Search Results for author:
Found 5 papers, 0 papers with code
Dynamic User Segmentation and Usage Profiling
In this work, we propose a clustering strategy of such categorical big data, utilizing the hidden sparsity of the dataset.
FairMixRep : Self-supervised Robust Representation Learning for Heterogeneous Data with Fairness constraints
Representation Learning in a heterogeneous space with mixed variables of numerical and categorical types has interesting challenges due to its complex feature manifold.
Learning Representation for Mixed Data Types with a Nonlinear Deep Encoder-Decoder Framework
Representation of data on mixed variables, numerical and categorical types to get suitable feature map is a challenging task as important information lies in a complex non-linear manifold.
Graph Spectral Feature Learning for Mixed Data of Categorical and Numerical Type
In this work, we propose a novel strategy to explicitly model the probabilistic dependence structure among the mixed type of variables by an undirected graph.
Semi-Bagging Based Deep Neural Architecture to Extract Text from High Entropy Images
Furthermore, the proposed text detection method along with a text recognizer outperforms the existing state-of-the-art approaches in extracting text from high entropy images.
