Cover Image

On the Local Complexity of Linear Regions in Deep ReLU Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Patel, Niket, Montufar, Guido
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Constraining the outputs of ReLU neural networks
by: Alexandr, Yulia, et al.
Published: (2025)

The Symmetries of Three-Layer ReLU Networks
by: Gegenfurtner, Johanna Marie, et al.
Published: (2026)

Mildly Overparameterized ReLU Networks Have a Favorable Loss Landscape
by: Karhadkar, Kedar, et al.
Published: (2023)

Complexity of Linear Regions in Self-supervised Deep ReLU Networks
by: Muthivhi, Mufhumudzi, et al.
Published: (2026)

Benign overfitting in leaky ReLU networks with moderate input dimension
by: Karhadkar, Kedar, et al.
Published: (2024)

The Computational Complexity of Counting Linear Regions in ReLU Neural Networks
by: Stargalla, Moritz, et al.
Published: (2025)

On Size-Independent Sample Complexity of ReLU Networks
by: Sellke, Mark
Published: (2023)

Discrete Functional Geometry of ReLU Networks via ReLU Transition Graphs
by: Dhayalkar, Sahil Rajesh
Published: (2025)

The Geometry of ReLU Networks through the ReLU Transition Graph
by: Dhayalkar, Sahil Rajesh
Published: (2025)

When Are Bias-Free ReLU Networks Effectively Linear Networks?
by: Zhang, Yedi, et al.
Published: (2024)

SurvReLU: Inherently Interpretable Survival Analysis via Deep ReLU Networks
by: Sun, Xiaotong, et al.
Published: (2024)

Complexity of One-Dimensional ReLU DNNs
by: Kogan, Jonathan, et al.
Published: (2025)

Convergence of Adam in Deep ReLU Networks via Directional Complexity and Kakeya Bounds
by: Sridhar, Anupama, et al.
Published: (2025)

Implicit Hypersurface Approximation Capacity in Deep ReLU Networks
by: Vallin, Jonatan, et al.
Published: (2024)

N-ReLU: Zero-Mean Stochastic Extension of ReLU
by: Manik, Md Motaleb Hossen, et al.
Published: (2025)

Complexity of Injectivity and Verification of ReLU Neural Networks
by: Froese, Vincent, et al.
Published: (2024)

Relating Piecewise Linear Kolmogorov Arnold Networks to ReLU Networks
by: Schoots, Nandi, et al.
Published: (2025)

The Resurrection of the ReLU
by: Horuz, Coşku Can, et al.
Published: (2025)

Understanding Learning Invariance in Deep Linear Networks
by: Duan, Hao, et al.
Published: (2025)

A Lower Bound for the Number of Linear Regions of Ternary ReLU Regression Neural Networks
by: Nakahara, Yuta, et al.
Published: (2025)

Compelling ReLU Networks to Exhibit Exponentially Many Linear Regions at Initialization and During Training
by: Milkert, Max, et al.
Published: (2023)

Deep Network Approximation: Beyond ReLU to Diverse Activation Functions
by: Zhang, Shijun, et al.
Published: (2023)

Deep Learning using Rectified Linear Units (ReLU)
by: Agarap, Abien Fred
Published: (2018)

Just-In-Time Piecewise-Linear Semantics for ReLU-type Networks
by: Duan, Hongyi, et al.
Published: (2025)

Pathwise Explanation of ReLU Neural Networks
by: Lim, Seongwoo, et al.
Published: (2025)

Optimal Sets and Solution Paths of ReLU Networks
by: Mishkin, Aaron, et al.
Published: (2023)

Online Realizable Regression and Applications for ReLU Networks
by: Doron-Arad, Ilan, et al.
Published: (2026)

Convexity in ReLU Neural Networks: beyond ICNNs?
by: Gagneux, Anne, et al.
Published: (2025)

Optimized Weight Initialization on the Stiefel Manifold for Deep ReLU Neural Networks
by: Lee, Hyungu, et al.
Published: (2025)

Why ReLU? A Bit-Model Dichotomy for Deep Network Training
by: Doron-Arad, Ilan, et al.
Published: (2026)

Beyond ReLU: Chebyshev-DQN for Enhanced Deep Q-Networks
by: Yazdannik, Saman, et al.
Published: (2025)

Sobolev Approximation of Deep ReLU Networks in Log-Barron Space
by: Song, Changhoon, et al.
Published: (2026)

Unveiling the Training Dynamics of ReLU Networks through a Linear Lens
by: Ye, Longqing
Published: (2025)

Component-based Sketching for Deep ReLU Nets
by: Wang, Di, et al.
Published: (2024)

Stochastic Bandits with ReLU Neural Networks
by: Xu, Kan, et al.
Published: (2024)

On Space Folds of ReLU Neural Networks
by: Lewandowski, Michal, et al.
Published: (2025)

ReLU-KAN: New Kolmogorov-Arnold Networks that Only Need Matrix Addition, Dot Multiplication, and ReLU
by: Qiu, Qi, et al.
Published: (2024)

Learning to Compress: Local Rank and Information Compression in Deep Neural Networks
by: Patel, Niket, et al.
Published: (2024)

ReLU Networks for Model Predictive Control: Network Complexity and Performance Guarantees
by: Li, Xingchen, et al.
Published: (2026)

Three Quantization Regimes for ReLU Networks
by: Ou, Weigutian, et al.
Published: (2024)