4 papers
Tempora: Characterising the Time-Contingent Utility of Online Test-Time Adaptation
Sudarshan Sreeram, Young D. Kwon, Cecilia Mascolo
Test-time adaptation (TTA) offers a compelling remedy for machine learning (ML) models that degrade under domain shifts, improving generalisation on-the-fly with only unlabelled sa…
Data-Free Group-Wise Fully Quantized Winograd Convolution via Learnable Scales
Shuokai Pan, Gerti Tuzi, Sudarshan Sreeram +1
Despite the revolutionary breakthroughs of large-scale text-to-image diffusion models for complex vision and downstream tasks, their extremely high computational and storage costs…
HASS: Hardware-Aware Sparsity Search for Dataflow DNN Accelerator
Zhewen Yu, Sudarshan Sreeram, Krish Agrawal +6
Deep Neural Networks (DNNs) excel in learning hierarchical representations from raw data, such as images, audio, and text. To compute these DNN models with high performance and ene…
Sculpting Efficiency: Pruning Medical Imaging Models for On-Device Inference
Sudarshan Sreeram, Bernhard Kainz
Leveraging ML advancements to augment healthcare systems can improve patient outcomes. Yet, uninformed engineering decisions in early-stage research inadvertently hinder the feasib…