#machine learning
29 resultsA Survey on Data Collection for Machine Learning: a Big Data -- AI Integration Perspective
Yuji Roh, Geon Heo, Steven Euijong Whang
The paper surveys methods for acquiring and labeling data for machine learning, focusing on challenges and techniques from a data management perspective and discussing the integrat…
The Adverse Effects of Code Duplication in Machine Learning Models of Code
Miltiadis Allamanis
The paper investigates how near-duplicate code in large code corpora inflates the reported performance of machine learning models for source code, showing that metrics can be overe…
Transcriptional Response of SK-N-AS Cells to Methamidophos
Akos Vertes, Albert-Baskar Arul, Peter Avar +13
The study measures how SK‑N‑AS neuroblastoma cells change their gene expression over time after exposure to the pesticide methamidophos, using statistical analysis and machine lear…
AI-enabled Blockchain: An Outlier-aware Consensus Protocol for Blockchain-based IoT Networks
Mehrdad Salimitari, Mohsen Joneidi, Mainak Chatterjee
The paper proposes an AI‑enabled blockchain framework that adds an outlier‑detection step before the standard PBFT consensus to improve fault tolerance in IoT networks built on Hyp…
Concepts and Applications of Conformal Prediction in Computational Drug Discovery
Isidro Cortés-Ciriano, Andreas Bender
The paper reviews conformal prediction as a way to quantify the reliability of machine‑learning models in drug discovery, showing how it provides calibrated confidence intervals fo…
Effects of Rate, Size and Prior Deformation in Microcrystal Plasticity
Stefanos Papanikolaou, Michail Tzimas
The paper presents a minimal discrete edge dislocation model for sub‑micron crystals, showing how loading rate, specimen size, and prior deformation affect plastic response and ava…
Machine Learning on Difference Image Analysis: A comparison of methods for transient detection
B. Sánchez, M. J. DomÃnguez R., M. Lares +12
The paper evaluates several difference image analysis techniques, both alone and combined with machine learning classifiers, for detecting optical transients associated with gravit…
Machine Learning and the future of Supernova Cosmology
Emille E. O. Ishida
The paper reviews how machine learning techniques can be adapted to astronomical data to automatically identify and classify supernovae, enabling their use as standard candles in f…
Sex differences in predicting fluid intelligence of adolescent brain from T1-weighted MRIs
Sara Ranjbar, Kyle W. Singleton, Lee Curtin +4
The study builds sex‑specific machine‑learning models (CNNs and random forests) to predict fluid intelligence in 9‑10‑year‑old children from T1‑weighted MRI scans, finding that ran…
Predicted disease compositions of human gliomas estimated from multiparametric MRI can predict endothelial proliferation, tumor grade, and overall survival
Emily E Diller, Sha Cao, Beth Ey +2
The study applies voxel‑wise radiomic features from multiparametric MRI and a k‑nearest‑neighbor classifier to predict disease composition in gliomas, demonstrating that these pred…
Assessing and Improving Machine Learning Model Predictions of Polymer Glass Transition Temperatures
Manav Ramprasad, Chiho Kim
The paper evaluates the accuracy of existing machine‑learning models for predicting polymer glass transition temperatures, expands the training set with 871 new polymers, and build…
The Softwarised Network Data Zoo
Manuel Peuster, Stefan Schneider, Holger Karl
The paper presents the Softwarised Network Data Zoo (SNDZoo), an open repository of software networking datasets designed to facilitate machine‑learning research on softwarised net…
Using Machine Learning to Optimize Web Interactions on Heterogeneous Mobile Multi-cores
Lu Yuan, Jie Ren, Ling Gao +2
The paper proposes a machine‑learning based runtime system that predicts frame rates for user interactions on mobile web pages and selects optimal processor cores and clock speeds…
Predicting Prosodic Prominence from Text with Pre-trained Contextualized Word Representations
Aarne Talman, Antti Suni, Hande Celikkanat +3
The paper presents a new dataset and benchmark for predicting prosodic prominence from written text, and shows that BERT-based contextualized word representations achieve the best…
PROBE: Predictive Robust Estimation for Visual-Inertial Navigation
Valentin Peretroukhin, Lee Clement, Matthew Giamou +1
The paper introduces a method that learns to weight visual features based on their predicted impact on localization error, improving accuracy in visual‑inertial navigation systems.
A Machine Learning Framework for Biometric Authentication using Electrocardiogram
Song-Kyoo Kim, Chan Yeob Yeun, Ernesto Damiani +1
The paper presents a framework that guides the use of machine‑learning methods for ECG‑based biometric authentication, defining dataset requirements, quality metrics, and providing…
Machine Learning Models for the Lattice Thermal Conductivity Prediction of Inorganic Materials
Lihua Chen, Huan Tran, Rohit Batra +2
The paper presents a machine‑learning model, based on Gaussian process regression and advanced feature engineering, that can instantly predict the lattice thermal conductivity of i…
The discernible and hidden effects of clonality on the genotypic and genetic states of populations: improving our estimation of clonal rates
Solenn Stoeckel, Barbara Porro, Sophie Arnaud-Haond
The paper uses forward simulations and machine learning to show how varying rates of clonality affect genotypic and genetic diversity metrics, and demonstrates that genotypic indic…
Universal Transforming Geometric Network
Jin Li
The paper presents the Universal Transforming Geometric Network, a differentiable model that replaces recurrent neural networks with a universal transformer encoder to improve prot…
sql4ml A declarative end-to-end workflow for machine learning
Nantia Makrynioti, Ruy Ley-Wild, Vasilis Vassalos
The paper introduces sql4ml, a system that lets users write both feature engineering and supervised machine learning models in SQL, automatically translating them to TensorFlow for…
Towards Surgically-Precise Technical Debt Estimation: Early Results and Research Roadmap
Valentina Lenarduzzi, Antonio Martini, Davide Taibi +1
The paper investigates whether simple machine‑learning regression models can improve the precision of technical debt estimates compared to current tools like SonarQube, presenting…
Cultural association based on machine learning for team formation
Hrishikesh Kulkarni, Bradly Alicea
The paper proposes a machine‑learning approach that uses a Graphical Association Method to quantify cultural similarity between individuals and apply this measure to form effective…
Modeling Daily Pan Evaporation in Humid Climates Using Gaussian Process Regression
Sevda Shabani, Saeed Samadianfard, Mohammad Taghi Sattari +4
The paper compares several machine‑learning models, especially Gaussian Process Regression, to estimate daily pan evaporation in humid regions of Iran using readily available meteo…
A review of feature extraction and performance evaluation in epileptic seizure detection using EEG
Poomipat Boonyakitanont, Apiwat Lek-uthai, Krisnachai Chomtho +1
The paper reviews feature extraction methods and evaluates their performance for automatic epileptic seizure detection from EEG signals, including experiments on individual feature…