Imagen de Portada

Stable and Privacy-Preserving Synthetic Educational Data with Empirical Marginals: A Copula-Based Approach

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Ramos, Gabriel Diaz, Luzi, Lorenzo, Mallick, Debshila Basu, Baraniuk, Richard
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning Computers and Society I.2.6, H.2.8
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

AI and Machine Learning Approaches for Predicting Nanoparticles Toxicity The Critical Role of Physiochemical Properties
por: Yousaf, Iqra
Publicado: (2024)

RareGraph-Synth: Knowledge-Guided Diffusion Models for Generating Privacy-Preserving Synthetic Patient Trajectories in Ultra-Rare Diseases
por: Uppalapati, Khartik, et al.
Publicado: (2025)

Are We Winning the Wrong Game? Revisiting Evaluation Practices for Long-Term Time Series Forecasting
por: Phungtua-eng, Thanapol, et al.
Publicado: (2026)

Simple yet Effective Node Property Prediction on Edge Streams under Distribution Shifts
por: Lee, Jongha, et al.
Publicado: (2025)

COMET: Codebook-based Online-adaptive Multi-scale Embedding for Time-series Anomaly Detection
por: Park, Jinwoo, et al.
Publicado: (2026)

The CRITICAL Records Integrated Standardization Pipeline (CRISP): End-to-End Processing of Large-scale Multi-institutional OMOP CDM Data
por: Luo, Xiaolong, et al.
Publicado: (2025)

ScaleMAP: Preserving Local Density and Neighborhood Structure in Low-Dimensional Embeddings
por: Poorna, Rajas, et al.
Publicado: (2026)

Analyzing the Impact of Release Season and Production Budget on Movie Revenue and Profitability
por: Torkamani, Mohammad Jalili, et al.
Publicado: (2026)

Tiny QA Benchmark++: Ultra-Lightweight, Synthetic Multilingual Dataset Generation & Smoke-Tests for Continuous LLM Evaluation
por: Koc, Vincent
Publicado: (2025)

The CTU Prague Relational Learning Repository
por: Motl, Jan, et al.
Publicado: (2015)

Bi-View Embedding Fusion: A Hybrid Learning Approach for Knowledge Graph's Nodes Classification Addressing Problems with Limited Data
por: Napoli, Rosario, et al.
Publicado: (2025)

Prior-Aligned Data Cleaning for Tabular Foundation Models
por: Berti-Equille, Laure
Publicado: (2026)

Evo-DKD: Dual-Knowledge Decoding for Autonomous Ontology Evolution in Large Language Models
por: Raman, Vishal, et al.
Publicado: (2025)

Survey Transfer Learning: Recycling Data with Silicon Responses
por: Amini, Ali
Publicado: (2025)

Noise or Signal? Deconstructing Contradictions and An Adaptive Remedy for Reversible Normalization in Time Series Forecasting
por: Fu, Fanzhe, et al.
Publicado: (2025)

SAGE: Scale-Aware Gradual Evolution for Continual Knowledge Graph Embedding
por: Li, Yifei, et al.
Publicado: (2025)

Learning from Preferences and Mixed Demonstrations in General Settings
por: Brown, Jason R, et al.
Publicado: (2025)

ReaGeo: Reasoning-Enhanced End-to-End Geocoding with LLMs
por: Cui, Jian, et al.
Publicado: (2026)

Dynamics of COVID-19 Misinformation: An Analysis of Conspiracy Theories, Fake Remedies, and False Reports
por: Thakur, Nirmalya, et al.
Publicado: (2025)

Enhancing Document AI Data Generation Through Graph-Based Synthetic Layouts
por: Agarwal, Amit, et al.
Publicado: (2024)

Differentially Private Non Parametric Copulas: Generating synthetic data with non parametric copulas under privacy guarantees
por: Osorio-Marulanda, Pablo A., et al.
Publicado: (2024)

Tulip Agent -- Enabling LLM-Based Agents to Solve Tasks Using Large Tool Libraries
por: Ocker, Felix, et al.
Publicado: (2024)

AgentLTV: An Agent-Based Unified Search-and-Evolution Framework for Automated Lifetime Value Prediction
por: Wu, Chaowei, et al.
Publicado: (2026)

LakeMLB: Data Lake Machine Learning Benchmark
por: Pan, Feiyu, et al.
Publicado: (2026)

Task Memory Engine: Spatial Memory for Robust Multi-Step LLM Agents
por: Ye, Ye
Publicado: (2025)

LEFT: Learnable Fusion of Tri-view Tokens for Unsupervised Time Series Anomaly Detection
por: Wang, Dezheng, et al.
Publicado: (2026)

HERO: Hint-Based Efficient and Reliable Query Optimizer
por: Zinchenko, Sergey, et al.
Publicado: (2024)

Systematic Classification of Studies Investigating Social Media Conversations about Long COVID Using a Novel Zero-Shot Transformer Framework
por: Thakur, Nirmalya, et al.
Publicado: (2025)

Sketch Decompositions for Classical Planning via Deep Reinforcement Learning
por: Aichmüller, Michael, et al.
Publicado: (2024)

LeanProgress: Guiding Search for Neural Theorem Proving via Proof Progress Prediction
por: George, Robert Joseph, et al.
Publicado: (2025)

Zero-Shot Context Generalization in Reinforcement Learning from Few Training Contexts
por: Chapman, James, et al.
Publicado: (2025)

From Cumulative Constraints to Adaptive Runtime Safety Control for Nonstationary Reinforcement Learning
por: Tomashevskiy, Timofey
Publicado: (2026)

FlowRL: Flow-Augmented Few-Shot Reinforcement Learning for Semi-Structured Sensor Data
por: Pivezhandi, Mohammad, et al.
Publicado: (2024)

A Parallel Hybrid Action Space Reinforcement Learning Model for Real-world Adaptive Traffic Signal Control
por: Wang, Yuxuan, et al.
Publicado: (2025)

Predicting and improving test-time scaling laws via reward tail-guided search
por: Li, Muheng, et al.
Publicado: (2026)

NeSIG: A Neuro-Symbolic Method for Learning to Generate Planning Problems
por: Núñez-Molina, Carlos, et al.
Publicado: (2023)

Constrained Auto-Bidding via Generative Response Modeling
por: Yang, Eunseok, et al.
Publicado: (2026)

Fractional Policy Gradients: Reinforcement Learning with Long-Term Memory
por: Pawar, Urvi, et al.
Publicado: (2025)

Learning to Select Goals in Automated Planning with Deep-Q Learning
por: Núñez-Molina, Carlos, et al.
Publicado: (2024)

Selective Progress-Aware Querying for Human-in-the-Loop Reinforcement Learning
por: Muraleedharan, Anujith, et al.
Publicado: (2025)