In this paper, we propose DnnSAT, a resource-guided AutoML approach for deep learning models to help existing AutoML tools efficiently reduce the configuration space ahead of time. DnnSAT can speed up the search process and achieve equal or even better model learning performance becaus...
注意模块使网络聚焦于包含感兴趣对象的较小区域[Wu和Ogai,2020]利用自我注意机制提升有用特征并抑制无用特征[Xie et al.,2020]设计了两个注意力模块和一个用于三维目标检测的特征融合模块,能够在patch、目标和全局场景级别利用上下文信息。类似地,[Liu et al.,2020b]提出了一个三重注意模块,它综合考虑了通道、...
导读:Deep Dynamics Models for Learning Dexterous Manipulation发表在CoRL 2019,作者是大牛Sergey Levine团队。这篇文章主要工作是提出了学习灵巧手部动作的深度动态模型,用Model-based RL的方式解决以往算法中需要数据量太大和不能完成复杂动作的问题。作者还在仿真机器手上进行了实验,通过仅仅4个小时的真实数据训练出一...
本学期由人工智能学院主办的倒数第二场讲座是由清华大学的朱军老师带来的《Learning Deep Generative Models Reliably and Efficiently》讲座,朱老师主要从生成模型的简介、训练和优化深度生成模型的方法以及一些团队工作展开。 朱老师首先回顾了简单...
Keras code and weights files for popular deep learning models. - deep-learning-models/mobilenet.py at master · fchollet/deep-learning-models
Pre-trained and Reproduced Deep Learning Models (『飞桨』官方模型库,包含多种学术前沿和工业场景验证的深度学习模型) - SUFEHeisenberg/models
ExploreMATLAB Deep Learning Model Hubto access the latest models by category and get tips on choosing a model. Load most models at the command line. For example: net = darknet19; Open-source models Convert TensorFlow™, PyTorch®, and ONNX™ models to MATLAB networks by using animport...
Emphasis is placed on understanding how these methods impact computational resource usage, including CPU/GPU utilization and memory consumption. Our findings reveal that deep learning models show promise in handling complex image datasets, while local patterns, known for their resource efficiency, may ...
Precision at 1% for preventable ED visits was 39% for deep learning compared to 33% for enhanced LR. For preventable cost, cost capture at 1% was 30% for sequential deep learning, compared to 18% for enhanced LR. The highest AUROCs for deep learning were 0.778, 0.681 and 0.727, ...
other problem settings have been considered. For example, studies [66,67,68] consider multiple sensitive attributes:\(S=\{S_1,S_2,...\}\), where the sensitive features can have multiple attribute values, such as race. With multiple values, it would be resource-intensive for the fair met...