:: Library Catalog

Saved in:

Bibliographic Details
Main Author:	Bao, Han
Format:	Preprint
Published:	2023
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2309.16109
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

PhiNets: Brain-inspired Non-contrastive Learning Based on Temporal Prediction Hypothesis
by: Ishikawa, Satoki, et al.
Published: (2024)

Preventing Collapse in Contrastive Learning with Orthonormal Prototypes (CLOP)
by: Li, Huanran, et al.
Published: (2024)

TQL: Scaling Q-Functions with Transformers by Preventing Attention Collapse
by: Dong, Perry, et al.
Published: (2026)

Explaining and Preventing Alignment Collapse in Iterative RLHF
by: Gauthier, Etienne, et al.
Published: (2026)

Golden Ratio Weighting Prevents Model Collapse
by: He, Hengzhi, et al.
Published: (2025)

Preventing Model Collapse via Contraction-Conditioned Neural Filters
by: Han, Zongjian, et al.
Published: (2025)

Why Prototypes Collapse: Diagnosing and Preventing Partial Collapse in Prototypical Self-Supervised Learning
by: Arteaga, Gabriel Y., et al.
Published: (2025)

Preventing Dimensional Collapse in Self-Supervised Learning via Orthogonality Regularization
by: He, Junlin, et al.
Published: (2024)

Neural Collapse Dynamics: Depth, Activation, Regularisation, and Feature Norm Threshold
by: Rupa, Anamika Paul
Published: (2026)

Preventing Model Collapse in Gaussian Process Latent Variable Models
by: Li, Ying, et al.
Published: (2024)

Preventing Representational Rank Collapse in MPNNs by Splitting the Computational Graph
by: Roth, Andreas, et al.
Published: (2024)

Collapse-Proof Non-Contrastive Self-Supervised Learning
by: Sansone, Emanuele, et al.
Published: (2024)

Preventing Curriculum Collapse in Self-Evolving Reasoning Systems
by: Mishra, Vaibhav
Published: (2026)

A Theoretical Framework for Preventing Class Collapse in Supervised Contrastive Learning
by: Lee, Chungpa, et al.
Published: (2025)

Sequential Subspace Noise Injection Prevents Accuracy Collapse in Certified Unlearning
by: Dolgova, Polina, et al.
Published: (2026)

Preventing Model Collapse in Deep Canonical Correlation Analysis by Noise Regularization
by: He, Junlin, et al.
Published: (2024)

LaDi-RL: Latent Diffusion Reasoning Prevents Entropy Collapse in Reinforcement Learning
by: Kang, Haoqiang, et al.
Published: (2026)

Towards Understanding Neural Collapse: The Effects of Batch Normalization and Weight Decay
by: Pan, Leyan, et al.
Published: (2023)

IConE: Batch Independent Collapse Prevention for Self-Supervised Representation Learning
by: Almpanakis, Konstantinos, et al.
Published: (2026)

Anchored Alignment: Preventing Positional Collapse in Multimodal Recommender Systems
by: Jeong, Yonghun, et al.
Published: (2026)

Hard Regularization to Prevent Deep Online Clustering Collapse without Data Augmentation
by: Mahon, Louis, et al.
Published: (2023)

Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse
by: Alman, Josh, et al.
Published: (2025)

Neural Collapse Beyond the Unconstrained Features Model: Landscape, Dynamics, and Generalization in the Mean-Field Regime
by: Wu, Diyuan, et al.
Published: (2025)

Residual Connections and Normalization Can Provably Prevent Oversmoothing in GNNs
by: Scholkemper, Michael, et al.
Published: (2024)

Understanding and Preventing Entropy Collapse in RLVR with On-Policy Entropy Flow Optimization
by: Xu, Huimin, et al.
Published: (2026)

CURE: Critical-Token-Guided Re-Concatenation for Entropy-Collapse Prevention
by: Li, Qingbin, et al.
Published: (2025)

Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning
by: Arefin, Md Rifat, et al.
Published: (2024)

Preventing Model Collapse Under Overparametrization: Optimal Mixing Ratios for Interpolation Learning and Ridge Regression
by: Garg, Anvit, et al.
Published: (2025)

Neural Collapse for Cross-entropy Class-Imbalanced Learning with Unconstrained ReLU Feature Model
by: Dang, Hien, et al.
Published: (2024)

Domain Feature Collapse: Implications for Out-of-Distribution Detection and Solutions
by: Yang, Hong, et al.
Published: (2025)

Normalization in Proportional Feature Spaces
by: Benatti, Alexandre, et al.
Published: (2024)

A Theoretical Perspective: How to Prevent Model Collapse in Self-consuming Training Loops
by: Fu, Shi, et al.
Published: (2025)

Non-Stationary Online Structured Prediction with Surrogate Losses
by: Sakaue, Shinsaku, et al.
Published: (2025)

Non-Normal Diffusion Models
by: Li, Henry
Published: (2024)

Confounder-Free Continual Learning via Recursive Feature Normalization
by: Shah, Yash, et al.
Published: (2025)

Beyond Unconstrained Features: Neural Collapse for Shallow Neural Networks with General Data
by: Hong, Wanli, et al.
Published: (2024)

Age-Normalized HRV Features for Non-Invasive Glucose Prediction: A Pilot Sleep-Aware Machine Learning Study
by: Azam, Md Basit, et al.
Published: (2025)

Preventing Rank Collapse in Federated Low-Rank Adaptation with Client Heterogeneity
by: Wu, Fei, et al.
Published: (2026)

Silent Collapse in Recursive Learning Systems
by: Zhang, Zhipeng
Published: (2026)

CLeAN: Continual Learning Adaptive Normalization in Dynamic Environments
by: Marasco, Isabella, et al.
Published: (2026)