Wu C, Khan Z, Ioannidis S, et al. Deep Kernel Learning for Clustering[C]//Proceedings of the 2020 SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics, 2020: 640-648. 摘要翻译 论文提出了一种深度学习方法来发现核(kernels),用于识别样本数据上的类簇。 所...
North American Chapter of the Association for Computational LinguisticsArroyo-Ferna´ndez, I.: Learning kernels for semantic clustering: A deep approach. In: NAACL-HLT 2015 Student Research Workshop (SRW). pp. 79-87 (2015)Arroyo-Ferna´ndez I. Learning kernels for semantic clustering: A ...
Single-cell RNA sequencing (scRNA-seq) can characterize cell types and states through unsupervised clustering, but the ever increasing number of cells and batch effect impose computational challenges. We present DESC, an unsupervised deep embedding algor
ECCV2018的一篇文章,即,"Deep CLustering for Unsupervised Learning of Visual Features". 这篇文章是 Facebook AI Research 的工作,文章开始说,仅仅随机初始参数的 ConvNet 就能在ImageNet上有12%的准确率,那么,采用适当的无监督训练,应该也能学到不错的参数。其主要贡献是提出了一个end-to-end 的深度聚类学习...
learning a good representation from noisy datasets. Here, we apply the denoising autoencoder to map the preprocessed read counts to a low dimensional embedded space to carry out clustering. Formally, denoting the preprocessed input as\({\tilde{\boldsymbol{X}}}\), the input for denoising auto...
约束潜在空间的表示:memory banks, clustering, and features modeling 记忆模块: 记忆模块是一个矩阵,其中每个元素与字典学习中的单词相似,能够编码无缺陷的样本特征。训练阶段只有有限的单词用于重建,使得每个矩阵元素表示每一行。正常样本被索引到最具可比性的元素进行重建,而异常样本和重建之间的差异被放大为异常分数。
A New Design of Iris Recognition Using Hough Transform with K-Means Clustering and Enhanced Faster R-CNN Iris recognition method is the most significant biometric modality for human identification. Currently, multiple deep structured architectures have been em... G Babu,AK Pinjari - 《Cybernetics &...
An Attention-based Collaboration Framework for Multi-View Network Representation Learning Meng Qu, Jian Tang, Jingbo Shang, Xiang Ren, Ming Zhang, Jiawei Han CIKM 2017 Multi-view Clustering with Graph Embedding for Connectome Analysis Guixiang Ma, Lifang He, Chun-Ta Lu, Weixiang Shao, Philip S...
CNN are widely used for image classification, image clustering and object detection in images. They are also employed for optical character recognition and natural language processing. Apart from images, when represented visually as a spectrogram, CNNs can also be applied to sound. Also, CNNs has...
Here, we develop a novel multimodal deep learning method, scMDC, for single-cell multi-omics data clustering analysis. scMDC is an end-to-end deep model that explicitly characterizes different data sources and jointly learns latent features of deep embedding for clustering analysis. Extensive ...