Based on the importance and potentiality of “Machine Learning” to analyze the data mentioned above, in this paper, we provide a comprehensive view on various types ofmachine learning algorithmsthat can be applied to enhance the intelligence and the capabilities of an application. Thus, the key ...
–In this paper, various machine learning algorithms have been discussed. These algorithms are used for various purposes like data mining, image processing, predictive analytics, etc. to name a few. The main advantage of using machine learning is that, once an algorithm learns what to do with ...
Penn Machine Learning Benchmarks (PMLB) is a large collection of curated benchmark datasets for evaluating and comparing supervised machine learning algorithms.
量子算法在各种机器学习问题上的speedup. J. Biamonte, Nature2017. 二. Quantum ML algorithms HHL算法: PhysRevLett.103.150502 这篇是量子机器学习领域目前为止最为重要的paper之一,它解决的问题是已知矩阵A向量b而且Ax=b,求向量x的问题(当然还有一些其他的constraints),亦即线性代数里最基础的矩阵运算问题。其核心...
Machine learning algorithms based on parametrized quantum circuits are prime candidates for near-term applications on noisy quantum computers. In this direction, various types of quantum machine learning models have been introduced and studied extensivel
Paper Fairness-aware machine learning: a perspective Algorithms learned from data are increasingly used for deciding many aspects in our life: from movies we see, to prices we pay, or medicine we get. Yet there is growing evidence that decision making by inappropriately trained algorithms may ...
Blockchain-enabled digital twin system for brain stroke prediction A digital twin is a virtual model of a real-world system that updates in real-time. In healthcare, digital twins are gaining popularity for monitoring activities like diet, physical activity, and sleep. Howeve... ...
Learning algorithms Network models Olfactory system This article is cited by A simple model for Behavioral Time Scale Synaptic Plasticity (BTSP) provides content addressable memory with binary synapses and one-shot learning Yujie Wu Wolfgang Maass ...
监督学习算法 (Supervised Algorithms):在监督学习训练过程中,可以由训练数据集学到或建立一个模式(函数 / learning model),并依此模式推测新的实例。该算法要求特定的输入/输出,首先需要决定使用哪种数据作为范例。例如,文字识别应用中一个手写的字符,或一行手写文字。主要算法包括神经网络、支持向量机、最近邻居法、朴...
Again, our Data Science Group implemented a deep reinforcement learning algorithm described in Playing Atari with Deep Reinforcement Learning paper by DeepMind.[embed]https://www.youtube.com/watch?v=T58HkwX-OuI[/embed]Fig.5. – Deep Reinforcement Learning - video...