Latest Research in Machine Learning

Top Research Topics in Machine Learning

• Distributed, Parallel, and Cluster Computing — 12 papers
• Hardware Architecture — 6 papers
• Machine Learning — 4 papers
• Networking and Internet Architecture — 3 papers
• Stochastic Gradient Optimization Techniques — 2 papers
• Cryptography and Security — 2 papers
• Cloud Computing and Resource Management — 2 papers
• Advanced Data Storage Technologies — 2 papers
• Adversarial Robustness in Machine Learning — 1 papers
• Performance — 1 papers

Highest-Cited Papers

1. The Price of the Bottleneck: A Pre-Registered, Multi-Domain Deployment Characterization of a Deterministic Edge Decision Token
2. Accelerating Stateful Network Applications with Performance Prediction on SoC SmartNICs
3. COMPASS-ABS: Reducing Fragmentation in Shared GPU Clusters for Deep Learning Training Workloads
4. XMPIaaS: Towards Cloud Native MPI via Cooperative Process Migration
5. X-Stage: Modeling Post-Issue Backpressure in GPU Communication--Computation Fusion
6. Accelerating Transfer-Learning-Based Autotuning with Predictive LLVM IR Performance Ranking
7. Ready Cohorts: Bounding GPU Opportunity and Avoiding Host Round Trips in LLM-Agent Control
8. ProfEdge: Efficient Construction of DNN Performance Evaluation Model on Edge Devices
9. Argus: Orchestrating Cross-Layer GPU Performance Measurements around Semantic Regions
10. Quantifying the Value of Privileged Information Using a PAC-Bayesian Approach
11. An Automated Evolutionary Modularization Approach for Performance-Aware Parallelization of Sequential Source Code
12. HBFSim: Fast and Faithful Simulation of High-Bandwidth Flash Under Real GPU Execution
13. Measuring Sustainability in Multi-Scale High-Performance Computing
14. Descriptive Dispatch of Computational Work
15. TASTE: Throughput-Aware Batch Size Tuning for On-Device Edge Learning
16. ForgeStencil: Automating Per-Case Stencil Specialization from Kernels to 100+ Real Applications
17. WaferTrans: Enabling IOMMU-free Distributed Virtual Address Translation for Wafer-scale GPUs
18. The Unseen Delta: Characterizing the Compiler Optimization Landscape via Top-Down Differential Analysis
19. KernelFoundry: Hardware-aware evolutionary GPU kernel optimization
20. Initialization and Rate-Quality Functions for Generative Network Layer Protocols