Aug 22, 2017 · Experimentally, the adaptive weights induce more competitive anytime predictions on multiple recognition data-sets and models than non-adaptive ...
This work proposes adaptive weights to balance the losses to the same scales online, and provides multiple the- oretical motivations. We empirically show ...
In particular, anytime neural networks (ANNs) can achieve the same accuracy faster using adaptive weights on a small network than using static constant weights ...
This work optimize auxiliary losses jointly in an adaptive weighted sum, where the weights are inversely proportional to average of each loss, ...
Specifically, we optimize auxiliary losses jointly in an adaptive weighted sum, where the weights are inversely proportional to average of each loss.
May 25, 2018 · This work proposes adaptive weights to balance the losses to the same scales online, and provides multiple theoretical motivations. We ...
Learning Anytime Predictions in Neural Networks via Adaptive Loss Balancing. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 3812 ...
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Learning Anytime Predictions in Neural Networks via Adaptive Loss Balancing. H Hu, D Dey, M Hebert, JA Bagnell. 117*, 2018. Efficient 3-d scene analysis from ...
Learning anytime predictions in neural networks via adaptive loss balancing. In Proceedings of the AAAI Conference on. Artificial Intelligence, volume 33 ...
We address the problem of anytime prediction in neural networks. An anytime predictor automatically adjusts to and utilizes available test-time budget: it ...