output
20172022
most citedMulti-Haul Quasi Network Flow Model for Vertical Alignment Optimization

32 citations

5 papers

cs.SE202210 cited

On the Effectiveness of Pretrained Models for API Learning

Mohammad Abdul Hadi, Imam Nur Bani Yusuf, Ferdian Thung +4

Developers frequently use APIs to implement certain functionalities, such as parsing Excel Files, reading and writing text files line by line, etc. Developers can greatly benefit f…

cs.CL2022

Pre-Trained Neural Language Models for Automatic Mobile App User Feedback Answer Generation

Yue Cao, Fatemeh H. Fard

Studies show that developers' answers to the mobile app users' feedbacks on app stores can increase the apps' star rating. To help app developers generate answers that are related…

cs.IR2020

AOBTM: Adaptive Online Biterm Topic Modeling for Version Sensitive Short-texts Analysis

Mohammad Abdul Hadi, Fatemeh H Fard

Analysis of mobile app reviews has shown its important role in requirement engineering, software maintenance and evolution of mobile apps. Mobile app developers check their users'…

cs.LG2019

Secure Distributed On-Device Learning Networks With Byzantine Adversaries

Yanjie Dong, Julian Cheng, Md. Jahangir Hossain +1

The privacy concern exists when the central server has the copies of datasets. Hence, there is a paradigm shift for the learning networks to change from centralized in-cloud learni…

math.OC201732 cited

Multi-Haul Quasi Network Flow Model for Vertical Alignment Optimization

Vahid Beiranvand, Warren Hare, Yves Lucet +1

The vertical alignment optimization problem for road design aims to generate a vertical alignment of a new road with a minimum cost, while satisfying safety and design constraints.…