Cover Image

Scaling Adversarial Training via Data Selection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ye, Youran, Wang, Dejin, Bhandare, Ajinkya
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Synthesizing Tabular Data Using Selectivity Enhanced Generative Adversarial Networks
by: Zhou, Youran, et al.
Published: (2025)

Enhancing Stability in Training Conditional Generative Adversarial Networks via Selective Data Matching
by: Kong, Kyeongbo, et al.
Published: (2021)

Scalable Multi-Objective and Meta Reinforcement Learning via Gradient Estimation
by: Zhang, Zhenshuo, et al.
Published: (2025)

IVGAE: Handling Incomplete Heterogeneous Data with a Variational Graph Autoencoder
by: Zhou, Youran, et al.
Published: (2025)

Large-Scale Dataset Pruning in Adversarial Training through Data Importance Extrapolation
by: Nieth, Björn, et al.
Published: (2024)

Data-Dependent Stability Analysis of Adversarial Training
by: Wang, Yihan, et al.
Published: (2024)

HI-PMK: A Data-Dependent Kernel for Incomplete Heterogeneous Data Representation
by: Zhou, Youran, et al.
Published: (2025)

Scaling Multi-Hop Training Data via Graph-Constrained Path Selection
by: Chen, Pengyu, et al.
Published: (2026)

Adversarial Training via Adaptive Knowledge Amalgamation of an Ensemble of Teachers
by: Hamidi, Shayan Mohajer, et al.
Published: (2024)

Correcting Mean Bias in Text Embeddings: A Refined Renormalization with Training-Free Improvements on MMTEB
by: Ren, Xingyu, et al.
Published: (2025)

MissHDD: Hybrid Deterministic Diffusion for Hetrogeneous Incomplete Data Imputation
by: Zhou, Youran, et al.
Published: (2025)

Adversarial Training: A Survey
by: Zhao, Mengnan, et al.
Published: (2024)

The Impact of Scaling Training Data on Adversarial Robustness
by: Zimmerli, Marco, et al.
Published: (2025)

MissMecha: An All-in-One Python Package for Studying Missing Data Mechanisms
by: Zhou, Youran, et al.
Published: (2025)

Review for Handling Missing Data with special missing mechanism
by: Zhou, Youran, et al.
Published: (2024)

Single-Rollout Hidden-State Dynamics for Training-Free RLVR Data Selection
by: Wu, Jianghao, et al.
Published: (2026)

Training-free Heterogeneous Graph Condensation via Data Selection
by: Liang, Yuxuan, et al.
Published: (2024)

Combatting Dimensional Collapse in LLM Pre-Training Data via Diversified File Selection
by: Fan, Ziqing, et al.
Published: (2025)

Joint Selection for Large-Scale Pre-Training Data via Policy Gradient-based Mask Learning
by: Fan, Ziqing, et al.
Published: (2025)

Efficient RLVR Training via Weighted Mutual Information Data Selection
by: Zhou, Xinyu, et al.
Published: (2026)

TableGuard -- Securing Structured & Unstructured Data
by: Sharma, Anantha, et al.
Published: (2024)

Efficient Data Selection at Scale via Influence Distillation
by: Nikdan, Mahdi, et al.
Published: (2025)

Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective
by: Xing, Yue, et al.
Published: (2024)

Developing robust methods to handle missing data in real-world applications effectively
by: Zhou, Youran, et al.
Published: (2025)

Adversarial Training of Reward Models
by: Bukharin, Alexander, et al.
Published: (2025)

Enhancing Adversarial Robustness via Uncertainty-Aware Distributional Adversarial Training
by: Dong, Junhao, et al.
Published: (2024)

New Paradigm of Adversarial Training: Releasing Accuracy-Robustness Trade-Off via Dummy Class
by: Wang, Yanyun, et al.
Published: (2024)

Selective Prediction via Training Dynamics
by: Rabanser, Stephan, et al.
Published: (2022)

Robustness Against Adversarial Attacks via Learning Confined Adversarial Polytopes
by: Hamidi, Shayan Mohajer, et al.
Published: (2024)

On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
by: Liu, Chen, et al.
Published: (2021)

Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Training
by: Pan, Yuhao, et al.
Published: (2025)

TRIX- Trading Adversarial Fairness via Mixed Adversarial Training
by: Medi, Tejaswini, et al.
Published: (2025)

Conflict-Aware Adversarial Training
by: Xue, Zhiyu, et al.
Published: (2024)

Lightweight Safety Guardrails via Synthetic Data and RL-guided Adversarial Training
by: Ilin, Aleksei, et al.
Published: (2025)

SPriFed-OMP: A Differentially Private Federated Learning Algorithm for Sparse Basis Recovery
by: Mulay, Ajinkya Kiran, et al.
Published: (2024)

Understanding and Improving Continuous Adversarial Training for LLMs via In-context Learning Theory
by: Fu, Shaopeng, et al.
Published: (2026)

Learning Images Across Scales Using Adversarial Training
by: Wolski, Krzysztof, et al.
Published: (2024)

Detecting Adversarial Data via Provable Adversarial Noise Amplification
by: Mumcu, Furkan, et al.
Published: (2026)

Enhancing Adversarial Training via Reweighting Optimization Trajectory
by: Huang, Tianjin, et al.
Published: (2023)

Adversarial Attacks on Data Attribution
by: Wang, Xinhe, et al.
Published: (2024)