Federated unlearning via class-discriminative pruning
We explore the problem of selectively forgetting categories from trained CNN classification
models in federated learning (FL). Given that the data used for training cannot be accessed …
models in federated learning (FL). Given that the data used for training cannot be accessed …
Managing bias and unfairness in data for decision support: a survey of machine learning and data engineering approaches to identify and mitigate bias and …
The increasing use of data-driven decision support systems in industry and governments is
accompanied by the discovery of a plethora of bias and unfairness issues in the outputs of …
accompanied by the discovery of a plethora of bias and unfairness issues in the outputs of …
A unified understanding of deep nlp models for text classification
The rapid development of deep natural language processing (NLP) models for text
classification has led to an urgent need for a unified understanding of these models …
classification has led to an urgent need for a unified understanding of these models …
Product improvement in a big data environment: A novel method based on text mining and large group decision making
F Zhang, W Song - Expert Systems with Applications, 2024 - Elsevier
Product improvement has become a multifaceted and uncertain endeavour for
manufacturers in an increasingly competitive business environment. Online platforms have …
manufacturers in an increasingly competitive business environment. Online platforms have …
Does the review deserve more helpfulness when its title resembles the content? Locating helpful reviews by text mining
Online review helpfulness has always sparked a heated discussion among academics and
practitioners. Despite the fact that research has extensively examined the impacts of review …
practitioners. Despite the fact that research has extensively examined the impacts of review …
Automatic identification of causal factors from fall-related accident investigation reports using machine learning and ensemble learning approaches
To enhance the performance of learning from past fall-related accidents, this study
developed an innovative framework for automatically extracting every individual causal …
developed an innovative framework for automatically extracting every individual causal …
Artificial intelligence accelerates multi-modal biomedical process: A Survey
The abundance of artificial intelligence AI algorithms and growing computing power has
brought a disruptive revolution to the smart medical industry. Its powerful data abstraction …
brought a disruptive revolution to the smart medical industry. Its powerful data abstraction …
Changes in consumers' awareness and interest in cosmetic products during the pandemic
YH Choi, SE Kim, KH Lee - Fashion and Textiles, 2022 - Springer
This research investigates the impact of the COVID-19 pandemic on consumers'
perspectives of beauty and individual cosmetic products. Since the first confirmed case of …
perspectives of beauty and individual cosmetic products. Since the first confirmed case of …
A comparative study on tf-idf feature weighting method and its analysis using unstructured dataset
Text Classification is the process of categorizing text into the relevant categories and its
algorithms are at the core of many Natural Language Processing (NLP). Term Frequency …
algorithms are at the core of many Natural Language Processing (NLP). Term Frequency …
Logencoder: Log-based contrastive representation learning for anomaly detection
In recent years, cloud computing centers have grown rapidly in size. Analyzing system logs
is an important way for the quality of service monitoring. However, systems produce massive …
is an important way for the quality of service monitoring. However, systems produce massive …