Session

DescriptionThe session features recent advancements in applying approximate computing techniques to different computing paradigms pertaining to Artificial Intelligence and Machine Learning, including hyperdimensional systems, spiking neural networks, probabilistic programming, and compressed video analytics. The techniques proposed include new encoding schemes, fixed-point quantization approaches, training methodologies, and compiler frameworks. The techniques have demonstrated significant improvement in both energy consumption and performance across various end-applications.