Papers Feature Engineering
“Feature Engineering” 태그가 달린 논문 1,990편 · 필터 해제
Understanding Developer Pain Points in Federated Learning: Insights from Stack Overflow and GitHub
Federated Learning (FL) enables collaborative model training without centralizing raw data, but building and operating FL systems remains difficult due to distributed execution, rapidly evolving frameworks, and privacy a…
Feature EngineeringFederated LearningOn the Impact of Entropy-based Features
Network anomaly detection is increasingly challenging due to the growing diversity and variability of traffic patterns, which are not always well captured by traditional statistical features. In this work, we explore the…
Intrusion DetectionFeature EngineeringAnomaly DetectionAn LLM-powered Agentic Recommendation System for Connected TV Content Discovery
Recommendation systems, from traditional multi-stage to recent unified generative architectures, face challenges in incorporating diverse contextual signals, such as trending topics, breaking news, cultural events, and c…
Recommendation SystemsFeature EngineeringTokenizing Numerical and Embedding Features for LLM RecSys
Large language models (LLMs) are increasingly used as backbone architectures for recommender systems because of their strong sequence modeling and representation learning capabilities. However, most LLM-based recommender…
Representation LearningFeature EngineeringPredicting Male Fertility Using Machine Learning: A Semen Parameters Based Analysis with the VISEM Dataset
Male infertility is a significant yet often underdiagnosed aspect of reproductive health, with semen analysis serving as the cornerstone of clinical evaluation. To address this problem, this study investigates the use of…
Feature EngineeringFormat-Controlled Multi-Scale JPEG Compression Response Analysis for Image-Level Forgery Screening
Image forgery detection is a critical task in digital forensics, yet many deep-learning localization approaches are typically GPU-accelerated and computationally heavier than handcrafted screening methods. We propose a l…
Feature EngineeringEEG-SpikeAgent: Agentic Closed-Loop Program Synthesis for Automated EEG Spike Detection
Automated detection of interictal epileptiform discharges in scalp electroencephalography (EEG) is clinically important, but recent high-performing deep-learning models often trade interpretability for accuracy. We intro…
Feature EngineeringProgram SynthesisSeeMe: Mitigating Hallucinations in Large Vision-Language Models through Effective Visual Token Engineering
Large Vision-Language Models (LVLMs) have achieved remarkable progress in visual understanding tasks such as image captioning and visual question answering. However, they remain susceptible to hallucinations, generating …
Visual Question AnsweringFeature EngineeringImage CaptioningEvolutionary Feature Engineering for Structured Data
Large language models are increasingly used as open-ended search operators in evolutionary optimization. We introduce Evolutionary Feature Engineering (EFE), a framework for using LLM-based evolution to discover preproce…
Feature EngineeringUnderstanding How Humans Inject Knowledge into Machine Learning Workflows through Visual Analytics
Visual analytics (VA) plays an increasingly important role in supporting machine learning (ML) workflows. In the field of visualization, such approaches and techniques are referred to as VIS4ML. While ML models are mostl…
Feature EngineeringRethinking the Role of Feature Engineering and Learning Strategies in Few-Shot Hidden Emotion Recognition
In this paper, we present the solution developed by our team, XInsight Lab, which achieved first place in Track 3 of the 4th EI-MIGA-IJCAI Challenge with a test accuracy of 0.76923. To address the challenge of weak and s…
Multiple Instance LearningEmotion RecognitionFeature EngineeringConsensus Clustering of Free-Viewing Gaze Data: New Insights into Human-Information Interaction
Free-viewing gaze data provides a rich, task-free window into human visual attention. Conventional exploratory data analysis of the data provides user attention patterns through fixations and areas of interest. However, …
Feature EngineeringEnsemble LearningBoundary Degree as a Node-level Feature for Epidemic Scenario Identification in Agent-based Cascade Simulations
Characterizing the scenario underlying an epidemic from its disease cascade is an important task in simulation analytics. We propose boundary degree, the count of an infected node's contacts in the underlying contact net…
Feature EngineeringExploring the potential of AlphaEarth and TESSERA embeddings for Fine-scale Local Climate Zone Mapping: A case study across five cities in Switzerland
Understanding urban spatial morphology is critical for climate modeling, risk assessment, and sustainable urban design, and Local Climate Zone (LCZ) mapping provides the basic framework for this. However, many cities sti…
Feature EngineeringMachine Learning Classification of Cryopathy Syndromes: A Comprehensive Comparative Study
Cryopathy syndromes are difficult to classify because laboratory patterns often overlap across diagnostic categories, while some diagnoses are rare. This makes routine interpretation of cryoglobulin-related tests challen…
Feature EngineeringTrustworthy Self-Composable Big-Data-as-a-Service: An LLM-Orchestrated Multi-Agent Framework for Automated Data Engineering, AutoML, MLOps Deployment, and Drift-Aware Lifecycle Optimization
Big-Data-as-a-Service (BDaaS) platforms require re liable automation across data ingestion, cleaning, feature engi neering, model development, deployment, and post-deployment monitoring. However, existing LLM-based data …
Feature EngineeringWhen LLMs Analyze Scars: From Images to Clinically-Meaningful Features
Medical image classification faces a fundamental dilemma: while deep learning models achieve remarkable performance at scale, real-world clinical scenarios often suffer from severe data scarcity due to annotation costs, …
Medical Image ClassificationFeature EngineeringAutonomous End-to-End SOH Prediction Services for Battery Systems via Temporal-Contrastive Representation Learning
Accurate state of health (SOH) estimation is a critical diagnostic service for lithium-ion battery management. However, reliance on labor-intensive manual feature engineering and opaque black-box models hinders scalable …
Representation LearningFeature EngineeringProgressive Knowledge-Guided Large Language Model Framework for Bearing Fault Diagnosis
Vibration-based bearing fault diagnosis requires resolving three interrelated measurement challenges, including the trade-off between global statistical feature efficiency and local transient signal fidelity, insufficien…
Feature EngineeringFault DiagnosisGRACE-DS: a Guarded Reward-guided Agent Correction Environment in Data Science
We introduce GRACE-DS, a Guarded Reward-guided Agent Correction Environment in Data Science for pre-deployment evaluation of LLM-powered AutoML agents. GRACE-DS is a set of evaluation metrics in an isolated environment t…
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