Universal Rates for Interactive Learning
Authors: Steve Hanneke, Amin Karbasi, Shay Moran, Grigoris Velegkas
NeurIPS 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | 3. If you ran experiments... (a) Did you include the code, data, and instructions needed to reproduce the main experimental results (either in the supplemental material or as a URL)? [N/A] |
| Researcher Affiliation | Collaboration | Steve Hanneke Purdue University steve.hanneke@gmail.com Amin Karbasi Yale University, Google Research amin.karbasi@yale.edu Shay Moran Technion, Google Research smoran@technion.ac.il Grigoris Velegkas Yale University grigoris.velegkas@yale.edu |
| Pseudocode | Yes | Figure 2: Arbitrarily Fast Rates Algorithm; Figure 3: Interactive Learning with Partial Concept Classes; Figure 4: Exponential Rates Algorithm; Figure 5: Aggregate Function Subroutine |
| Open Source Code | No | 3. If you ran experiments... (a) Did you include the code, data, and instructions needed to reproduce the main experimental results (either in the supplemental material or as a URL)? [N/A] |
| Open Datasets | No | The paper describes a theoretical framework involving 'unlabeled data points from X that are drawn i.i.d. from PX' as part of its model, but does not refer to specific publicly available datasets or provide access information for empirical training data. |
| Dataset Splits | No | The paper is purely theoretical and does not involve empirical experiments or dataset evaluations, thus no validation dataset splits are provided. |
| Hardware Specification | No | The paper is theoretical and does not conduct empirical experiments, therefore no hardware specifications are mentioned. The reproducibility checklist states N/A for hardware. |
| Software Dependencies | No | The paper is theoretical and does not conduct empirical experiments, therefore no specific software dependencies with version numbers are mentioned. The reproducibility checklist states N/A for software. |
| Experiment Setup | No | The paper is purely theoretical and does not include empirical experiments, thus no experimental setup details like hyperparameters or training configurations are provided. |