Papers Feature Engineering
“Feature Engineering” 태그가 달린 논문 1,990편 · 필터 해제
Feature Engineering Approach to Building Load Prediction: A Case Study for Commercial Building Chiller Plant Optimization in Tropical Weather
In tropical countries with high humidity, air conditioning can account for up to 60% of a building's energy use. For commercial buildings with centralized systems, the efficiency of the chiller plant is vital, and model …
ClusteringFeature EngineeringModel Predictive ControlPredictionPainDECOG: Machine Learning-Based Identification of Pain Biomarkers from sEEG Signals
This study presents a systematic machine-learning approach for classifying acute pain from raw electrophysiological signals. We address binary and ternary classification tasks, leveraging Power-In-Band (PIB) and signal c…
Feature EngineeringManagementSEM-CLIP: Precise Few-Shot Learning for Nanoscale Defect Detection in Scanning Electron Microscope Image
In the field of integrated circuit manufacturing, the detection and classification of nanoscale wafer defects are critical for subsequent root cause analysis and yield enhancement. The complex background patterns observe…
Defect DetectionFeature EngineeringFew-Shot LearningSegmentationRecent Advances in Malware Detection: Graph Learning and Explainability
The rapid evolution of malware has necessitated the development of sophisticated detection methods that go beyond traditional signature-based approaches. Graph learning techniques have emerged as powerful tools for model…
Feature EngineeringGraph EmbeddingGraph LearningMalware Analysis+2Chronic Diseases Prediction Using ML
The recent increase in morbidity is primarily due to chronic diseases including Diabetes, Heart disease, Lung cancer, and brain tumours. The results for patients can be improved, and the financial burden on the healthcar…
Feature EngineeringPredictionDecision Tree Based Wrappers for Hearing Loss
Audiology entities are using Machine Learning (ML) models to guide their screening towards people at risk. Feature Engineering (FE) focuses on optimizing data for ML models, with evolutionary methods being effective in f…
Feature Engineeringfeature selectionA Survey on Data-Centric AI: Tabular Learning from Reinforcement Learning and Generative AI Perspective
Tabular data is one of the most widely used data formats across various domains such as bioinformatics, healthcare, and marketing. As artificial intelligence moves towards a data-centric perspective, improving data quali…
Feature Engineeringfeature selectionMarketingReinforcement Learning (RL)+1LLM4GNAS: A Large Language Model Based Toolkit for Graph Neural Architecture Search
Graph Neural Architecture Search (GNAS) facilitates the automatic design of Graph Neural Networks (GNNs) tailored to specific downstream graph learning tasks. However, existing GNAS approaches often require manual adapta…
Feature EngineeringGraph LearningHyperparameter OptimizationLanguage Modeling+3Enhancing Physics-Informed Neural Networks Through Feature Engineering
Physics-Informed Neural Networks (PINNs) seek to solve partial differential equations (PDEs) with deep learning. Mainstream approaches that deploy fully-connected multi-layer deep learning architectures require prolonged…
Feature EngineeringExploring Patterns Behind Sports
This paper presents a comprehensive framework for time series prediction using a hybrid model that combines ARIMA and LSTM. The model incorporates feature engineering techniques, including embedding and PCA, to transform…
Computational EfficiencyFeature EngineeringFeature ImportanceTime Series+2Application of quantum machine learning using quantum kernel algorithms on multiclass neuron M type classification
The functional characterization of different neuronal types has been a longstanding and crucial challenge. With the advent of physical quantum computers, it has become possible to apply quantum machine learning algorithm…
Binary ClassificationFeature EngineeringQuantum Machine LearningAgentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews
The advent of large language models has ushered in a new era of agentic systems, where artificial intelligence programs exhibit remarkable autonomous decision-making capabilities across diverse domains. This paper explor…
Decision MakingFeature EngineeringFraud DetectionManagement+1Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory
Neural architectures such as Recurrent Neural Networks (RNNs), Transformers, and State-Space Models have shown great success in handling sequential data by learning temporal dependencies. Decision Trees (DTs), on the oth…
Feature EngineeringState Space ModelsBenchmarking Time Series Forecasting Models: From Statistical Techniques to Foundation Models in Real-World Applications
Time series forecasting is essential for operational intelligence in the hospitality industry, and particularly challenging in large-scale, distributed systems. This study evaluates the performance of statistical, machin…
BenchmarkingFeature EngineeringTime SeriesTime Series ForecastingFrom Features to Transformers: Redefining Ranking for Scalable Impact
We present LiGR, a large-scale ranking framework developed at LinkedIn that brings state-of-the-art transformer-based modeling architectures into production. We introduce a modified transformer architecture that incorpor…
DiversityFeature EngineeringCAAT-EHR: Cross-Attentional Autoregressive Transformer for Multimodal Electronic Health Record Embeddings
Electronic health records (EHRs) provide a comprehensive source of longitudinal patient data, encompassing structured modalities such as laboratory results, imaging data, and vital signs, and unstructured clinical notes.…
Feature EngineeringYear-over-Year Developments in Financial Fraud Detection via Deep Learning: A Systematic Literature Review
This paper systematically reviews advancements in deep learning (DL) techniques for financial fraud detection, a critical issue in the financial sector. Using the Kitchenham systematic literature review approach, 57 stud…
Deep LearningFeature EngineeringFraud DetectionPrivacy Preserving+1RAINER: A Robust Ensemble Learning Grid Search-Tuned Framework for Rainfall Patterns Prediction
Rainfall prediction remains a persistent challenge due to the highly nonlinear and complex nature of meteorological data. Existing approaches lack systematic utilization of grid search for optimal hyperparameter tuning, …
Dimensionality ReductionEnsemble LearningFeature EngineeringImputation+2Sample-Efficient Behavior Cloning Using General Domain Knowledge
Behavior cloning has shown success in many sequential decision-making tasks by learning from expert demonstrations, yet they can be very sample inefficient and fail to generalize to unseen scenarios. One approach to thes…
Car RacingFeature EngineeringGeneral KnowledgeSequential Decision Making360Brew: A Decoder-only Foundation Model for Personalized Ranking and Recommendation
Ranking and recommendation systems are the foundation for numerous online experiences, ranging from search results to personalized content delivery. These systems have evolved into complex, multilayered architectures tha…
DecoderFeature EngineeringRecommendation Systems