Crowdsourced Clustering: Querying Edges vs Triangles
Authors: Ramya Korlakai Vinayak, Babak Hassibi
NeurIPS 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In addition to theoretical justification, through several simulations and experiments on two real data sets on Amazon Mechanical Turk, we empirically demonstrate that, for a fixed budget, triangle queries uniformly outperform edge queries. |
| Researcher Affiliation | Academia | Ramya Korlakai Vinayak Department of Electrical Engineering Caltech, Pasadena ramya@caltech.edu Babak Hassibi Department of Electrical Engineering Caltech, Pasadena hassibi@systems.caltech.edu |
| Pseudocode | No | The paper describes algorithms but does not provide structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link indicating that the source code for the described methodology is publicly available. |
| Open Datasets | Yes | 1. Dogs3 dataset has images of the following 3 breeds of dogs from the Stanford Dogs Dataset [28]: Norfolk Terrier (172), Toy Poodle (150) and Bouvier des Flanders (151), giving a total of 473 dogs images. ... 2. Birds5 dataset has 5 bird species from CUB-200-2011 dataset [29]: Laysan Albatross (60), Least Tern (60), Artic Tern (58), Cardinal (57) and Green Jay (57). |
| Dataset Splits | No | The paper does not explicitly provide training/test/validation dataset splits (percentages, counts, or specific methodology) for their experiments. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., CPU/GPU models, memory, or cloud instance types) used for running its experiments. |
| Software Dependencies | No | The paper mentions software components and algorithms (e.g., k-means, Spectral Clustering, Amazon Mechanical Turk) but does not provide specific version numbers for any software dependencies. |
| Experiment Setup | Yes | We run the improved convex program (4.1) by setting λ = 1/ n. ... For edge queries, each HIT (Human Intelligence Task) has 30 queries of random pairs... For triangle queries, each HIT has 20 queries, with each query having 3 random images. |