Multi-view Self-Paced Learning for Clustering

Authors: Chang Xu, Dacheng Tao, Chao Xu

IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental Experimental results on toy and real-world data demonstrate the efficacy of the proposed algorithm.
Researcher Affiliation Academia Key Lab. of Machine Perception (Ministry of Education) Peking University, Beijing 100871, China Centre for Quantum Computation and Intelligent Systems University of Technology, Sydney 2007, Australia
Pseudocode No The paper describes the optimization steps and equations, but does not include formal pseudocode or an algorithm block.
Open Source Code No The paper does not provide any explicit statement or link regarding the availability of its source code.
Open Datasets Yes The Handwritten Numerals dataset is composed of 2000 examples from 0 to 9 ten-digit classes. Six kinds of features are used to represent each example... The Animal with attribute dataset contains 30475 examples from 50 classes and described by six features...
Dataset Splits No The paper references datasets used but does not specify any explicit training, validation, or test dataset splits.
Hardware Specification No The paper does not specify any hardware details (e.g., CPU, GPU models, memory) used for running the experiments.
Software Dependencies No The paper does not mention any specific software dependencies or their version numbers.
Experiment Setup Yes The initial λ is set such that more than half of examples (views) are selected, and then it is iteratively decreased.