems verify the practical effectiveness of the proposed algorithm. |
| Researcher Affiliation | Collaboration | 1Microsoft Research, Redmond, USA 2Princeton University, Princeton, USA 3Carnegie Mellon University, Pittsburgh, USA. |
| Pseudocode | Yes | In Algorithm 1 we give a pseducode description of the algorithm, which makes use of a binary search routine (Algorithm 2) that ๏ฌnds the unique constant ct for which tr(At) = tr[(ct I + P i ฮt 1 xix i ) 2] = 1. |
| Open Source Code | No | The paper states that algorithms are implemented in MATLAB and C, but does not provide any links or explicit statements about the availability of the source code for the described methodology. |
| Open Datasets | No | For the |
| Dataset Splits | No | The paper does not specify explicit training, validation, or test dataset splits. |
| Hardware Specification | No | The paper mentions that algorithms are implemented in MATLAB and C, but does not specify any hardware details such as CPU, GPU models, or memory. |
| Software Dependencies | No | The paper states that algorithms are implemented in MATLAB and C, but does not provide specific version numbers for these environments or any other software libraries. |
| Experiment Setup | Yes | The maximum number of iterations T for Fedorov s exchange is set at T = 100. We always set k = r in the optimization problem Eq. (6)... In Algorithm 1 we set ฮฑ = 10; our similuations suggest that the algorithm is not sensitive to ฮฑ. |