One supervised learning approach is also proposed to optimize ranking function by employing 264 features, including part-of-speech, and bigram co-occurrence etc. Experiments show that 7.06% further improvement can be achieved.doi:10.1007/978-3-540-71701-0_55Guoping Hu...
Therefore can reduce MC VFA to doing supervised learning on a set of (state, return) pairs:\langle s_1,G_1\rangle,\langle s_2,G_2\rangle,\ldots,\langle s_T,G_T\rangle SubstituteG_tfor the trueV^\pi(s_t)when fit function approximator Concretely when using linear VFA for policy...
On Loss Functions for Supervised Monaural Time-Domain Speech Enhancement 8、Perceptual Loss——STOI STOI短时客观可懂度(Short-Time Objective Intelligibility),通过计算语音信号的时域和频域特征之间的相关性来预测语音的可理解度,范围从0到1,分数越高可懂度越高。它适用于评估噪声环境下的语音可懂度改善效果...
In our dataset, of the 30.8 M protein sequences, 19.8% could not be associated with any known annotation (see Methods), and 27.5% could not be associated with any known Pfam domains using a recent deep learning approach (ProtENN38). Understanding the functional role of these proteins ...
Surrogate gradient learning is robust to the shape of the surrogate derivative 替代梯度学习的一个必要成分是合适的替代导数。为了比较地研究替代导数的影响,我们生成了一个具有十个类的随机流形数据集。我们选择了剩余的参数,即输入单元的数量、流形维数和平滑度,以使没有隐藏层的网络无法解决问题,同时保持最小的...
hybrid learningmulti-objective optimizationmulti-objective particle swarm optimizationThe problem of unsupervised and supervised learning of RBF networks is discussed with Multi-Objective Particle Swarm Optimization (MOPSO). This study presents an evolutionary multi-objective selection method of RBF networks ...
You can specify the kernel function using theKernelFunctionname-value pair argument in a call tofitrgp. You can either specify one of the built-in kernel parameter options, or specify a custom function. When providing the initial kernel parameter values for a built-in kernel function, input the...
This paper presents the ‘hyper-sinh’, a variation of the m-arcsinh activation function suit-able for Deep Learning (DL)-based algorithms for supervised learning, including Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), such as the Long Short-Term Memory (LSTM). hype...
Surrogate gradient learning is robust to changes in the loss functions, input paradigms, and datasets Surrogate gradient learning in networks with current-based input Optimal sparse spiking activity levels in SNNs Discussion Methods Supervised learning tasks ...
Learning Continuous Image Representation with Local Implicit Image Function(阅读笔记)11.03 局部隐式图像函数(LIIF)表示连续中的图像,可以以任意高分辨率表示。 摘要:如何表示图像?当视觉世界以连续的方式呈现时,机器用二维像素数组以离散的方式存储和观看图像。本文中,试图学习图像的连续表示。受隐式神经表示在三维重建...