Deep learning is an evolutionary advancement in the field of machine learning. The technique has been adopted in several areas where the computer after processing volumes of data are expected to make intelligent decisions. An important field of application for deep learning is the area of biometrics...
of a broad data science focused book. This chapter provided a brief high-level overview of the collection of techniques known asdeep learning. An overview on how the majority of today’s AI applications are supported solely bydeep learningwas provided. The fundamental similarity between deep ...
This post gives an overview of various deep learning based clustering techniques. I will be explaining the latest advances in unsupervised clustering which achieve the state-of-the-art performance by leveraging deep learning. Unsupervised learning is an active field of research and has alway...
Policy π(a_t | s_t ) : : Can be approximated by Deep NN. State transition probability P( s_{t+1} | s_t, a_t ) : Can be approximated by Deep NN. Discount factor γ Action value Q^pi( s, a ) for certain policy Pi. : Can be approximated by Deep NN. State value V^pi(...
✍️ [阅读笔记] An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies ??? 艺、Introduction ??? 尔、威胁模型??? Threat Model A. ??? 攻击面(Attack surface) B. ??? 客户端或者服务端的攻击(Client or server-side attacks) C. ??
Deep learningis a powerful representation technique that is state of the art in many ML problems. Adeep learningmodel is aneural networkwith many layers, which is able to learn from large amounts of data to do specific tasks. For a comprehensive review of deep learning techniques in medical ...
Artificial neural networks are not new; they have been around for about 50 years and got some practical recognition after the mid-1980s with the introduction of a method (backpropagation) that allowed for the training of multiple-layer neural networks. However, the true birth of deep learning ...
Deep learning techniques have received much attention in the area of image denoising. However, there are substantial differences in the various types of deep learning methods dealing with image denoising. Specifically, discriminative learning based on deep learning can ably address the issue of Gaussian...
本次介绍的文章全称 Speaker Recognition Based on Deep Learning: An Overview,2021年发表在Neural Networks。 全文的主要架构如下: Introduction and brief overview Speaker feature extraction The loss functions of the end-to-end speaker verification. Speaker diarization. Robust speaker recognition. Benchmark cor...
【多任务学习】An Overview of Multi-Task Learning in Deep Neural Networks,译自:http://sebastianruder.com/multi-task/1.前言在机器学习中,我们通常关心优化某一特定指标,不管这个指标是一个标准值,还是企业KPI。为了达到这个目标,我们训练单一模型或多个模型集合