Search Results for author:
Found 10 papers, 1 papers with code
An Analysis of Composite Neural Network Performance from Function Composition Perspective
This work investigates the performance of a composite neural network, which is composed of pre-trained neural network models and non-instantiated neural network models, connected to form a rooted directed graph.
Headline Diagnosis: Manipulation of Content Farm Headlines
As technology grows faster, the news spreads through social media.
Integration of Static and Dynamic Analysis for Malware Family Classification with Composite Neural Network
In this paper, we combine static and dynamic analysis features with deep neural networks for Windows malware classification.
Learning Malware Representation based on Execution Sequences
The encoder comprises gated recurrent units (GRU) to preserve the ordinal position of API calls and a self-attention mechanism for comparing intra-relations among different positions of API calls.
Composite Neural Network: Theory and Application to PM2.5 Prediction
In addition, if an extra pre-trained component is added to a composite network, with high probability, the overall performance will not be degraded.
Theoretical Investigation of Composite Neural Network
In this work, we prove that a composite neural network, with high probability, performs better than any of its pre-trained components under certain assumptions.
Bringing personalized learning into computer-aided question generation
This paper proposes a novel and statistical method of ability estimation based on acquisition distribution for a personalized computer aided question generation.
Development and Evaluation of a Personalized Computer-aided Question Generation for English Learners to Improve Proficiency and Correct Mistakes
In this work, we present a personalized computer aided question generation that generates multiple choice questions at various difficulty levels and types, including vocabulary, grammar and reading comprehension.
Characterizing the Influence of Features on Reading Difficulty Estimation for Non-native Readers
In recent years, the number of people studying English as a second language (ESL) has surpassed the number of native speakers.
Wrapped Loss Function for Regularizing Nonconforming Residual Distributions
Multi-output is essential in machine learning that it might suffer from nonconforming residual distributions, i. e., the multi-output residual distributions are not conforming to the expected distribution.
