Image de couverture de livre

SDP-CROWN: Efficient Bound Propagation for Neural Network Verification with Tightness of Semidefinite Programming

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Chiu, Hong-Ming, Chen, Hao, Zhang, Huan, Zhang, Richard Y.
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Chordal Sparsity for SDP-based Neural Network Verification
par: Xue, Anton, et autres
Publié: (2022)

Bridging Control with Neural Network Verifier alpha-beta-CROWN: A Tutorial
par: Li, Haoyu, et autres
Publié: (2026)

E-Globe: Scalable $ε$-Global Verification of Neural Networks via Tight Upper Bounds and Pattern-Aware Branching
par: Li, Wenting, et autres
Publié: (2026)

Training Safe Neural Networks with Global SDP Bounds
par: Soletskyi, Roman, et autres
Publié: (2024)

Neural Network Verification with Branch-and-Bound for General Nonlinearities
par: Shi, Zhouxing, et autres
Publié: (2024)

Statistically Optimal K-means Clustering via Nonnegative Low-rank Semidefinite Programming
par: Zhuang, Yubo, et autres
Publié: (2023)

Well-conditioned Primal-Dual Interior-point Method for Accurate Low-rank Semidefinite Programming
par: Chiu, Hong-Ming, et autres
Publié: (2024)

Fast and Accurate Estimation of Low-Rank Matrices from Noisy Measurements via Preconditioned Non-Convex Gradient Descent
par: Zhang, Gavin, et autres
Publié: (2023)

Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees
par: Zhang, Guanqin, et autres
Publié: (2025)

Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification
par: Fukuda, Kota, et autres
Publié: (2025)

Verification of Neural Control Barrier Functions with Symbolic Derivative Bounds Propagation
par: Hu, Hanjiang, et autres
Publié: (2024)

Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification
par: Ueda, Ryota, et autres
Publié: (2025)

Scalable Verification of Neural Control Barrier Functions Using Linear Bound Propagation
par: Vertovec, Nikolaus, et autres
Publié: (2025)

Provably Bounding Neural Network Preimages
par: Kotha, Suhas, et autres
Publié: (2023)

Tight and Efficient Upper Bound on Spectral Norm of Convolutional Layers
par: Grishina, Ekaterina, et autres
Publié: (2024)

Branch and Bound for Piecewise Linear Neural Network Verification
par: Bunel, Rudy, et autres
Publié: (2019)

Scalable Neural Network Verification with Branch-and-bound Inferred Cutting Planes
par: Zhou, Duo, et autres
Publié: (2024)

On Integer Programming for the Binarized Neural Network Verification Problem
par: Kim, Woojin, et autres
Publié: (2025)

Quantum Interval Bound Propagation for Certified Training of Quantum Neural Networks
par: Andrews, Emma, et autres
Publié: (2026)

Semidefinite Programming for Quantum Channel Learning
par: Belov, Mikhail Gennadievich, et autres
Publié: (2026)

Robustness Verification of Polynomial Neural Networks
par: Alexandr, Yulia, et autres
Publié: (2026)

Solving Probabilistic Verification Problems of Neural Networks using Branch and Bound
par: Boetius, David, et autres
Publié: (2024)

Hierarchical End-to-End Taylor Bounds for Complete Neural Network Verification
par: Entesari, Taha, et autres
Publié: (2026)

Efficient Verification of Neural Control Barrier Functions with Smooth Nonlinear Activations
par: Zhang, Jun, et autres
Publié: (2026)

Generalization Bounds for Neural Belief Propagation Decoders
par: Adiga, Sudarshan, et autres
Publié: (2023)

Clip-and-Verify: Linear Constraint-Driven Domain Clipping for Accelerating Neural Network Verification
par: Zhou, Duo, et autres
Publié: (2025)

An Optimal Tightness Bound for the Simulation Lemma
par: Lobel, Sam, et autres
Publié: (2024)

Towards Optimal Branching of Linear and Semidefinite Relaxations for Neural Network Robustness Certification
par: Anderson, Brendon G., et autres
Publié: (2021)

Normalize Then Propagate: Efficient Homophilous Regularization for Few-shot Semi-Supervised Node Classification
par: Zhang, Baoming, et autres
Publié: (2025)

Tight Robustness Certificates and Wasserstein Distributional Attacks for Deep Neural Networks
par: Le, Bach C., et autres
Publié: (2025)

On the Expressive Power of Subgraph Graph Neural Networks for Graphs with Bounded Cycles
par: Chen, Ziang, et autres
Publié: (2025)

Exploring and Improving Initialization for Deep Graph Neural Networks: A Signal Propagation Perspective
par: Wang, Senmiao, et autres
Publié: (2025)

Label Propagation Training Schemes for Physics-Informed Neural Networks and Gaussian Processes
par: Zhong, Ming, et autres
Publié: (2024)

A Semidefinite Programming-Based Branch-and-Cut Algorithm for Biclustering
par: Sudoso, Antonio M.
Publié: (2024)

Neural Network Verification is a Programming Language Challenge
par: Cordeiro, Lucas C., et autres
Publié: (2025)

Which Algorithms Have Tight Generalization Bounds?
par: Gastpar, Michael, et autres
Publié: (2024)

Dendritic Neural Networks with Equilibrium Propagation
par: Kubo, Yoshimasa
Publié: (2026)

Sparse Explanations of Neural Networks Using Pruned Layer-Wise Relevance Propagation
par: Sarmiento, Paulo Yanez, et autres
Publié: (2024)

BaB-prob: Branch and Bound with Preactivation Splitting for Probabilistic Verification of Neural Networks
par: Wang, Fangji, et autres
Publié: (2025)

Heterophilous Distribution Propagation for Graph Neural Networks
par: Zheng, Zhuonan, et autres
Publié: (2024)