Capturing Individuality and Commonality Between Anchor Graphs for Multi-View Clustering
Authors: Zhoumin Lu, Yongbo Yu, Linru Ma, Feiping Nie, Rong Wang
IJCAI 2025 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Comprehensive experiments demonstrate the effectiveness and efficiency of our method compared to various state-of-the-art algorithms. Our experiments employ 9 public datasets for comparison, including 3Sources, Web KB, NUS-WIDE, Notting Hill, Cifar10, Cifar100, You Tube Face10, You Tube Face20 and You Tube Face50. |
| Researcher Affiliation | Academia | 1School of Computer Science, School of Artificial Intelligence, OPtics and Electro Nics (i OPEN), Northwestern Polytechnical University, Xi an 710072, China. 2Institute of Systems Engineering, AMS, Beijing 100071, China. |
| Pseudocode | Yes | Algorithm 1 CICAG Solver Input: Dataset {X(i)}v i=1, anchor number m, cluster number c, and parameters α, β and γ. Output: Learned anchor graph Z . 1: Initialize Z(i), Z and F . 2: while non-convergence do 3: Update A(i) by Theorem 1. 4: Update Z(i) by Theorem 2. 5: Update Z by Theorem 3. 6: end while 7: Obtain Z by Equation (36). |
| Open Source Code | No | The paper does not contain any explicit statement about providing open-source code for the methodology or a link to a code repository. |
| Open Datasets | Yes | Our experiments employ 9 public datasets for comparison, including 3Sources, Web KB, NUS-WIDE, Notting Hill, Cifar10, Cifar100, You Tube Face10, You Tube Face20 and You Tube Face50. |
| Dataset Splits | No | The paper mentions using 9 public datasets but does not explicitly provide details about training/test/validation splits, sample counts for each split, or references to predefined splits for reproducibility. |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., CPU, GPU models, memory) used to run the experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies, such as programming languages, libraries, or frameworks with their version numbers. |
| Experiment Setup | Yes | For our model, α is set to 0.1, while the remaining hyperparameters are tuned by a grid search, whose ranges are m {1c, 3c, 5c}, β {0.001, 0.01, , 100, 1000}, and γ {0.001, 0.01, , 100, 1000}. |