10 citations · 20 across the 9 of their papers we have counts for
9 papers
Neural Language Modeling With Implicit Cache Pointers
Ke Li, Daniel Povey, Sanjeev Khudanpur
A cache-inspired approach is proposed for neural language models (LMs) to improve long-range dependency and better predict rare words from long contexts. This approach is a simpler…
Surrogate Assisted Evolutionary Algorithm for Medium Scale Expensive Multi-Objective Optimisation Problems
Xiaoran Ruan, Ke Li, Bilel Derbel +1
Building a surrogate model of an objective function has shown to be effective to assist evolutionary algorithms (EAs) to solve real-world complex optimisation problems which involv…
Understanding the Automated Parameter Optimization on Transfer Learning for CPDP: An Empirical Study
Ke Li, Zilin Xiang, Tao Chen +2
Data-driven defect prediction has become increasingly important in software engineering process. Since it is not uncommon that data from a software project is insufficient for trai…
A New Deep Learning Method for Image Deblurring in Optical Microscopic Systems
Huangxuan Zhao, Ziwen Ke, Ningbo Chen +8
Deconvolution is the most commonly used image processing method to remove the blur caused by the point-spread-function (PSF) in optical imaging systems. While this method has been…
Does Preference Always Help? A Holistic Study on Preference-Based Evolutionary Multi-Objective Optimisation Using Reference Points
Ke Li, Minhui Liao, Kalyanmoy Deb +2
The ultimate goal of multi-objective optimisation is to help a decision maker (DM) identify solution(s) of interest (SOI) achieving satisfactory trade-offs among multiple conflicti…
Visualisation of Pareto Front Approximation: A Short Survey and Empirical Comparisons
Huiru Gao, Haifeng Nie, Ke Li
Visualisation is an effective way to facilitate the analysis and understanding of multivariate data. In the context of multi-objective optimisation, comparing to quantitative perfo…