Scientific Research Publishing

Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features ()

Phishing is a form of cybercrime in which people are deceived into exposing their personal information which can result in ...
IEEE

Prediction of Rockburst Risk in Coal Mines Based on a Locally Weighted C4.5 Algorithm

Abstract: Rockburst is a dynamic phenomenon characterized by the sudden, abrupt, and violent release of deformation energy in coal and rock masses around mine shafts and slopes that can result in ...
IEEE

Density Peaks Clustering Based on Label Propagation and K-Mutual-Nearest Neighbors

Abstract: The density peaks clustering algorithm is one of the density-based clustering algorithms. This algorithm has several advantages, including not requiring a preset number of clusters, ...
Tech Xplore on MSN

Combining lessons from ants and birds to improve AI

Combining ideas inspired by ant colonies and flocks of birds may hold the key to unlocking more effective artificial ...
Nature

Will AI spark a scientific renaissance — or a diffuse monoculture?

Xizhe Zhang is a professor working across computer science and medicine at the Affiliated Brain Hospital of Nanjing Medical University and the School of Biomedical Engineering and Informatics, Nanjing ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
Journal of Medical Internet Research

Mortality Risk Prediction in Patients With Antimelanoma Differentiation–Associated, Gene 5 Antibody–Positive, Dermatomyositis–Associated Interstitial Lung Disease ...

The primary endpoint was 3-month mortality due to all causes. Six ML algorithms (Extreme Gradient Boosting [XGBoost], logistic regression (LR), Light Gradient Boosting Machine [LightGBM], random ...
C&EN

Chemists ran 50,688 reactions to make a huge open dataset

The dataset, which the researchers have made available on the Open Reaction Database, is nearly five times as large as the ...
GitHub

approximate-nearest-neighbor-search

postgres machine-learning sql ai clustering ml regression embeddings artificial-intelligence forecasting classification ann approximate-nearest-neighbor-search knn rag vector-database llm Updated on ...
GitHub

02_end_to_end_machine_learning_project.ipynb

Rather than restrict ourselves to k-Nearest Neighbors regressors, let's create a transformer that accepts any regressor. For this, we can extend the MetaEstimatorMixin and have a required estimator ...
Frontiers

Enhanced Differentiation of Breast Lesions through Integration of Microvascular Flow Imaging and Machine Learning Algorithms

Among eight machine learning models trained on six clinical and sonographic features, the K-Nearest Neighbors model achieved the best performance on the independent test set with an accuracy of 0.927 ...
www.cs.cmu.edu

Tom Mitchell

Founders University Professor Machine Learning Department Carnegie Mellon University Visiting Scholar Digital Economy Lab Stanford University Resume / Curriculum Vitae Tom.Mitchell@cmu.edu, 412 268 ...