39 citations · 154 across the 26 of their papers we have counts for
7 papers · 1 filter
Mixture-based Multiple Imputation Model for Clinical Data with a Temporal Dimension
Ye Xue, Diego Klabjan, Yuan Luo
The problem of missing values in multivariable time series is a key challenge in many applications such as clinical data mining. Although many imputation methods show their effecti…
Data Extraction from Charts via Single Deep Neural Network
Xiaoyi Liu, Diego Klabjan, Patrick NBless
Automatic data extraction from charts is challenging for two reasons: there exist many relations among objects in a chart, which is not a common consideration in general computer v…
Dynamic Cell Structure via Recursive-Recurrent Neural Networks
Xin Qian, Matthew Kennedy, Diego Klabjan
In a recurrent setting, conventional approaches to neural architecture search find and fix a general model for all data samples and time steps. We propose a novel algorithm that ca…
Scale Invariant Power Iteration
Cheolmin Kim, Youngseok Kim, Diego Klabjan
Power iteration has been generalized to solve many interesting problems in machine learning and statistics. Despite its striking success, theoretical understanding of when and how…
Convergence Analyses of Online ADAM Algorithm in Convex Setting and Two-Layer ReLU Neural Network
Biyi Fang, Diego Klabjan
Nowadays, online learning is an appealing learning paradigm, which is of great interest in practice due to the recent emergence of large scale applications such as online advertisi…
Automatic Ontology Learning from Domain-Specific Short Unstructured Text Data
Yiming Xu, Dnyanesh Rajpathak, Ian Gibbs +1
Ontology learning is a critical task in industry, dealing with identifying and extracting concepts captured in text data such that these concepts can be used in different tasks, e.…