:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Zeng, Xuanrui
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2410.04722
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Pluralistic Alignment for Healthcare: A Role-Driven Framework
by: Zhong, Jiayou, et al.
Published: (2025)

Semantic Segmentation from Image Labels by Reconstruction from Structured Decomposition
by: Zeng, Xuanrui
Published: (2024)

Geometric and Spectral Alignment for Deep Neural Network I
by: Liu, Ziran, et al.
Published: (2026)

Geometric and Spectral Alignment for Deep Neural Network II
by: Liu, Ziran, et al.
Published: (2026)

Connecting Concept Convexity and Human-Machine Alignment in Deep Neural Networks
by: Dorszewski, Teresa, et al.
Published: (2024)

Multi-View Subgraph Neural Networks: Self-Supervised Learning with Scarce Labeled Data
by: Wang, Zhenzhong, et al.
Published: (2024)

Label Alignment Regularization for Distribution Shift
by: Imani, Ehsan, et al.
Published: (2022)

Deep Latent Variable Model based Vertical Federated Learning with Flexible Alignment and Labeling Scenarios
by: Hong, Kihun, et al.
Published: (2025)

DeepDefense: Layer-Wise Gradient-Feature Alignment for Building Robust Neural Networks
by: Lin, Ci, et al.
Published: (2025)

Feature-Label Modal Alignment for Robust Partial Multi-Label Learning
by: Chen, Yu, et al.
Published: (2026)

On the Neural Feature Ansatz for Deep Neural Networks
by: Tansley, Edward, et al.
Published: (2025)

A Review of Neural Networks in Precipitation Prediction
by: Zeng, Yugong, et al.
Published: (2025)

Graph Random Walk with Feature-Label Space Alignment: A Multi-Label Feature Selection Method
by: Gao, Wanfu, et al.
Published: (2025)

Hard-Label Cryptanalytic Extraction of Neural Network Models
by: Chen, Yi, et al.
Published: (2024)

A Theoretical Analysis of Soft-Label vs Hard-Label Training in Neural Networks
by: Mandal, Saptarshi, et al.
Published: (2024)

Flag Varieties: A Geometric Framework for Deep Network Alignment
by: Xiao, Jingchuan, et al.
Published: (2026)

Learned Random Label Predictions as a Neural Network Complexity Metric
by: Becker, Marlon, et al.
Published: (2024)

Improving Graph Neural Networks on Multi-node Tasks with the Labeling Trick
by: Wang, Xiyuan, et al.
Published: (2023)

Fed-Listing: Federated Label Distribution Inference in Graph Neural Networks
by: Nakarmi, Suprim, et al.
Published: (2026)

Implicit Regularization in Feedback Alignment Learning Mechanisms for Neural Networks
by: Robertson, Zachary, et al.
Published: (2023)

Spectral Alignment as Predictor of Loss Explosion in Neural Network Training
by: Qiu, Haiquan, et al.
Published: (2025)

PLANETALIGN: A Comprehensive Python Library for Benchmarking Network Alignment
by: Yu, Qi, et al.
Published: (2025)

Label-NTK Alignments and A Tighter Convergence Bound in the NTK Regime
by: Marreddy, Ruchirinkil, et al.
Published: (2026)

On the Stability of Neural Networks in Deep Learning
by: Delattre, Blaise
Published: (2025)

Exact Certification of (Graph) Neural Networks Against Label Poisoning
by: Sabanayagam, Mahalakshmi, et al.
Published: (2024)

Training-free Graph Neural Networks and the Power of Labels as Features
by: Sato, Ryoma
Published: (2024)

Rethinking Neural Network Learning Rates: A Stackelberg Perspective
by: Zeng, Sihan, et al.
Published: (2026)

Label Propagation Training Schemes for Physics-Informed Neural Networks and Gaussian Processes
by: Zhong, Ming, et al.
Published: (2024)

Exact Certification of Neural Networks and Partition Aggregation Ensembles against Label Poisoning
by: Mohgaonkar, Ajinkya, et al.
Published: (2026)

Deep Grokking: Would Deep Neural Networks Generalize Better?
by: Fan, Simin, et al.
Published: (2024)

CASUAL: Conditional Support Alignment for Domain Adaptation with Label Shift
by: Nguyen, Anh T, et al.
Published: (2023)

Forest-Guided Semantic Transport for Label-Supervised Manifold Alignment
by: Aumon, Adrien, et al.
Published: (2026)

Architectural Strategies for the optimization of Physics-Informed Neural Networks
by: Saratchandran, Hemanth, et al.
Published: (2024)

Not Just Change the Labels, Learn the Features: Watermarking Deep Neural Networks with Multi-View Data
by: Li, Yuxuan, et al.
Published: (2024)

Graph Neural Networks for Protein-Protein Interactions -- A Short Survey
by: Xu, Mingda, et al.
Published: (2024)

ESSA: Evolutionary Strategies for Scalable Alignment
by: Korotyshova, Daria, et al.
Published: (2025)

Towards Certified Unlearning for Deep Neural Networks
by: Zhang, Binchi, et al.
Published: (2024)

On Local Overfitting and Forgetting in Deep Neural Networks
by: Stern, Uri, et al.
Published: (2024)

On the Hardness of Training Deep Neural Networks Discretely
by: Doron-Arad, Ilan
Published: (2024)

On Expressivity of Height in Neural Networks
by: Fan, Feng-Lei, et al.
Published: (2023)