由个人翻译,不保证准确。请见原文: Neural Tangent Kernel: Convergence and Generalization in Neural Networks 32nd Conference on Neural Information Processing Systems (NIPS 2018), Montréal, Canada. …
Summary: This paper presents a study of convergence modalities in a small adaptive network of conductance-based neurons, receiving input patterns with different degrees correlation . The models for the neurons, synapses and plasticity rules (STDP) have a common biophysics basis. The neural network ...
At initialization, artificial neural networks (ANNs) are equivalent to Gaussian processes in the infinite-width limit, thus connecting them to kernel methods. We prove that the evolution of an ANN during training can also be described by a kernel: during gradient descent on the parameters of an...
While significant theoretical and experimental progress has been made in the development of neural network-based systems for the autonomous identification and control of space platforms, there remain important unresolved issues associated with the reliable prediction of convergence speed and the avoidance of...
Convergence times and the corresponding dispersions have been studied numerically as parameters to measure the efficiency of neural network models. These quantities are also supposed to be related to the number of spurious states for each configuration of stored patterns. In this work we measure these...
In the paper, a recurrent neural network based on an augmented Lagrangian function is proposed for seeking local minima of nonconvex optimization problems with inequality constraints. First, each equilibrium point of the neural network corresponds to a Karush-Kuhn-Tucker (KKT) point of the problem....
Neural networks have become a prominent approach to solve inverse problems in recent years. While a plethora of such methods was developed to solve inverse problems empirically, we are still lacking clear theoretical guarantees for these methods. On the other hand, many works proved convergence to ...
Cells colours indicate the clusters they belonged to according to unsupervised clustering (a), or the adult clusters they were classified as by the neural network (b, same as in Fig. 1e). Black circles indicate high granularity regions, where less frequent cell types were grouped together by ...
of deep neural network.Based on new assumptions,we studied the convergence and convergence rate of SGD and its two common variant algorithms.In addition,we carried out numerical experiments with LeNet-5,a common network framework...
In one embodiment using Border Gateway Protocol (BGP) for inter-domain route and reachability communication, nodes that need to remove routes using EBGP NLRI a... K Patel,C Appanna,J Scudder - US 被引量: 5发表: 2007年 A Neural Network Approach to Planar-Object Recognition in 3D Space ...