Hubness Change Point Detection
Authors: Ikumi Suzuki, Kazuo Hara, Eiji Murakami
AAAI 2025 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments with synthetic data show that the proposed method achieves accuracy comparable to or exceeding that of existing methods. Additionally, the proposed method achieves good accuracy with real-world data from hydraulic systems and gas sensors, along with excellent runtime performance. |
| Researcher Affiliation | Collaboration | Ikumi Suzuki1, Kazuo Hara1, Eiji Murakami2 1Yamagata University 2Azbil Kimmon Co.,Ltd., Keio University EMAIL, EMAIL, EMAIL |
| Pseudocode | Yes | Algorithm 1: Residual Normalization Algorithm 2: Proposed Hub-CPD Algorithm |
| Open Source Code | Yes | The Appendix and code are available at https://analogy.sakura.ne.jp/AAAI25/appendix.pdf and https://analogy.sakura.ne.jp/AAAI25/code and data.zip. |
| Open Datasets | Yes | real-world data from hydraulic systems and gas sensors (Helwig and Eliseo Pignanelli 2015)2 and the concentration changes of carbon monoxide detected by gas sensors (Burgu es, Jim enez-Soto, and Marco 2018).3 2https://archive.ics.uci.edu/dataset/447 3https://archive.ics.uci.edu/dataset/487 |
| Dataset Splits | No | The parameters of the change detection methods were determined using validation data. The paper discusses data generation and evaluation points but does not specify explicit train/test/validation percentages, sample counts, or a detailed splitting methodology for reproducibility beyond this general statement. |
| Hardware Specification | Yes | The execution was performed on an Intel Xeon Gold 6134 CPU with 526GB RAM and an NVIDIA Quadro P5000 GPU with 16GB SGRAM. KL-CPD was run using GPU. |
| Software Dependencies | No | Ru LSIF was run using MATLAB s built-in multithreading. No specific version numbers for MATLAB or other key software components used in the proposed method's implementation are provided in the main text. |
| Experiment Setup | Yes | Algorithm 2: Proposed Hub-CPD Algorithm Input: D = {v1, . . . , vn}, D = {v 1, . . . , v n}, k, r. The paper explicitly lists 'k' and 'r' as input parameters for the proposed algorithm and discusses their impact in the results section, for example, 'the r = 1 and r = 2 variants' and 'The behavior with respect to k differs'. |