MS Thesis Presentation
Efficient Multi-GPU K-means Clustering
DISSERTATION DEFENSE
DEEP NEURAL NETWORK REPRESENTATIONS OF PHYSIOLOGICAL TIME-SERIES SENSOR DATA FOR IMPROVED RECOGNITION PERFORMANCE
DISSERTATION DEFENSE
Mitigating the Effects of Label Noise in Time-Series Sensor Data Using Deep Feature Extraction
THESIS DEFENSE PRESENTION
Fall Detection Using Federated Learning for Model Personalization and Anomaly Detection
DISSERTATION DEFENSE
Reducing Training Cost and Improving Inference Speed Through Neural Network Compression
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