1 citations · 1 across the 5 of their papers we have counts for
5 papers
UnIT: Scalable Unstructured Inference-Time Pruning for MAC-efficient Neural Inference on MCUs
Ashe Neth, Sawinder kaur, Mohammad Nur Hossain Khan +3
Existing pruning methods are typically applied during training or compile time and often rely on structured sparsity. While compatible with low-power microcontrollers (MCUs), struc…
Human Heterogeneity Invariant Stress Sensing
Yi Xiao, Harshit Sharma, Sawinder Kaur +2
Stress affects physical and mental health, and wearable devices have been widely used to detect daily stress through physiological signals. However, these signals vary due to facto…
CRoP: Context-wise Robust Static Human-Sensing Personalization
Sawinder Kaur, Avery Gump, Yi Xiao +5
The advancement in deep learning and internet-of-things have led to diverse human sensing applications. However, distinct patterns in human sensing, influenced by various factors o…
VeriCompress: A Tool to Streamline the Synthesis of Verified Robust Compressed Neural Networks from Scratch
Sawinder Kaur, Yi Xiao, Asif Salekin
AI's widespread integration has led to neural networks (NNs) deployment on edge and similar limited-resource platforms for safety-critical scenarios. Yet, NN's fragility raises con…
Deadwooding: Robust Global Pruning for Deep Neural Networks
Sawinder Kaur, Ferdinando Fioretto, Asif Salekin
The ability of Deep Neural Networks to approximate highly complex functions is key to their success. This benefit, however, comes at the expense of a large model size, which challe…