Abstract: The Johnson-Lindenstrauss (JL) lemma, with known probability, sets a lower bound q0 on the dimension for which a random projection of p-dimensional vector data is guaranteed to be within (1±ε) of being an isometry in a randomly projected downspace.… Read More
Tag: clustering
Partial Membership Latent Dirichlet Allocation
Abstract: For many years, topic models (e.g., pLSA, LDA, SLDA) have been widely used for segmenting and recognizing objects in imagery simultaneously. However, these models are confined to the analysis of categorical data, forcing a visual word to belong to… Read More
Bayesian fuzzy clustering
Abstract: We present a Bayesian probabilistic model and inference algorithm for fuzzy clustering that provides expanded capabilities over the traditional Fuzzy C-Means approach. Additionally, we extend the Bayesian Fuzzy Clustering model to handle a variable number of clusters and present… Read More