AbstractJoint 2D cardiac segmentation and 3D volume reconstruction are fundamental in building statistical anatomy models understanding functional mechanisms from motion patterns. However, due to the low through-plane resolution of cine MR high inter-subject variance, accurately segmenting images reconstructing challenging. In this study, we propose an end-to-end latent-space-based framework, D...

Users of social networking services can connect with each other by forming communities for online interaction. Yet as the number of communities hosted by such websites grows over time, users have even greater need for effective community recommendations in order to meet more users. In this paper, we investigate two algorithms from very different domains and evaluate their effectiveness for pers...

Recently, Local Matrix Factorization (LMF) [Lee et al., 2013] has been shown to be more effective than traditional matrix factorization for rating prediction. The core idea for LMF is to first partition the original matrix into several smaller submatrices, further exploit local structures of submatrices for better low-rank approximation. Various clustering-based methods with heuristic extension...

Despite the effectiveness of highly active antiretroviral therapy (HAART) in treating individuals infected with HIV, HAART is not a cure. A latent reservoir, composed mainly of resting CD4+T cells, drives viral rebound once therapy is stopped. Understanding the formation and maintenance of latently infected cells could provide clues to eradicating this reservoir. However, there have been discre...

1077-3142/$ see front matter 2010 Elsevier Inc. A doi:10.1016/j.cviu.2010.04.006 * Corresponding author. E-mail addresses: [email protected] (J. (S. Gong). Temporal dependency is a very important cue for modeling human actions. However, approaches using latent topics models, e.g., probabilistic latent semantic analysis (pLSA), employ the bag of words assumption therefore word dependencies ...

To tackle a multi-label classification problem with many classes, recently label space dimension reduction (LSDR) is proposed. It encodes the original label space to a low-dimensional latent space and uses a decoding process for recovery. In this paper, we propose a novel method termed FaIE to perform LSDR via Feature-aware Implicit label space Encoding. Unlike most previous work, the proposed ...

Neural circuits contain heterogeneous groups of neurons that differ in type, location, connectivity, and basic response properties. However, traditional methods for dimensionality reduction and clustering are ill-suited to recovering the structure underlying the organization of neural circuits. In particular, they do not take advantage of the rich temporal dependencies in multi-neuron recording...

Many machine learning problems inherently involve multiple views. Kernel combination approaches to multiview learning [1] are particularly effective when the views are independent. In contrast, other methods take advantage of the dependencies in the data. The best-known example is Canonical Correlation Analysis (CCA), which learns latent representations of the views whose correlation is maximal...

Industry classification is a crucial step for financial analysis. However, existing industry classification schemes have several limitations. In order to overcome these limitations, in this paper, we propose an industry classification methodology on the basis of business commonalities using the topic features learned by the Latent Dirichlet Allocation (LDA) from firms’ business descriptions. Tw...