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Federated learning : privacy and incentive / / edited by Qiang Yang, Lixin Fan, and Han Yu
| Federated learning : privacy and incentive / / edited by Qiang Yang, Lixin Fan, and Han Yu |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2020] |
| Descrizione fisica | 1 online resource (X, 286 p. 94 illus., 82 illus. in color.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Federated database systems
Application software Machine learning |
| ISBN | 3-030-63076-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Privacy -- Threats to Federated Learning -- Rethinking Gradients Safety in Federated Learning -- Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks -- Task-Agnostic Privacy-Preserving Representation Learning via Federated Learning -- Large-Scale Kernel Method for Vertical Federated Learning -- Towards Byzantine-resilient Federated Learning via Group-wise Robust Aggregation -- Federated Soft Gradient Boosting Machine for Streaming Data -- Dealing with Label Quality Disparity In Federated Learning -- Incentive -- FedCoin: A Peer-to-Peer Payment System for Federated Learning -- Efficient and Fair Data Valuation for Horizontal Federated Learning -- A Principled Approach to Data Valuation for Federated Learning -- A Gamified Research Tool for Incentive Mechanism Design in Federated Learning -- Budget-bounded Incentives for Federated Learning -- Collaborative Fairness in Federated Learning -- A Game-Theoretic Framework for Incentive Mechanism Design in Federated Learning -- Applications -- Federated Recommendation Systems -- Federated Learning for Open Banking -- Building ICU In-hospital Mortality Prediction Model with Federated Learning -- Privacy-preserving Stacking with Application to Cross-organizational Diabetes Prediction. . |
| Record Nr. | UNINA-9910427668503321 |
| Cham, Switzerland : , : Springer, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Federated learning : privacy and incentive / / edited by Qiang Yang, Lixin Fan, and Han Yu
| Federated learning : privacy and incentive / / edited by Qiang Yang, Lixin Fan, and Han Yu |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2020] |
| Descrizione fisica | 1 online resource (X, 286 p. 94 illus., 82 illus. in color.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Federated database systems
Application software Machine learning |
| ISBN | 3-030-63076-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Privacy -- Threats to Federated Learning -- Rethinking Gradients Safety in Federated Learning -- Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks -- Task-Agnostic Privacy-Preserving Representation Learning via Federated Learning -- Large-Scale Kernel Method for Vertical Federated Learning -- Towards Byzantine-resilient Federated Learning via Group-wise Robust Aggregation -- Federated Soft Gradient Boosting Machine for Streaming Data -- Dealing with Label Quality Disparity In Federated Learning -- Incentive -- FedCoin: A Peer-to-Peer Payment System for Federated Learning -- Efficient and Fair Data Valuation for Horizontal Federated Learning -- A Principled Approach to Data Valuation for Federated Learning -- A Gamified Research Tool for Incentive Mechanism Design in Federated Learning -- Budget-bounded Incentives for Federated Learning -- Collaborative Fairness in Federated Learning -- A Game-Theoretic Framework for Incentive Mechanism Design in Federated Learning -- Applications -- Federated Recommendation Systems -- Federated Learning for Open Banking -- Building ICU In-hospital Mortality Prediction Model with Federated Learning -- Privacy-preserving Stacking with Application to Cross-organizational Diabetes Prediction. . |
| Record Nr. | UNISA-996418217803316 |
| Cham, Switzerland : , : Springer, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Heterogeneous data management, polystores, and analytics for healthcare : vldb workshops, poly 2020 and dmah 2020, virtual event, august 31 and september 4, 2020, revised selected papers / / edited by Vijay Gadepally, 6 others
| Heterogeneous data management, polystores, and analytics for healthcare : vldb workshops, poly 2020 and dmah 2020, virtual event, august 31 and september 4, 2020, revised selected papers / / edited by Vijay Gadepally, 6 others |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XIII, 233 p. 84 illus., 71 illus. in color.) |
| Disciplina | 005.74 |
| Collana | Security and Cryptology |
| Soggetto topico |
Medical informatics
Database management Federated database systems |
| ISBN | 3-030-71055-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Poly 2020: Privacy, Security and/or Policy Issues for Heterogenous Data -- A Polystore Based Database Operating System (DBOS) -- Polypheny-DB: Towards Bridging the Gap Between Polystores and HTAP Systems -- Persona Model Transfer for User Activity Prediction across Heterogeneous Domains -- PolyMigrate: Dynamic Schema Evolution and Data Migration in a Distributed Polystore -- An Architecture for the Development of Distributed Analytics based on Polystore Events -- Towards Data Discovery by Example -- The Transformers for Polystores - the next frontier for Polystore research -- DMAH 2020: COVID-19 Data Analytics and Visualization -- Open-world COVID-19 Data Visualization -- DMAH 2020: Deep Learning based Biomedical Data Analytics -- Privacy-Preserving Knowledge Transfer with Bootstrap Aggregation of Teacher Ensembles -- An Intelligent and Efficient Rehabilitation Status Evaluation Method: A Case Study on Stroke Patients -- Multiple Interpretations Improve Deep Learning Transparency for Prostate Lesion Detection -- DMAH 2020: NLP based Learning from Unstructured Data -- Tracing State-Level Obesity Prevalence from Sentence Embeddings of Tweets: A Feasibility Study -- Enhancing Medical Word Sense Inventories Using Word Sense Induction: A Preliminary Study -- DMAH 2020: Biomedical Data Modelling and Prediction -- Teaching analytics medical-data common sense -- CDRGen: A Clinical Data Registry Generator -- Prediction of lncRNA-disease associations from tripartite graphs -- DMAH 2020: Invited Paper -- Parameter Sensitivity Analysis for the Progressive Sampling-Based Bayesian Optimization Method for Automated Machine Learning Model Selection. . |
| Record Nr. | UNINA-9910484843803321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Heterogeneous data management, polystores, and analytics for healthcare : vldb workshops, poly 2020 and dmah 2020, virtual event, august 31 and september 4, 2020, revised selected papers / / edited by Vijay Gadepally, 6 others
| Heterogeneous data management, polystores, and analytics for healthcare : vldb workshops, poly 2020 and dmah 2020, virtual event, august 31 and september 4, 2020, revised selected papers / / edited by Vijay Gadepally, 6 others |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XIII, 233 p. 84 illus., 71 illus. in color.) |
| Disciplina | 005.74 |
| Collana | Security and Cryptology |
| Soggetto topico |
Medical informatics
Database management Federated database systems |
| ISBN | 3-030-71055-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Poly 2020: Privacy, Security and/or Policy Issues for Heterogenous Data -- A Polystore Based Database Operating System (DBOS) -- Polypheny-DB: Towards Bridging the Gap Between Polystores and HTAP Systems -- Persona Model Transfer for User Activity Prediction across Heterogeneous Domains -- PolyMigrate: Dynamic Schema Evolution and Data Migration in a Distributed Polystore -- An Architecture for the Development of Distributed Analytics based on Polystore Events -- Towards Data Discovery by Example -- The Transformers for Polystores - the next frontier for Polystore research -- DMAH 2020: COVID-19 Data Analytics and Visualization -- Open-world COVID-19 Data Visualization -- DMAH 2020: Deep Learning based Biomedical Data Analytics -- Privacy-Preserving Knowledge Transfer with Bootstrap Aggregation of Teacher Ensembles -- An Intelligent and Efficient Rehabilitation Status Evaluation Method: A Case Study on Stroke Patients -- Multiple Interpretations Improve Deep Learning Transparency for Prostate Lesion Detection -- DMAH 2020: NLP based Learning from Unstructured Data -- Tracing State-Level Obesity Prevalence from Sentence Embeddings of Tweets: A Feasibility Study -- Enhancing Medical Word Sense Inventories Using Word Sense Induction: A Preliminary Study -- DMAH 2020: Biomedical Data Modelling and Prediction -- Teaching analytics medical-data common sense -- CDRGen: A Clinical Data Registry Generator -- Prediction of lncRNA-disease associations from tripartite graphs -- DMAH 2020: Invited Paper -- Parameter Sensitivity Analysis for the Progressive Sampling-Based Bayesian Optimization Method for Automated Machine Learning Model Selection. . |
| Record Nr. | UNISA-996464437003316 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
