Cover Image

ReLU integral probability metric and its applications

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Park, Yuha, Kim, Kunwoong, Kong, Insung, Kim, Yongdai
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fair Representation Learning for Continuous Sensitive Attributes using Expectation of Integral Probability Metrics
by: Kong, Insung, et al.
Published: (2025)

Doubly-Regressing Approach for Subgroup Fairness
by: Kim, Kunwoong, et al.
Published: (2025)

Fairness Through Matching
by: Kim, Kunwoong, et al.
Published: (2025)

Posterior concentrations of fully-connected Bayesian neural networks with general priors on the weights
by: Kong, Insung, et al.
Published: (2024)

Bayesian Additive Regression Trees for functional ANOVA model
by: Park, Seokhun, et al.
Published: (2025)

Fair Bayesian Model-Based Clustering
by: Lee, Jihu, et al.
Published: (2025)

Fair Model-based Clustering
by: Park, Jinwon, et al.
Published: (2026)

Knowledge Distillation of Uncertainty using Deep Latent Factor Model
by: Park, Sehyun, et al.
Published: (2025)

Fair Clustering via Alignment
by: Kim, Kunwoong, et al.
Published: (2025)

SLIDE: a surrogate fairness constraint to ensure fairness consistency
by: Kim, Kunwoong, et al.
Published: (2022)

Tensor Product Neural Networks for Functional ANOVA Model
by: Park, Seokhun, et al.
Published: (2025)

A Composite Activation Function for Learning Stable Binary Representations
by: Park, Seokhun, et al.
Published: (2026)

Bayesian Neural Networks for Functional ANOVA model
by: Park, Seokhun, et al.
Published: (2025)

ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models
by: Kim, Dongha, et al.
Published: (2023)

Minimum width for universal approximation using ReLU networks on compact domain
by: Kim, Namjun, et al.
Published: (2023)

Hyper Input Convex Neural Networks for Shape Constrained Learning and Optimal Transport
by: Hundrieser, Shayan, et al.
Published: (2026)

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

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

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

Generalization analysis with deep ReLU networks for metric and similarity learning
by: Zhou, Junyu, et al.
Published: (2024)

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

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

Convex Relaxations of ReLU Neural Networks Approximate Global Optima in Polynomial Time
by: Kim, Sungyoon, et al.
Published: (2024)

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

Symmetric Matrix Completion with ReLU Sampling
by: Liu, Huikang, et al.
Published: (2024)

Explicit integral representations and quantitative bounds for two-layer ReLU networks
by: Lee, Anthony
Published: (2026)

The Cost of Robustness: Tighter Bounds on Parameter Complexity for Robust Memorization in ReLU Nets
by: Kim, Yujun, et al.
Published: (2025)

Expressive Power of ReLU and Step Networks under Floating-Point Operations
by: Park, Yeachan, et al.
Published: (2024)

Is ReLU Adversarially Robust?
by: Sooksatra, Korn, et al.
Published: (2024)

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

Benign Overfitting for Regression with Trained Two-Layer ReLU Networks
by: Park, Junhyung, et al.
Published: (2024)

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

Toric geometry of ReLU neural networks
by: Fu, Yaoying
Published: (2025)

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

Nearly Optimal Differentially Private ReLU Regression
by: Ding, Meng, et al.
Published: (2025)

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

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

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

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

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