Cover Image

Lipschitz Constant Meets Condition Number: Learning Robust and Compact Deep Neural Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Feng, Yangqi, Lin, Shing-Ho J., Gao, Baoyuan, Wei, Xian
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Enhancing Certifiable Semantic Robustness via Robust Pruning of Deep Neural Networks
by: Hu, Hanjiang, et al.
Published: (2025)

When Invariant Representation Learning Meets Label Shift: Insufficiency and Theoretical Insights
by: Luo, You-Wei, et al.
Published: (2024)

Verification of Geometric Robustness of Neural Networks via Piecewise Linear Approximation and Lipschitz Optimisation
by: Batten, Ben, et al.
Published: (2024)

OmniField: Conditioned Neural Fields for Robust Multimodal Spatiotemporal Learning
by: Valencia, Kevin, et al.
Published: (2025)

COD: Learning Conditional Invariant Representation for Domain Adaptation Regression
by: Yang, Hao-Ran, et al.
Published: (2024)

Memory Efficient Neural Processes via Constant Memory Attention Block
by: Feng, Leo, et al.
Published: (2023)

Classification of Polarimetric SAR Images Using Compact Convolutional Neural Networks
by: Ahishali, Mete, et al.
Published: (2020)

Perturbation on Feature Coalition: Towards Interpretable Deep Neural Networks
by: Hu, Xuran, et al.
Published: (2024)

Calibrating Deep Neural Network using Euclidean Distance
by: Liang, Wenhao, et al.
Published: (2024)

Deep Learning Meets OBIA: Tasks, Challenges, Strategies, and Perspectives
by: Ma, Lei, et al.
Published: (2024)

DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks
by: Fu, Yonggan, et al.
Published: (2022)

Quantized and Interpretable Learning Scheme for Deep Neural Networks in Classification Task
by: Maleki, Alireza, et al.
Published: (2024)

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks
by: Mecharbat, Lotfi Abdelkrim, et al.
Published: (2025)

Curvature Learning for Generalization of Hyperbolic Neural Networks
by: Fan, Xiaomeng, et al.
Published: (2025)

Automatic Construction of Pattern Classifiers Capable of Continuous Incremental Learning and Unlearning Tasks Based on Compact-Sized Probabilistic Neural Network
by: Hoya, Tetsuya, et al.
Published: (2025)

Deep Kronecker Network
by: Feng, Long, et al.
Published: (2022)

Dual Precision Deep Neural Network
by: Park, Jae Hyun, et al.
Published: (2020)

TinyVQA: Compact Multimodal Deep Neural Network for Visual Question Answering on Resource-Constrained Devices
by: Rashid, Hasib-Al, et al.
Published: (2024)

Robustness of Deep Neural Networks for Micro-Doppler Radar Classification
by: Czerkawski, Mikolaj, et al.
Published: (2024)

Adaptive Data Dropout: Towards Self-Regulated Learning in Deep Neural Networks
by: Gahir, Amar, et al.
Published: (2026)

How Deep Neural Networks Learn Compositional Data: The Random Hierarchy Model
by: Cagnetta, Francesco, et al.
Published: (2023)

Revisiting Neural Networks for Continual Learning: An Architectural Perspective
by: Lu, Aojun, et al.
Published: (2024)

Optimizing Retinal Prosthetic Stimuli with Conditional Invertible Neural Networks
by: Wu, Yuli, et al.
Published: (2024)

Compositional Curvature Bounds for Deep Neural Networks
by: Entesari, Taha, et al.
Published: (2024)

DQA: An Efficient Method for Deep Quantization of Deep Neural Network Activations
by: Hu, Wenhao, et al.
Published: (2024)

The Curse of Conditions: Analyzing and Improving Optimal Transport for Conditional Flow-Based Generation
by: Cheng, Ho Kei, et al.
Published: (2025)

Tuning the Frequencies: Robust Training for Sinusoidal Neural Networks
by: Novello, Tiago, et al.
Published: (2024)

Improved Regularization and Robustness for Fine-tuning in Neural Networks
by: Li, Dongyue, et al.
Published: (2021)

Towards Robust Neural Networks via Orthogonal Diversity
by: Fang, Kun, et al.
Published: (2020)

Growing Efficient Accurate and Robust Neural Networks on the Edge
by: Sundaresha, Vignesh, et al.
Published: (2024)

Enhancing JEPAs with Spatial Conditioning: Robust and Efficient Representation Learning
by: Littwin, Etai, et al.
Published: (2024)

An Experimental Study of Semantic Continuity for Deep Learning Models
by: Wu, Shangxi, et al.
Published: (2020)

Occlusion-Aware Deep Convolutional Neural Network via Homogeneous Tanh-transforms for Face Parsing
by: Qiua, Jianhua, et al.
Published: (2023)

An Explainable Fast Deep Neural Network for Emotion Recognition
by: Di Luzio, Francesco, et al.
Published: (2024)

Revisiting the Evaluation of Deep Neural Networks for Pedestrian Detection
by: Feifel, Patrick, et al.
Published: (2025)

Compact Twice Fusion Network for Edge Detection
by: Li, Yachuan, et al.
Published: (2023)

Language Embedding Meets Dynamic Graph: A New Exploration for Neural Architecture Representation Learning
by: Jing, Haizhao, et al.
Published: (2025)

Sparse Representations Improve Adversarial Robustness of Neural Network Classifiers
by: Steunou, Killian, et al.
Published: (2025)

A New Formulation of Lipschitz Constrained With Functional Gradient Learning for GANs
by: Wan, Chang, et al.
Published: (2025)

Conditional Uncertainty-Aware Political Deepfake Detection with Stochastic Convolutional Neural Networks
by: Gardoş, Rafael-Petruţ
Published: (2026)