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
Mining and application of tourism online review text based on natural language processing and text classification technology
This paper firstly describes the research status of online review text mining and finds out the
problems existing in the mining and application of tourism texts. Aiming at these problems …
problems existing in the mining and application of tourism texts. Aiming at these problems …
Exploring Quantization Techniques for Large-Scale Language Models: Methods, Challenges and Future Directions
Breakthroughs in natural language processing (NLP) by large-scale language models
(LLMs) have led to superior performance in multilingual tasks such as translation …
(LLMs) have led to superior performance in multilingual tasks such as translation …
SignGD with error feedback meets lazily aggregated technique: Communication-efficient algorithms for distributed learning
The proliferation of massive datasets has led to significant interests in distributed algorithms
for solving large-scale machine learning problems. However, the communication overhead …
for solving large-scale machine learning problems. However, the communication overhead …
Consensus-based distributed kernel one-class support vector machine for anomaly detection
One-class support vector machine (OCSVM) is one of the most widely used methods for
learning from imbalanced data and has been successfully applied to numerous tasks such …
learning from imbalanced data and has been successfully applied to numerous tasks such …
Generalized sparse and outlier-robust broad learning systems for multi-dimensional output problems
Y Zhang, Y Dai, S Ke, Q Wu, J Li - Information Sciences, 2024 - Elsevier
Broad learning systems (BLSs) are becoming increasingly popular due to their fast and
superior learning capabilities. However, their performances are susceptible to outliers and …
superior learning capabilities. However, their performances are susceptible to outliers and …
A pruning extreme learning machine with regularization for multi-dimensional output problems
Y Dai, Y Zhang, Q Wu - International Journal of Machine Learning and …, 2024 - Springer
As a fast algorithm for training single-hidden layer feedforward neural networks, extreme
learning machine (ELM) has been successfully applied to various classification and …
learning machine (ELM) has been successfully applied to various classification and …
Sparse and Outlier Robust Extreme Learning Machine Based on the Alternating Direction Method of Multipliers
Y Zhang, Y Dai, Q Wu - Neural Processing Letters, 2023 - Springer
Extreme learning machine (ELM) has been extensively researched for its fast training speed
and powerful learning abilities. Entering the era of big data, large-scale learning tasks, the …
and powerful learning abilities. Entering the era of big data, large-scale learning tasks, the …
Parallel ADMM Algorithm with Gaussian Back Substitution for High-Dimensional Quantile Regression and Classification
X Wu, D Guo, R Liang, Z Zhang - arxiv preprint arxiv:2501.07035, 2025 - arxiv.org
In the field of high-dimensional data analysis, modeling methods based on quantile loss
function are highly regarded due to their ability to provide a comprehensive statistical …
function are highly regarded due to their ability to provide a comprehensive statistical …
Increasing momentum-like factors: A method for reducing training errors on multiple GPUs
In distributed training, increasing batch size can improve parallelism, but it can also bring
many difficulties to the training process and cause training errors. In this work, we investigate …
many difficulties to the training process and cause training errors. In this work, we investigate …
An efficient hybrid MPI/OpenMP parallelization of the asynchronous ADMM algorithm
Alternating direction method of multipliers (ADMM) is an efficient algorithm to solve large-
scale machine learning problems in a distributed environment. To make full use of the …
scale machine learning problems in a distributed environment. To make full use of the …