:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Cao, Hongliu
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2312.14628
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Holistic Safety and Responsibility Evaluations of Advanced AI Models
by: Weidinger, Laura, et al.
Published: (2024)

Writing Style Matters: An Examination of Bias and Fairness in Information Retrieval Systems
by: Cao, Hongliu
Published: (2024)

Semantic Adapter for Universal Text Embeddings: Diagnosing and Mitigating Negation Blindness to Enhance Universality
by: Cao, Hongliu
Published: (2025)

AnalogFed: Federated Discovery of Analog Circuit Topologies with Generative AI
by: Li, Qiufeng, et al.
Published: (2025)

A Comprehensive Perspective on Explainable AI across the Machine Learning Workflow
by: Paterakis, George, et al.
Published: (2025)

FL-GUARD: A Holistic Framework for Run-Time Detection and Recovery of Negative Federated Learning
by: Lin, Hong, et al.
Published: (2024)

Recent advances in text embedding: A Comprehensive Review of Top-Performing Methods on the MTEB Benchmark
by: Cao, Hongliu
Published: (2024)

Adaptive Guidance for Local Training in Heterogeneous Federated Learning
by: Zhang, Jianqing, et al.
Published: (2024)

FedCCA: Client-Centric Adaptation against Data Heterogeneity in Federated Learning on IoT Devices
by: Wang, Kaile, et al.
Published: (2026)

Beyond Myopia: Learning from Positive and Unlabeled Data through Holistic Predictive Trends
by: Wang, Xinrui, et al.
Published: (2023)

Deep Learning with CNNs: A Compact Holistic Tutorial with Focus on Supervised Regression (Preprint)
by: Tejeda, Yansel Gonzalez, et al.
Published: (2024)

Data-centric Federated Graph Learning with Large Language Models
by: Yan, Bo, et al.
Published: (2025)

Toward a Holistic Approach to Continual Model Merging
by: Phan, Hoang, et al.
Published: (2025)

Holistic Artificial Intelligence in Medicine; improved performance and explainability
by: Petridis, Periklis, et al.
Published: (2025)

Data Agent: A Holistic Architecture for Orchestrating Data+AI Ecosystems
by: Sun, Zhaoyan, et al.
Published: (2025)

Large-Small Model Collaborative Framework for Federated Continual Learning
by: Yu, Hao, et al.
Published: (2025)

FedKDX: Federated Learning with Negative Knowledge Distillation for Enhanced Healthcare AI Systems
by: Pham, Quang-Tu, et al.
Published: (2026)

Centralized vs Decentralized Federated Learning: A trade-off performance analysis
by: Medjadji, Chaimaa, et al.
Published: (2026)

Reinforcement Learning for Generative AI: A Survey
by: Cao, Yuanjiang, et al.
Published: (2023)

Holistic Utility Preference Learning for Listwise Alignment
by: Zhou, Jiacong, et al.
Published: (2024)

FedRD: Reducing Divergences for Generalized Federated Learning via Heterogeneity-aware Parameter Guidance
by: Wang, Kaile, et al.
Published: (2026)

Towards Efficient Mixture of Experts: A Holistic Study of Compression Techniques
by: He, Shwai, et al.
Published: (2024)

PiXTime: A Model for Federated Time Series Forecasting with Heterogeneous Data across Nodes
by: Zhou, Yiming, et al.
Published: (2026)

Federated Learning Playground
by: Shan, Bryan, et al.
Published: (2026)

Provable Sparse Inversion and Token Relabel Enhanced One-shot Federated Learning with ViTs
by: Shen, Li, et al.
Published: (2026)

A Federated Learning Framework for Handling Subtype Confounding and Heterogeneity in Large-Scale Neuroimaging Diagnosis
by: Zhao, Xinglin, et al.
Published: (2025)

Enhancing Federated Domain Adaptation with Multi-Domain Prototype-Based Federated Fine-Tuning
by: Zhang, Jingyuan, et al.
Published: (2024)

FM-G-CAM: A Holistic Approach for Explainable AI in Computer Vision
by: Silva, Ravidu Suien Rammuni, et al.
Published: (2023)

Enhancing Smart Farming Through Federated Learning: A Secure, Scalable, and Efficient Approach for AI-Driven Agriculture
by: Janga, Ritesh, et al.
Published: (2025)

Certifiably Byzantine-Robust Federated Conformal Prediction
by: Kang, Mintong, et al.
Published: (2024)

GTHNA: Local-global Graph Transformer with Memory Reconstruction for Holistic Node Anomaly Evaluation
by: Li, Mingkang, et al.
Published: (2025)

A robust methodology for long-term sustainability evaluation of Machine Learning models
by: Paz-Ruza, Jorge, et al.
Published: (2025)

Federated Learning for Privacy-Preserving Medical AI
by: Hoang, Tin
Published: (2026)

Exploring the sustainable scaling of AI dilemma: A projective study of corporations' AI environmental impacts
by: Desroches, Clément, et al.
Published: (2025)

Federated Learning with Neural Graphical Models
by: Chajewska, Urszula, et al.
Published: (2023)

Federated Generative Learning with Foundation Models
by: Zhang, Jie, et al.
Published: (2023)

One-Shot Clustering for Federated Learning
by: Zuziak, Maciej Krzysztof, et al.
Published: (2025)

Bayesian Federated Learning for Continual Training
by: Milasheuski, Usevalad, et al.
Published: (2025)

Gradient Inversion in Federated Reinforcement Learning
by: He, Shenghong
Published: (2025)

AFed: Algorithmic Fair Federated Learning
by: Chen, Huiqiang, et al.
Published: (2025)