Support vector machine (SVM) is an optimal margin based classification technique in
machine learning. SVM is a binary linear classifier which has been extended to non-linear …

Markov chain Monte Carlo methods are often deemed too computationally intensive to be of
any practical use for big data applications, and in particular for inference on datasets …

The capacity of a neural network to absorb information is limited by its number of
parameters. Conditional computation, where parts of the network are active on a per …

An introduction to a broad range of topics in deep learning, covering mathematical and
conceptual background, deep learning techniques used in industry, and research …

Previous research on empathetic dialogue systems has mostly focused on generating
responses given certain emotions. However, being empathetic not only requires the ability of …

Inventors have long dreamed of creating machines that think. Ancient Greek myths tell of
intelligent objects, such as animated statues of human beings and tables that arrive full of …

Due to the simplicity of their implementations, least square support vector machine (LS-
SVM) and proximal support vector machine (PSVM) have been widely used in binary …

We consider the problem of learning causal directed acyclic graphs from an observational
joint distribution. One can use these graphs to predict the outcome of interventional …

Abstract The Mixture-of-Experts (MoE) layer, a sparsely-activated model controlled by a
router, has achieved great success in deep learning. However, the understanding of such …

摘要单隐藏层前馈神经网络(Single hiddenLayerFeedforwardNeuralNetwork, SLFN)
已经在模式识别, 自动控制及数据挖掘等领域取得了广泛的应用, 但传统学习方法的速度远远 …