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Found 6 papers, 2 papers with code
To Optimize, or Not to Optimize, That Is the Question: TelU-KU Models for WMT21 Large-Scale Multilingual Machine Translation
We describe TelU-KU models of large-scale multilingual machine translation for five Southeast Asian languages: Javanese, Indonesian, Malay, Tagalog, Tamil, and English.
T-DFNN: An Incremental Learning Algorithm for Intrusion Detection Systems
Moreover, our proposed T-DFNN model has significantly shorter training times than a DFNN model trained using a dataset containing all targeted intrusions.
Efficient Feature Extraction Model for Validation Performance Improvement of Duplicate Bug Report Detection in Software Bug Triage Systems
The results also showed that the combination of all types of features could improve the validation performance of DBRD even for the LR classifier with less validation performance, which can be implemented easily for software bug triage systems.
Text Detection on Roughly Placed Books by Leveraging a Learning-based Model Trained with Another Domain Data
Text detection enables us to extract rich information from images.
DBMS-KU Interpolation for WMT19 News Translation Task
We examine the use of interpolation method using a different language model order.
DBMS-KU at SemEval-2019 Task 9: Exploring Machine Learning Approaches in Classifying Text as Suggestion or Non-Suggestion
This paper describes the participation of DBMS-KU team in the SemEval 2019 Task 9, that is, suggestion mining from online reviews and forums.
