The idea is based on discovering common characteristics shared among subsets of images by posing a method that is able to organise the data while eliminating irrelevant instances. We propose a novel clustering and outlier detection method, namely Concept Map (CMAP). Given an image collection ...
Dynamic Clustering Forest (DCF) is a statistical based method Song et al., 2016. It deals with concept drift over the data stream. This method constructs several clustering trees (CTs). Each CT represents the different concepts of the data stream. Here, DCF uses two approaches, namely Discrim...
In the case of real-world data streams, the underlying data distribution will not be static; it is subject to variation over time, which is known as the primary reason for concept drift. Concept drift poses severe problems to the accuracy of a model in o
Title: Incremental classification and clustering, concept drift, novelty detection, active learning in big/fast data context Description: The development of dynamic information analysis methods, like incremental classification/clustering, concept drift management novelty detection techniques and active learning i...
FCA has also been applied to text mining for discovering important themes and topics from large document collections. The identification of relevant concepts provides insights about the underlying structure of the data, which in turn helps develop more accurate document clustering and classification ...
23rd IEEE International Conference on Data Mining (ICDM 2023) Title: Incremental classification and clustering, concept drift, novelty detection, active learning in big/fast data context Acronym: IncrLearn Duration: One day Description: The development of dynamic information analysis methods, like ...
clustering [16,21] or NNs [9], which, however, pose additional requirements to the labels. Unsupervised approaches require no concept labels at all, like ICE [50] that applies matrix factorization to the latent space. Alternatives relying on intelligent choice of concept candidate patches [11,...
2003. Privacy-preserving K-means clustering over vertically partitioned data. In Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’03). ACM, New York, NY, 206–215. DOI:https://doi.org/10.1145/956750.956776 [64] Jaideep Vaidya and Chris ...
5 FEDERATED LEARNING AND DATA ALLIANCE OF ENTERPRISES 联邦学习不仅是一种技术标准,也是一种商业模式。当人们意识到大数据的影响时,他们首先想到的是将数据聚合在一起,通过远程处理器计算模型,然后下载结果供进一步使用。云计算就是在这种需求下产生的。然而,随着数据隐私和数据安全的重要性越来越高,以及公司利润与其...
the structure of large-scale space. This approach is proposed to solve theSLAMtask in an environment with multiple nested large-scale loops.Cebollada, Payá, Mayol et al. (2019)propose a study aboutclustering methodsto carry out efficiently thedata compactionof metric and topological maps based ...