DEEP learningRANDOM forest algorithmsMACHINE learningRAINFALLATMOSPHEREOur subject is a new catalogue of radar-based heavy rainfall events (CatRaRE) over Germany and how it relates to the concurrent atmospheric circulation. We classify daily ERA5 fields of convective indices accordi...
In the frame of the submitted research, the shallow learning approach is thoroughly compared to the deep learning techniques which are based on the use of a Restricted Boltzmann Machine (RBM) and an Auto-Encoder (AE). To do so, these learning techniques are applied on a feed-forward multi-...
在学术界也是,比如在各个应用领域里,Automatic Speech Recognition (ASR) 中不仅 deep learning 超越了传统的 state-of-the-art 算法,而且超越程度之大使得 ASR 领域本身迎来了一次新的 break through(Hinton et al., 2012);Collaborative Filtering 里,Deep Learning 在 Netflix 最后获奖算法中占据重要地位;Computer...
在学术界也是,比如在各个应用领域里,Automatic Speech Recognition (ASR) 中不仅 deep learning 超越了传统的 state-of-the-art 算法,而且超越程度之大使得 ASR 领域本身迎来了一次新的 break through(Hinton et al., 2012);Collaborative Filtering 里,Deep Learning 在 Netflix 最后获奖算法中占据重要地位;Computer...
Deep Learning and Shallow Learning 由于Deep Learning 现在如火如荼的势头,在各种领域逐渐占据 state-of-the-art 的地位,上个学期在一门课的 project 中见识过了 deep learning 的效果,最近在做一个东西的时候模型上遇到一点瓶颈于是终于决定也来了解一下这个魔幻的领域。
【 深度学习框架 】Good Patterns For Deep Learning With TensorFlow(英文字幕) 贝叶斯派对 139 0 【谷歌 I/O '18开发者大会 TF】TensorFlow and deep reinforcement learning, without a PhD(英文 贝叶斯派对 193 0 【谷歌 I/O '18开发者大会 ML】Intro to machine learning on Google Cloud Platform (英...
Learning Deep and Shallow Features for Human Activity RecognitionAn important application domain for Machine learning is sentiment classification. Here, the traditional approach is to represent documents using a Bag-Of-Words (BOW) model, where individual terms are used as features. However, the BOW ...
Bayesian inference for deep learning using labeled data information in probabilistic model and reconstruction-based model active learning in AD 2. 异常检测领域待需改进的问题: robustness:模型的鲁棒性包括考虑模型识别异常时的置信度;考虑对训练样本分布外的异常(out-of-distribution anomalies)进行识别;open set...
六、浅层学习(Shallow Learning)和深度学习(Deep Learning)七、Deep learning与Neural Network 八、Deep learning训练 … blog.csdn.net|基于20个网页 2. 深度学习是针对于浅层 深度学习是针对于浅层(shallow learning)学习而提出的一个概念。为了更好地理解他们之间的关系与特征,我们首先要了解一下 … ...
Deep Reinforecement Learning (DRL): 用深度神经网络来计算值函数或策略。 Shallow Reinforcement Learning (SRL): 用线性函数计算值函数或策略。 自1997年以来,研究人员在SRL类方法上发表了很多论文。SRL的优势是结果稳定(stable),需要的数据量比较少(data efficient)。但是,此类方法严重依赖特征的选择。选好特征,效...