DBLP is a training-phase-aware bounded-loss transport protocol that reduces end-to-end distributed ML training time by 24.4% on average (up to 33.9%) and achieves up to 5.88x communication speedup during microbursts while maintaining comparable test accuracy.
A network-centric hardware/algorithm co-design to accelerate distributed training of deep neural networks
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A qualitative study maps emotions exploited by financial scammers and help-seeking needs at different scam stages, identifying risk factors and suggesting design implications for interventions.
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DBLP: Phase-Aware Bounded-Loss Transport for Burst-Resilient Distributed ML Training
DBLP is a training-phase-aware bounded-loss transport protocol that reduces end-to-end distributed ML training time by 24.4% on average (up to 33.9%) and achieves up to 5.88x communication speedup during microbursts while maintaining comparable test accuracy.
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"It didn't feel right but I needed a job so desperately": Understanding People's Emotions & Help Needs During Financial Scams
A qualitative study maps emotions exploited by financial scammers and help-seeking needs at different scam stages, identifying risk factors and suggesting design implications for interventions.