2 papers
cs.LG2025
FiCABU: A Fisher-Based, Context-Adaptive Machine Unlearning Processor for Edge AI
Eun-Su Cho, Jongin Choi, Jeongmin Jin +2
Machine unlearning, driven by privacy regulations and the "right to be forgotten", is increasingly needed at the edge, yet server-centric or retraining-heavy methods are impractica…
eess.AS2025
ASAP-FE: Energy-Efficient Feature Extraction Enabling Multi-Channel Keyword Spotting on Edge Processors
Jongin Choi, Jina Park, Woojoo Lee +2
Multi-channel keyword spotting (KWS) has become crucial for voice-based applications in edge environments. However, its substantial computational and energy requirements pose signi…