We use the term neural networks (NNs) to denote a class of models which are referenced in the literature under various names, including: artificial neural systems, connectionist models and parallel distributed processing models. The name neural networks was selected from the variety of currently ...
Recurrent Neural Networks are one of the most common Neural Networks used in Natural Language Processing because of its promising results. The applications of RNN in language models consist of two main approaches. We can either make the model predict or
The network consists of simple processing elements that are interconnected via weights. The network is first trained using an appropriate learning algorithm for the estimation of interconnection weights. Once the network is trained, unknown test signals can be classified. The class of neural networks ...
Neural Network Research refers to the pursuit of accurate mathematical characterizations of the electrophysiological properties of individual neurons and interconnected networks, leading to the development of models for pattern recognition and other applications in engineering and medicine. ...
【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
Continual learning of context-dependent processing in neural networks 摘要: 深度神经网络能够学习出输入输出之间的复杂的映射规则,但是这个规则是固定的,不能够学习出多种场景下的不同的映射规则并根据场景的采用这些规则。正交权重修正以及场景以来的处理模块能够有效的解决深度神经网络的这个限制使得深度神经网络能够适用...
In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning. This historical survey compactly summarises relevant work, much of it from the previous millennium. Shallow and deep learners are distinguished by the depth...
Fig. 6. Illustration of how Algorithm Distillation (AD) works. 图6. 算法蒸馏(AD)的工作原理示意图。 (Image source:Laskin et al. 2023). (图片来源:Laskin等人,2023年)。 The paper hypothesizes that any algorithm that generates a set of learning histories can be distilled into aneural networkby...
Spiking Neural Networks and online learning: An overview and perspectives Neural Networks, (2020): 88-100 Abstract 以快速流的形式生成大量数据的应用正变得越来越普遍,因此有必要以在线方式学习。这些条件通常会施加内存和处理时间限制,并且它们通常会变成不断变化的环境,其中的变化可能会影响输入数据的分布...
First of all, to capture the complex internal formats of instructions, we use a fine-grained strategy to decompose instructions: we consider each instruction as a sentence and decompose it into basic tokens. Then, in order to train the deep neural network to understand the internal structures of...