Learning User Perceived Clusters with Feature-Level Supervision
Authors: Ting-Yu Cheng, Guiguan Lin, xinyang gong, Kang-Jun Liu, Shan-Hung (Brandon) Wu
NeurIPS 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The figures display performance comparisons of different methods like OKM, OKM*, OKM*+LPE, and OKM*+NPE with y-axis values ranging from 0 to 1. This implies empirical evaluation and data analysis. |
| Researcher Affiliation | Academia | No author affiliations, university names, company names, or email domains are provided in the given text snippet. |
| Pseudocode | No | No structured pseudocode or algorithm blocks are present in the provided text. |
| Open Source Code | No | No concrete access information (specific repository link, explicit code release statement, or code in supplementary materials) for source code is provided in the text. |
| Open Datasets | No | No concrete access information (specific link, DOI, repository name, formal citation, or reference to established benchmark datasets) for a publicly available dataset is provided in the text. |
| Dataset Splits | No | No specific dataset split information (percentages, sample counts, citations to predefined splits, or detailed splitting methodology) is provided in the text. |
| Hardware Specification | No | No specific hardware details (exact GPU/CPU models, processor types, memory amounts, or detailed computer specifications) used for running experiments are provided in the text. |
| Software Dependencies | No | No specific ancillary software details (library or solver names with version numbers) needed to replicate the experiment are provided in the text. |
| Experiment Setup | No | No specific experimental setup details (concrete hyperparameter values, training configurations, or system-level settings) are provided in the text. |