Elementary Symmetric Polynomials for Optimal Experimental Design
Authors: Zelda E. Mariet, Suvrit Sra
NeurIPS 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our analysis establishes approximation guarantees on these algorithms, while our empirical results substantiate our claims and demonstrate a curious phenomenon concerning our greedy method. |
| Researcher Affiliation | Academia | Zelda Mariet Massachusetts Institute of Technology Cambridge, MA 02139 zelda@csail.mit.edu Suvrit Sra Massachusetts Institute of Technology Cambridge, MA 02139 suvrit@mit.edu |
| Pseudocode | Yes | Algorithm 1: Sample from z Data: budget k, z Rn Result: S of size k S while |S| < k do Sample i [n] \ S uniformly at random Sample x Bernoulli(z i ) if x = 1 then S S {i} return S |
| Open Source Code | No | The paper does not explicitly state that the source code for the methodology is released or provide a link to it. |
| Open Datasets | Yes | We used the Concrete Compressive Strength dataset [47] (with column normalization) from the UCI repository to evaluate ESP-design on real data; this dataset consists in 1030 possible experiments to model concrete compressive strength as a linear combination of 8 physical parameters. |
| Dataset Splits | No | The paper does not explicitly specify dataset splits like percentages or sample counts for training, validation, or test sets. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., CPU/GPU models, memory) used for running experiments. |
| Software Dependencies | No | The paper mentions using a specific code for projection: "the convex optimization was solved using projected gradient descent, the projection being done with the code from [12]". However, it does not specify software versions for this or other dependencies. |
| Experiment Setup | No | The paper does not contain specific hyperparameters, training configurations, or system-level settings for the experiments. |