Latest Research in Machine Learning

Top Research Topics in Machine Learning

• Machine Learning — 57 papers
• Privacy-Preserving Technologies in Data — 23 papers
• Cryptography and Security — 18 papers
• Distributed, Parallel, and Cluster Computing — 10 papers
• Software Engineering — 7 papers
• Software System Performance and Reliability — 7 papers
• Security and Verification in Computing — 4 papers
• Machine Learning — 4 papers
• Signal Processing — 3 papers
• Methodology — 3 papers

Highest-Cited Papers

1. Training Machine Learning Models at the Edge: A Survey (8 citations)
2. The Verification Model: Bounding What a Council Cannot See
3. Analysis of Intelligent Privacy Protection Mechanisms for Smart Healthcare in the Context of the Internet of Things
4. FedFIbOS: Fisher Importance based Optimal Submodelling for Heterogeneous Federated Learning
5. Batch Normalization Amplifies Memorization and Privacy Risks
6. Efficiently Distributed Federated Learning
7. Accelerating Sharded Data Parallelism at Scale with Federated Learning
8. Adaptive Strategies for GR(1) Games
9. Distributionally Robust Federated Learning with Multi-Source Data
10. QuanText: Protecting Dataset-Level Secrets in Textual Data Sharing
11. CaMeLoT: CaMeL orchestrated with Temporal logic for static verification and liveness
12. Federated Soft Clustering via Generalized Total Variation Minimization
13. TasmScan: Continuation-Aware Taint Analysis for TVM Bytecode with Savelist Abstraction
14. Frankenstein’s RAM: A Simulation Framework for Evaluating Memory Forensic Acquisition Strategies
15. FedLucra : Federated Learning With Loss‐Utility Controlled Robust Aggregation
16. Single-Live-Environment (SLE): A Stigmergic, Zero-Rollback Architectural Paradigm for Production-Only Continuous Systems
17. Single-Live-Environment (SLE): A Stigmergic, Zero-Rollback Architectural Paradigm for Production-Only Continuous Systems
18. Personalized Federated Learning through Global Knowledge Distillation and Local Head Adaptation
19. FedLTLib: A Comprehensive Benchmark for Federated Long-Tail Learning
20. Noise-Aware and Dynamically Adaptive Federated Defense Framework for SAR Image Target Recognition