Cover Image

Generative Adversarial Networks for Imputing Sparse Learning Performance

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Liang, Yeasin, Mohammed, Lin, Jionghao, Havugimana, Felix, Hu, Xiangen
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Generative Data Imputation for Sparse Learner Performance Data Using Generative Adversarial Imputation Networks
by: Zhang, Liang, et al.
Published: (2025)

3DG: A Framework for Using Generative AI for Handling Sparse Learner Performance Data From Intelligent Tutoring Systems
by: Zhang, Liang, et al.
Published: (2024)

Data Augmentation for Sparse Multidimensional Learning Performance Data Using Generative AI
by: Zhang, Liang, et al.
Published: (2024)

Predicting Learning Performance with Large Language Models: A Study in Adult Literacy
by: Zhang, Liang, et al.
Published: (2024)

SPL: A Socratic Playground for Learning Powered by Large Language Model
by: Zhang, Liang, et al.
Published: (2024)

Offline Reinforcement Learning with Imputed Rewards
by: Romeo, Carlo, et al.
Published: (2024)

M$^3$-Impute: Mask-guided Representation Learning for Missing Value Imputation
by: Yu, Zhongyi, et al.
Published: (2024)

Towards Interpretable Adversarial Examples via Sparse Adversarial Attack
by: Lin, Fudong, et al.
Published: (2025)

Prediction-Powered Inference with Imputed Covariates and Nonuniform Sampling
by: Kluger, Dan M., et al.
Published: (2025)

Causal-Aware Generative Adversarial Networks with Reinforcement Learning
by: Nguyen, Tu Anh Hoang, et al.
Published: (2025)

A Proposed Paradigm for Imputing Missing Multi-Sensor Data in the Healthcare Domain
by: Gupta, Vaibhav, et al.
Published: (2026)

Impute With Confidence: A Framework for Uncertainty Aware Multivariate Time Series Imputation
by: Weatherhead, Addison, et al.
Published: (2025)

Sparse Decomposition of Graph Neural Networks
by: Hu, Yaochen, et al.
Published: (2024)

DiffImpute: Tabular Data Imputation With Denoising Diffusion Probabilistic Model
by: Wen, Yizhu, et al.
Published: (2024)

Adversarial Generative Flow Network for Solving Vehicle Routing Problems
by: Zhang, Ni, et al.
Published: (2025)

Adaptive Learning of the Latent Space of Wasserstein Generative Adversarial Networks
by: Qiu, Yixuan, et al.
Published: (2024)

Adversarial Signed Graph Learning with Differential Privacy
by: Ke, Haobin, et al.
Published: (2025)

ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data
by: Li, Mengxuan, et al.
Published: (2025)

GAR: Generative Adversarial Reinforcement Learning for Formal Theorem Proving
by: Wang, Ruida, et al.
Published: (2025)

Adversarial Curriculum Graph Contrastive Learning with Pair-wise Augmentation
by: Zhao, Xinjian, et al.
Published: (2024)

Sparse-RL: Breaking the Memory Wall in LLM Reinforcement Learning via Stable Sparse Rollouts
by: Luo, Sijia, et al.
Published: (2026)

Rethinking Adversarial Attacks in Reinforcement Learning from Policy Distribution Perspective
by: Duan, Tianyang, et al.
Published: (2025)

DLGAN : Time Series Synthesis Based on Dual-Layer Generative Adversarial Networks
by: Hou, Xuan, et al.
Published: (2025)

On the Adversarial Transferability of Generalized "Skip Connections"
by: Wang, Yisen, et al.
Published: (2024)

A Dual-Agent Adversarial Framework for Robust Generalization in Deep Reinforcement Learning
by: Xie, Zhengpeng, et al.
Published: (2025)

Tutorial on the Probabilistic Unification of Estimation Theory, Machine Learning, and Generative AI
by: Elmusrati, Mohammed
Published: (2025)

Distribution Fitting for Combating Mode Collapse in Generative Adversarial Networks
by: Gong, Yanxiang, et al.
Published: (2022)

Improvement of AMPs Identification with Generative Adversarial Network and Ensemble Classification
by: Keshavarzpour, Reyhaneh, et al.
Published: (2025)

ChronoGAN: Supervised and Embedded Generative Adversarial Networks for Time Series Generation
by: EskandariNasab, MohammadReza, et al.
Published: (2024)

Towards Interpretable and Inference-Optimal COT Reasoning with Sparse Autoencoder-Guided Generation
by: Zhao, Daniel, et al.
Published: (2025)

A Hybrid Model for Traffic Incident Detection based on Generative Adversarial Networks and Transformer Model
by: Lu, Xinying, et al.
Published: (2024)

Certified Robustness against Sparse Adversarial Perturbations via Data Localization
by: Pal, Ambar, et al.
Published: (2024)

Superposition as Lossy Compression: Measure with Sparse Autoencoders and Connect to Adversarial Vulnerability
by: Bereska, Leonard, et al.
Published: (2025)

Fast Adversarial Training against Sparse Attacks Requires Loss Smoothing
by: Zhong, Xuyang, et al.
Published: (2025)

Domain Adversarial Active Learning for Domain Generalization Classification
by: Chen, Jianting, et al.
Published: (2024)

Sparse Interpretable Deep Learning with LIES Networks for Symbolic Regression
by: Montazerin, Mansooreh, et al.
Published: (2025)

Dynamic Adversarial Reinforcement Learning for Robust Multimodal Large Language Models
by: Bao, Yicheng, et al.
Published: (2026)

An Efficient Sparse Kernel Generator for O(3)-Equivariant Deep Networks
by: Bharadwaj, Vivek, et al.
Published: (2025)

CoLoR-GAN: Continual Few-Shot Learning with Low-Rank Adaptation in Generative Adversarial Networks
by: Ali, Munsif, et al.
Published: (2025)

Privacy-Preserving Federated Learning via Homomorphic Adversarial Networks
by: Dong, Wenhan, et al.
Published: (2024)