Zobrazeno 1 - 10
of 39
pro vyhledávání: ''
Publikováno v:
IJCNN
Least square support vector machines (LSSVMs) are an alternative to SVMs because the training process for LSSVMs is based on solving a linear equation system while the training process for SVMs relies on solving a quadratic programming optimization p
Publikováno v:
IJCNN
Multiple-kernel k-means (MKKM) clustering has demonstrated good clustering performance by combining pre-specified kernels. In this paper, we argue that deep relationships within data and the complementary information among them can improve the perfor
Publikováno v:
IJCNN
D-Wave 2X with more than 1000 qubits was applied to the relatively rugged energy landscape of trained Restricted Boltzmann Machines (RBMs). The D-Wave machine has a Chimera interconnect architecture. A native RBM restricted to the Chimera graph was f
Publikováno v:
IJCNN
For big, high-dimensional dense features, it is important to learn compact binary codes or compress them for greater memory efficiency. This paper proposes a Binarized Multilinear PCA (BMP) method for this problem with Free-Form Reshaping (FFR) of su
Publikováno v:
IJCNN
Spiking neuron models, which can realize diverse kinds of neural coding by describing spiking activity of membrane potential, have been widely utilized. Among these models, several hybrid spiking neuron models, which combine continuous spike-generati
Autor:
Shayan Garani Srinivasa, Prayag Gowgi
Publikováno v:
IJCNN
We look at the neural network as a non-linear probability density function (pdf) transformer by stochastic learning cumulative (SLC) technique. We formulate a potential function that drives a neural network to non-linearly transform the input pdf to
Publikováno v:
IJCNN
In this paper, we introduce a data-dependent kernel called deep quasi-linear kernel, which can directly gain a profit from a pre-trained feedforward deep network. Firstly, a multi-layer gated bilinear classifier is formulated to mimic the functionali
Publikováno v:
IJCNN
The importance of the q-Gaussian distributions is attributed to their power law nature and the fact that they generalize the Gaussian distributions (q → 1 retrieves the Gaussian distributions). While for q > 1, a q-Gaussian distribution is nothing
Publikováno v:
IJCNN
In order to reduce the computational complexity of kernel machines and improve their performance in multi-label classification, we develop a systematic two step batch approach for constructing and training a new multiclass kernel machine (MKM). The p
Publikováno v:
IJCNN
In this paper we introduce a new learning approach, which provides automated topological co-clustering based on Self-Organizing Map. The proposed approach (wd-TCoC) is computationally simple, learns a different feature's weights vector for each proto