~/talk

Machine Learning in the Age of IoT

Talkat CODES+ISSS 2022 · 2022-10-07..10-14· [machine-learning, iot]
name:Jun Xia
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name:Tian Liu
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name:Ting Wang
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name:Xin Fu
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name:Yue Tang
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name:Yawen Wu
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name:Yunji Qin
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name:Lei Gong
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name:Chao Wang
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slides:none on file

PervasiveFL proposes a lightweight cloud modulate that pairs with diverse local nets, uses an entropy-based decision gating and ensemble mutual learning, uploads modulate gradients from 10 emulated boards and shows ImageNet10 accuracy gains (~+3.17%) while reducing communication: modulate gradients 8.71 MB vs large model 162 MB and 1.65s vs 13.96s per round. Random-forest work implements three DT kernels on a RISC‑V MCU (struct loop, packed struct, DTE array), achieves 4–4.8× speedups, 4.5 µs latency, 220k inferences/s and large energy savings. Temporal action localization streams video on-device with a contrastive, self-adaptive merging and interest-based sampling to limit oracle labels and improve weakly supervised localization from long untrimmed streams.

AI-written summary · about

  1. 0:00Start
  2. 5:29Step 6: Modellet Synchronization
  3. 28:29Detecting actions in videos on edge devices
  4. 31:18Revisiting Video Learning
  5. 34:31Self-adaptive Video Dividing Approach
  6. 35:55Interests-based Sampling Strategy
  7. 36:39Experimental Setup
  8. 37:47Different Merging and Sampling Strategies
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