[Github]
Generative clustering (model the categories via statistical data of input)
K-means | Gaussian mixture
Discriminative clustering (directly identify categories)
[Pytorch Forum for Clustering Loss]
Information theoretical | max-margin | spectral graph
- Xie, Junyuan, Ross Girshick, and Ali Farhadi. "Unsupervised deep embedding for clustering analysis." International conference on machine learning. 2016.
- utilize KL-divergence to approximate clustering loss
- model prob by student t-distribution (t-sne) "standard"
- Guo, Xifeng, et al. "Improved Deep Embedded Clustering with Local Structure Preservation." IJCAI. 2017.
- Add a reconstruction loss based on (1)
- Yazhou Ren, Kangrong Hu, Xinyi Dai, Lili Pan, Steven C. H. Hoi, Zenglin Xu: Semi-supervised deep embedded clustering. Neurocomputing 325: 121-130 (2019) [pdf]
- extend to semi-supervised setting
- Only add a affinity constraint for labeled data.
- Ghasedi Dizaji, Kamran, et al. "Deep clustering via joint convolutional autoencoder embedding and relative entropy minimization." Proceedings of the IEEE International Conference on Computer Vision. 2017. [pdf] [code]
- a multi-nominal logistic regression (softmax)
- relative entropy (KL divergence) minimization
- Peng, Xi, et al. "Cascade subspace clustering." Thirty-First AAAI Conference on Artificial Intelligence. 2017. [pdf]
- **Clustering -> Verification**x; Assumption: the distribution between a given sample x and cluster centers Y is invariant to different distance metrics on the manifold, where each distribution is defined as probability map (i.e., soft-assignment) between x and Y.
- use two metrics to constrain (Euclidean & cosine)
- Lin et al. "Jointly Deep Multi-View Learning for Clustering " arxiv, 2018 [pdf]
- multi-view branches -> fusion (q) -> target p -> KL divergence
- Tian, Fei, et al. "Learning deep representations for graph clustering." Twenty-Eighth AAAI Conference on Artificial Intelligence. 2014. [pdf]
- auto-encoder to learn low dimensional features of original graph; k-means
- Chen, Gang. "Deep learning with nonparametric clustering." arXiv preprint arXiv:1501.03084 (2015). [pdf]
- Deep Belief Network (DBN)
- Peng, Xi, et al. "Deep Subspace Clustering with Sparsity Prior." IJCAI. 2016. [pdf]
- Caron, Mathilde, et al. "Deep clustering for unsupervised learning of visual features." Proceedings of the European Conference on Computer Vision (ECCV). 2018. [pdf] [code]