:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Hong, Kihun, Park, Sejun, Hwang, Ganguk
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2505.11035
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Kernel Perspective on Distillation-based Collaborative Learning
by: Park, Sejun, et al.
Published: (2024)

On Expressive Power of Quantized Neural Networks under Fixed-Point Arithmetic
by: Park, Yeachan, et al.
Published: (2024)

On the Expressive Power of Floating-Point Transformers
by: Park, Sejun, et al.
Published: (2026)

Floating-Point Networks with Automatic Differentiation Can Represent Almost All Floating-Point Functions and Their Gradients
by: Park, Sejun, et al.
Published: (2026)

Expressive Power of Floating-Point Neural Networks with Arbitrary Reduction Orders and Inexact Activation Implementations
by: Park, Yeachan, et al.
Published: (2026)

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

Minimum width for universal approximation using squashable activation functions
by: Shin, Jonghyun, et al.
Published: (2025)

Floating-Point Neural Networks Are Provably Robust Universal Approximators
by: Hwang, Geonho, et al.
Published: (2025)

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

IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs
by: Park, Sejun, et al.
Published: (2024)

LEA: Label Enumeration Attack in Vertical Federated Learning
by: Jiang, Wenhao, et al.
Published: (2026)

Federated Reinforcement Learning in Heterogeneous Environments
by: Hwang, Ukjo, et al.
Published: (2025)

Deep Latent Variable Modeling of Physiological Signals
by: Vo, Khuong
Published: (2024)

Identifying Metric Structures of Deep Latent Variable Models
by: Syrota, Stas, et al.
Published: (2025)

Poisoning Deep Learning Based Recommender Model in Federated Learning Scenarios
by: Rong, Dazhong, et al.
Published: (2022)

LabObf: A Label Protection Scheme for Vertical Federated Learning Through Label Obfuscation
by: He, Ying, et al.
Published: (2024)

TabVFL: Improving Latent Representation in Vertical Federated Learning
by: Rashad, Mohamed, et al.
Published: (2024)

Identifiable Deep Latent Variable Models for MNAR Data
by: Xie, Huiming, et al.
Published: (2026)

MetaGreen: Meta-Learning Inspired Transformer Selection for Green Semantic Communication
by: Mukherjee, Shubhabrata, et al.
Published: (2024)

Federated Learning with Flexible Architectures
by: Park, Jong-Ik, et al.
Published: (2024)

Tree-based Models for Vertical Federated Learning: A Survey
by: Qian, Bingchen, et al.
Published: (2025)

Transfer Learning for Latent Variable Network Models
by: Jalan, Akhil, et al.
Published: (2024)

Towards Privacy-Guaranteed Label Unlearning in Vertical Federated Learning: Few-Shot Forgetting without Disclosure
by: Gu, Hanlin, et al.
Published: (2024)

Revisiting Label Inference Attacks in Vertical Federated Learning: Why They Are Vulnerable and How to Defend
by: Liu, Yige, et al.
Published: (2026)

FedLED: Label-Free Equipment Fault Diagnosis with Vertical Federated Transfer Learning
by: Shen, Jie, et al.
Published: (2023)

KDk: A Defense Mechanism Against Label Inference Attacks in Vertical Federated Learning
by: Arazzi, Marco, et al.
Published: (2024)

A Strategy for Label Alignment in Deep Neural Networks
by: Zeng, Xuanrui
Published: (2024)

Disentanglement Analysis in Deep Latent Variable Models Matching Aggregate Posterior Distributions
by: Saha, Surojit, et al.
Published: (2025)

Federated Automatic Latent Variable Selection in Multi-output Gaussian Processes
by: Gao, Jingyi, et al.
Published: (2024)

Certifying the Right to Be Forgotten: Primal-Dual Optimization for Sample and Label Unlearning in Vertical Federated Learning
by: Jiang, Yu, et al.
Published: (2025)

Transformers for Green Semantic Communication: Less Energy, More Semantics
by: Mukherjee, Shubhabrata, et al.
Published: (2023)

Random Latent Exploration for Deep Reinforcement Learning
by: Mahankali, Srinath, et al.
Published: (2024)

Label Inference Attacks against Node-level Vertical Federated GNNs
by: Arazzi, Marco, et al.
Published: (2023)

Deep Latent Force Models: ODE-based Process Convolutions for Bayesian Deep Learning
by: Baldwin-McDonald, Thomas, et al.
Published: (2023)

FedRand: Enhancing Privacy in Federated Learning with Randomized LoRA Subparameter Updates
by: Park, Sangwoo, et al.
Published: (2025)

Bayesian Active Learning for Discrete Latent Variable Models
by: Jha, Aditi, et al.
Published: (2022)

Personalized Auto-Grading and Feedback System for Constructive Geometry Tasks Using Large Language Models on an Online Math Platform
by: Lee, Yong Oh, et al.
Published: (2025)

Enhanced Federated Deep Multi-View Clustering under Uncertainty Scenario
by: Wei, Bingjun, et al.
Published: (2025)

Model Stitching by Functional Latent Alignment
by: Athanasiadis, Ioannis, et al.
Published: (2025)

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