Latest Research in Hardware Architecture

Top Research Topics in Hardware Architecture

• Machine Learning — 33 papers
• Hardware Architecture — 3 papers
• Advanced Neural Network Applications — 3 papers
• Imbalanced Data Classification Techniques — 2 papers
• Numerical Methods and Algorithms — 2 papers
• Text and Document Classification Technologies — 2 papers
• Sentiment Analysis and Opinion Mining — 2 papers
• Explainable Artificial Intelligence (XAI) — 2 papers
• Machine Learning and Data Classification — 2 papers
• Machine Learning — 1 papers

Highest-Cited Papers

1. RoboGPU: Accelerating GPU Collision Detection for Robotics
2. Learning Kernels by Alignment for Multiclass Bayes Classification
3. Limits of Transfer Learning
4. How Many Labels Does Model Choice Need? Certificates and Budgets for Selective Prediction
5. Radio-Frequency Convolutional Neural Networks
6. Deep Learning Models for IoT: MobileNetV2 Compression Using Structured Pruning and Post-Training Quantization
7. Deep Learning Models for IoT: MobileNetV2 Compression Using Structured Pruning and Post-Training Quantization
8. When majority rules, minority loses: bias amplification of gradient descent
9. Perturbation Sensitivity of Maximum-Likelihood Pairwise Ranking in Computational Decision Systems
10. ScaleLUT: A Fully-Parallel Configurable LUT-Based Accelerator for Real-Time Multi-Scale Super-Resolution
11. Breaking the Compression Barrier: Cross-Architecture Compression Boundary Learning via Reverse Regrowth
12. TabPFN-3.5: Technical Report
13. A Gradient-Level Diagnosis of Extreme Class Imbalance in Multiple Instance Learning via q-Calculus
14. Bounded Adjustment with Reliability-Guided Embedding for Imbalanced Learning with Noisy Labels
15. Beyond Noise: Understanding and Overcoming Temperature Effects in Analog DNN Inference
16. Observational Multiplicity
17. Partition Scores Are Not System Scores: Deployment-Fidelity Gaps in Decomposed Algorithm Selection
18. Damping Is a Ridge Penalty: Calibration-Only Selection for Post-Training Quantization under Scarce Calibration
19. Hardware-Aware Learned Representation Compression for Distributed In-Sensor Vision
20. Odds-Shift Slippage in One-vs-Rest Rankers: Diagnosing and Repairing Reweighting-Induced Top-K Errors