Data Augmentation for Deep Learning Regression Tasks by Machine Learning Models
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | Shmuel, Assaf, Glickman, Oren, Lazebnik, Teddy |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
Symbolic Regression as Feature Engineering Method for Machine and Deep Learning Regression Tasks
par: Shmuel, Assaf, et autres
Publié: (2023)
par: Shmuel, Assaf, et autres
Publié: (2023)
A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets
par: Shmuel, Assaf, et autres
Publié: (2024)
par: Shmuel, Assaf, et autres
Publié: (2024)
Global Lightning-Ignited Wildfires Prediction and Climate Change Projections based on Explainable Machine Learning Models
par: Shmuel, Assaf, et autres
Publié: (2024)
par: Shmuel, Assaf, et autres
Publié: (2024)
Pulling the Carpet Below the Learner's Feet: Genetic Algorithm To Learn Ensemble Machine Learning Model During Concept Drift
par: Lazebnik, Teddy
Publié: (2024)
par: Lazebnik, Teddy
Publié: (2024)
Introducing 'Inside' Out of Distribution
par: Lazebnik, Teddy
Publié: (2024)
par: Lazebnik, Teddy
Publié: (2024)
Spatio-Temporal SIR Model of Pandemic Spread During Warfare with Optimal Dual-use Healthcare System Administration using Deep Reinforcement Learning
par: Shuchami, Adi, et autres
Publié: (2024)
par: Shuchami, Adi, et autres
Publié: (2024)
Accelerating Reinforcement Learning Algorithms Convergence using Pre-trained Large Language Models as Tutors With Advice Reusing
par: Toral, Lukas, et autres
Publié: (2025)
par: Toral, Lukas, et autres
Publié: (2025)
Break a Lag: Triple Exponential Moving Average for Enhanced Optimization
par: Peleg, Roi, et autres
Publié: (2023)
par: Peleg, Roi, et autres
Publié: (2023)
Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models
par: Taskin, Bilge, et autres
Publié: (2025)
par: Taskin, Bilge, et autres
Publié: (2025)
Knowledge-integrated AutoEncoder Model
par: Lazebnik, Teddy, et autres
Publié: (2023)
par: Lazebnik, Teddy, et autres
Publié: (2023)
Cancer-inspired Genomics Mapper Model for the Generation of Synthetic DNA Sequences with Desired Genomics Signatures
par: Lazebnik, Teddy, et autres
Publié: (2023)
par: Lazebnik, Teddy, et autres
Publié: (2023)
Quality-preserving Model for Electronics Production Quality Tests Reduction
par: Haneefa, Noufa, et autres
Publié: (2026)
par: Haneefa, Noufa, et autres
Publié: (2026)
Profiling Privacy Preservation Against Gradient Inversion Attacks in Tabular Federated Learning
par: Nilsson, Ivo Osterberg, et autres
Publié: (2026)
par: Nilsson, Ivo Osterberg, et autres
Publié: (2026)
Tighten The Lasso: A Convex Hull Volume-based Anomaly Detection Method
par: Itai, Uri, et autres
Publié: (2025)
par: Itai, Uri, et autres
Publié: (2025)
AutoLoop: Fast Visual SLAM Fine-tuning through Agentic Curriculum Learning
par: Lahiany, Assaf, et autres
Publié: (2025)
par: Lahiany, Assaf, et autres
Publié: (2025)
Catastrophic Forgetting Mitigation Through Plateau Phase Activity Profiling
par: Mashiach, Idan, et autres
Publié: (2025)
par: Mashiach, Idan, et autres
Publié: (2025)
SubStrat: A Subset-Based Strategy for Faster AutoML
par: Lazebnik, Teddy, et autres
Publié: (2022)
par: Lazebnik, Teddy, et autres
Publié: (2022)
First-Order Manifold Data Augmentation for Regression Learning
par: Kaufman, Ilya, et autres
Publié: (2024)
par: Kaufman, Ilya, et autres
Publié: (2024)
Investigating Tax Evasion Emergence Using Dual Large Language Model and Deep Reinforcement Learning Powered Agent-based Simulation
par: Lazebnik, Teddy, et autres
Publié: (2025)
par: Lazebnik, Teddy, et autres
Publié: (2025)
Mixed Semi-Supervised Generalized-Linear-Regression with Applications to Deep-Learning and Interpolators
par: Yuval, Oren, et autres
Publié: (2023)
par: Yuval, Oren, et autres
Publié: (2023)
The Impact of Feature Scaling In Machine Learning: Effects on Regression and Classification Tasks
par: Pinheiro, João Manoel Herrera, et autres
Publié: (2025)
par: Pinheiro, João Manoel Herrera, et autres
Publié: (2025)
Hippasus: Effective and Efficient Automatic Feature Augmentation for Machine Learning Tasks on Relational Data
par: Papadias, Serafeim, et autres
Publié: (2026)
par: Papadias, Serafeim, et autres
Publié: (2026)
Evaluation of Machine and Deep Learning Techniques for Cyclone Trajectory Regression and Status Classification by Time Series Data
par: Lo, Ethan Zachary, et autres
Publié: (2025)
par: Lo, Ethan Zachary, et autres
Publié: (2025)
RC-Mixup: A Data Augmentation Strategy against Noisy Data for Regression Tasks
par: Hwang, Seong-Hyeon, et autres
Publié: (2024)
par: Hwang, Seong-Hyeon, et autres
Publié: (2024)
Online Data Augmentation for Forecasting with Deep Learning
par: Cerqueira, Vitor, et autres
Publié: (2024)
par: Cerqueira, Vitor, et autres
Publié: (2024)
Augmented Regression Models using Neurochaos Learning
par: Henry, Akhila, et autres
Publié: (2025)
par: Henry, Akhila, et autres
Publié: (2025)
Transforming Norm-based To Graph-based Spatial Representation for Spatio-Temporal Epidemiological Models
par: Lazebnik, Teddy
Publié: (2024)
par: Lazebnik, Teddy
Publié: (2024)
Unemployment Dynamics Forecasting with Machine Learning Regression Models
par: Kim, Kyungsu
Publié: (2025)
par: Kim, Kyungsu
Publié: (2025)
PFT: Phonon Fine-tuning for Machine Learned Interatomic Potentials
par: Koker, Teddy, et autres
Publié: (2026)
par: Koker, Teddy, et autres
Publié: (2026)
More Data or Better Algorithms: Latent Diffusion Augmentation for Deep Imbalanced Regression
par: Alahyari, Shayan
Publié: (2025)
par: Alahyari, Shayan
Publié: (2025)
The Topology of a Family Tree Graph and Its Members' Satisfaction with One Another: A Machine Learning Approach
par: Lazebnik, Teddy, et autres
Publié: (2023)
par: Lazebnik, Teddy, et autres
Publié: (2023)
Deep Learning, Machine Learning, Advancing Big Data Analytics and Management
par: Hsieh, Weiche, et autres
Publié: (2024)
par: Hsieh, Weiche, et autres
Publié: (2024)
SPINEX: Similarity-based Predictions and Explainable Neighbors Exploration for Regression and Classification Tasks in Machine Learning
par: Naser, M. Z., et autres
Publié: (2023)
par: Naser, M. Z., et autres
Publié: (2023)
Curvature Enhanced Data Augmentation for Regression
par: Sirot, Ilya Kaufman, et autres
Publié: (2025)
par: Sirot, Ilya Kaufman, et autres
Publié: (2025)
Regression Augmentation With Data-Driven Segmentation
par: Alahyari, Shayan, et autres
Publié: (2025)
par: Alahyari, Shayan, et autres
Publié: (2025)
IM-Context: In-Context Learning for Imbalanced Regression Tasks
par: Nejjar, Ismail, et autres
Publié: (2024)
par: Nejjar, Ismail, et autres
Publié: (2024)
Deep Learning for Subspace Regression
par: Fanaskov, Vladimir, et autres
Publié: (2025)
par: Fanaskov, Vladimir, et autres
Publié: (2025)
Transductive and Learning-Augmented Online Regression
par: Raman, Vinod, et autres
Publié: (2025)
par: Raman, Vinod, et autres
Publié: (2025)
Mathematical model of dating apps influence on sexually transmitted diseases spread
par: Lazebnik, Teddy
Publié: (2023)
par: Lazebnik, Teddy
Publié: (2023)
Service Preservation from Matching Non-Matching Socks Under Stochastic Loss
par: Lazebnik, Teddy
Publié: (2026)
par: Lazebnik, Teddy
Publié: (2026)
Documents similaires
-
Symbolic Regression as Feature Engineering Method for Machine and Deep Learning Regression Tasks
par: Shmuel, Assaf, et autres
Publié: (2023) -
A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets
par: Shmuel, Assaf, et autres
Publié: (2024) -
Global Lightning-Ignited Wildfires Prediction and Climate Change Projections based on Explainable Machine Learning Models
par: Shmuel, Assaf, et autres
Publié: (2024) -
Pulling the Carpet Below the Learner's Feet: Genetic Algorithm To Learn Ensemble Machine Learning Model During Concept Drift
par: Lazebnik, Teddy
Publié: (2024) -
Introducing 'Inside' Out of Distribution
par: Lazebnik, Teddy
Publié: (2024)