搜索过程中的评估方式采用了execution这样实测的方式,被作为性能基线;接下来是论文中提到的两种搜索方式beam search + cost model (红色)和MCTS + cost model (黄色),其中评估采取了cost model的方式;最后作为对比的则是Halide里提出的auto scheduler(绿色)。
tSNE图 传统方法 体现每一层的学习成果。 对于本文我觉得优点是可视化的研究了一些前人在fault diagnosis领域忽略的东西。 但是对网络结构没有本质上的创新,还是传统的一套,缺点就是第二层开始的特征都缺乏物理意义(所以作者只集中讨论了第一层), 同时CNN本身的学习很受噪音干扰(即使作者用大核优化来避免),从第一...
Online learning, though, asks for the combination of different delivery methodologies to contribute towards the optimization not only of the learning development, but also of deployment costs and time8. In this context, a key-factor that adds value to the quality of the learning experience is the...
We use Deeplabv3+ with MobileNetv2 backbone as the main model structure, additionly, some simple yet effective modifications are designed for improving the satellite image-based surface water mapping. -- DataSet Surface water dataset for Deep learning could be downloaded from Zenodo[Link]. ...
此外,现有模型中deep ZSL模型并不多,性能优于non-deep ZSL模型的更是少之又少。本文认为提升ZSL分类模型的关键在于选择正确的嵌入空间,同时提出一种可以融合多种语义模态的深度模型并通过端对端方式联合优化。 二、主要贡献: (1)提出一种新的ZSL模型,将visual space作为嵌入空间,可以减轻hubness问题; (2) 对hub...
A collection of various deep learning architectures, models, and tips - RangeKing/deeplearning-models
文章要点:这篇文章主要是deep的model based RL的综述,说起来主要的目标就是一句话achieve high predictive power while maintaining low sample complexity. 主要分了三大类using explicit planning on given transitions,using explicit planning on learned transitions, end-to-end learning of both planning and transiti...
Zero-Shot Learning via Class-Conditioned Deep Generative Models We present a deep generative model for learning to predict classes not seen at training time. Unlike most existing methods for this problem, that represent... W Wang,Y Pu,VK Verma,... 被引量: 25发表: 2017年 A Deep Graph ...
最近小伙伴们分析了《Cortex: a compiler for recursive deep learning models》这篇论文,给大家分享一下,此论文第一作者为卡耐基梅隆大学的Pratik Fegade,第二作者为OctoML的陈天奇。研究项目受到NSF及大量工业界的资助。笔者从作者和背后金主来头能感受到这份研究同时受到学术界和工业界的高度关注。文章中提出cortex,...