Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
An evolutionary multitasking optimization framework for constrained multiobjective optimization problems
When addressing constrained multiobjective optimization problems (CMOPs) via
evolutionary algorithms, various constraints and multiple objectives need to be satisfied and …
evolutionary algorithms, various constraints and multiple objectives need to be satisfied and …
Robust sparse and low-redundancy multi-label feature selection with dynamic local and global structure preservation
Recent years, joint feature selection and multi-label learning have received extensive
attention as an open problem. However, there exist three general issues in previous multi …
attention as an open problem. However, there exist three general issues in previous multi …
A review on transferability estimation in deep transfer learning
Deep transfer learning has become increasingly prevalent in various fields such as industry
and medical science in recent years. To ensure the successful implementation of target …
and medical science in recent years. To ensure the successful implementation of target …
Embedding graph auto-encoder for graph clustering
Graph clustering, aiming to partition nodes of a graph into various groups via an
unsupervised approach, is an attractive topic in recent years. To improve the representative …
unsupervised approach, is an attractive topic in recent years. To improve the representative …
Robust and sparse principal component analysis with adaptive loss minimization for feature selection
Principal component analysis (PCA) is one of the most successful unsupervised subspace
learning methods and has been used in many practical applications. To deal with the …
learning methods and has been used in many practical applications. To deal with the …
A theory-driven deep learning method for voice chat–based customer response prediction
As artificial intelligence and digitalization technologies are flourishing real-time, online
interaction–based commercial modes, exploiting customers' purchase intention implied in …
interaction–based commercial modes, exploiting customers' purchase intention implied in …
Matrix completion via non-convex relaxation and adaptive correlation learning
The existing matrix completion methods focus on optimizing the relaxation of rank function
such as nuclear norm, Schatten-norm, etc. They usually need many iterations to converge …
such as nuclear norm, Schatten-norm, etc. They usually need many iterations to converge …
Multi-dimensional classification: paradigm, algorithms and beyond
Multi-dimensional classification (MDC) aims at learning from objects where each of them is
represented by a single instance while associated with multiple class variables. In recent …
represented by a single instance while associated with multiple class variables. In recent …
An end-to-end deep graph clustering via online mutual learning
In clustering fields, the deep graph models generally utilize the graph neural network to
extract the deep embeddings and aggregate them according to the data structure. The …
extract the deep embeddings and aggregate them according to the data structure. The …
Deep multi-task mining Calabi–Yau four-folds
We continue earlier efforts in computing the dimensions of tangent space cohomologies of
Calabi–Yau manifolds using deep learning. In this paper, we consider the dataset of all …
Calabi–Yau manifolds using deep learning. In this paper, we consider the dataset of all …