Image de couverture de livre

Asymptotic Midpoint Mixup for Margin Balancing and Moderate Broadening

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Kim, Hoyong, Lee, Semi, Kim, Kangil
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Revisiting Softmax Masking: Stop Gradient for Enhancing Stability in Replay-based Continual Learning
par: Kim, Hoyong, et autres
Publié: (2023)

Provably Learning Diverse Features in Multi-View Data with Midpoint Mixup
par: Chidambaram, Muthu, et autres
Publié: (2022)

CFASL: Composite Factor-Aligned Symmetry Learning for Disentanglement in Variational AutoEncoder
par: Jung, Hee-Jun, et autres
Publié: (2024)

Multiple Invertible and Partial-Equivariant Function for Latent Vector Transformation to Enhance Disentanglement in VAEs
par: Jung, Hee-Jun, et autres
Publié: (2025)

Toward Reasoning on the Boundary: A Mixup-based Approach for Graph Anomaly Detection
par: Kim, Hwan, et autres
Publié: (2024)

Feature Structure Distillation with Centered Kernel Alignment in BERT Transferring
par: Jung, Hee-Jun, et autres
Publié: (2022)

Learning from Matured Dumb Teacher for Fine Generalization
par: Jung, HeeSeung, et autres
Publié: (2021)

Tailoring Mixup to Data for Calibration
par: Bouniot, Quentin, et autres
Publié: (2023)

On the Equivalence of Graph Convolution and Mixup
par: Han, Xiaotian, et autres
Publié: (2023)

Difficulty-aware Balancing Margin Loss for Long-tailed Recognition
par: Son, Minseok, et autres
Publié: (2024)

Beyond 5G Network Failure Classification for Network Digital Twin Using Graph Neural Network
par: Isah, Abubakar, et autres
Publié: (2024)

FIRE: Frobenius-Isometry Reinitialization for Balancing the Stability-Plasticity Tradeoff
par: Han, Isaac, et autres
Publié: (2026)

Importance Analysis for Dynamic Control of Balancing Parameter in a Simple Knowledge Distillation Setting
par: Kim, Seongmin, et autres
Publié: (2025)

Nevermind: Instruction Override and Moderation in Large Language Models
par: Kim, Edward
Publié: (2024)

AGMixup: Adaptive Graph Mixup for Semi-supervised Node Classification
par: Lu, Weigang, et autres
Publié: (2024)

Mixup Domain Adaptations for Dynamic Remaining Useful Life Predictions
par: Furqon, Muhammad Tanzil, et autres
Publié: (2024)

ID-MixGCL: Identity Mixup for Graph Contrastive Learning
par: Zhang, Gehang, et autres
Publié: (2023)

Sensor Calibration Model Balancing Accuracy, Real-time, and Efficiency
par: Yun, Jinyong, et autres
Publié: (2025)

On the Effectiveness of Hybrid Pooling in Mixup-Based Graph Learning for Language Processing
par: Dong, Zeming, et autres
Publié: (2022)

GradMix: Gradient-based Selective Mixup for Robust Data Augmentation in Class-Incremental Learning
par: Kim, Minsu, et autres
Publié: (2025)

AdaMixup: A Dynamic Defense Framework for Membership Inference Attack Mitigation
par: Chen, Ying, et autres
Publié: (2025)

CUBE: Contrastive Understanding by Balanced Experiments
par: Kim, Dongseok, et autres
Publié: (2025)

Separating Novel Features for Logical Anomaly Detection: A Straightforward yet Effective Approach
par: Lee, Kangil, et autres
Publié: (2024)

CAPMix: Robust Time Series Anomaly Detection Based on Abnormal Assumptions with Dual-Space Mixup
par: Mou, Xudong, et autres
Publié: (2025)

MathMixup: Boosting LLM Mathematical Reasoning with Difficulty-Controllable Data Synthesis and Curriculum Learning
par: Li, Xuchen, et autres
Publié: (2026)

Subspace-based Approximate Hessian Method for Zeroth-Order Optimization
par: Kim, Dongyoon, et autres
Publié: (2025)

Hybrid Spectro-Temporal Fusion Framework for Structural Health Monitoring
par: Kim, Jongyeop, et autres
Publié: (2026)

Fair Bayesian Model-Based Clustering
par: Lee, Jihu, et autres
Publié: (2025)

Preserve-Then-Quantize: Balancing Rank Budgets for Quantization Error Reconstruction in LLMs
par: Cho, Yoonjun, et autres
Publié: (2026)

SFTMix: Elevating Language Model Instruction Tuning with Mixup Recipe
par: Xiao, Yuxin, et autres
Publié: (2024)

A Survey on Mixup Augmentations and Beyond
par: Jin, Xin, et autres
Publié: (2024)

Region Mixup
par: Saha, Saptarshi, et autres
Publié: (2024)

CleaR: Towards Robust and Generalized Parameter-Efficient Fine-Tuning for Noisy Label Learning
par: Kim, Yeachan, et autres
Publié: (2024)

MUXQ: Mixed-to-Uniform Precision MatriX Quantization via Low-Rank Outlier Decomposition
par: Lee, Seoungsub, et autres
Publié: (2026)

Inconsistency-Aware Minimization: Improving Generalization with Unlabeled Data
par: Kim, Hee-Sung, et autres
Publié: (2026)

Pioneering 4-Bit FP Quantization for Diffusion Models: Mixup-Sign Quantization and Timestep-Aware Fine-Tuning
par: Zhao, Maosen, et autres
Publié: (2025)

ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models
par: Kim, Dongha, et autres
Publié: (2023)

eMargin: Revisiting Contrastive Learning with Margin-Based Separation
par: Shamba, Abdul-Kazeem, et autres
Publié: (2025)

FEATHer: Fourier-Efficient Adaptive Temporal Hierarchy Forecaster for Time-Series Forecasting
par: Lee, Jaehoon, et autres
Publié: (2026)

Enhancing Anomaly Detection via Generating Diversified and Hard-to-distinguish Synthetic Anomalies
par: Kim, Hyuntae, et autres
Publié: (2024)