333 citations · 396 across the 4 of their papers we have counts for
4 papers
Multi-step LRU: SIMD-based Cache Replacement for Lower Overhead and Higher Precision
Hiroshi Inoue
A key-value cache is a key component of many services to provide low-latency and high-throughput data accesses to a huge amount of data. To improve the end-to-end performance of su…
Multi-Sample Dropout for Accelerated Training and Better Generalization
Hiroshi Inoue
Dropout is a simple but efficient regularization technique for achieving better generalization of deep neural networks (DNNs); hence it is widely used in tasks based on DNNs. Durin…
Data Augmentation by Pairing Samples for Images Classification
Hiroshi Inoue
Data augmentation is a widely used technique in many machine learning tasks, such as image classification, to virtually enlarge the training dataset size and avoid overfitting. Tra…
Adaptive Ensemble Prediction for Deep Neural Networks based on Confidence Level
Hiroshi Inoue
Ensembling multiple predictions is a widely used technique for improving the accuracy of various machine learning tasks. One obvious drawback of ensembling is its higher execution…