In subject area: Computer Science A Path Routing Algorithm is a method used in computer networks to determine the most efficient route for data packets to travel from a source to a destination. It includes algorithms like shortest path and widest path routing for IP and telephone networks, respe...
used a graph-theory based generation method of computation sequences to trace the calculation order of components and pipeline. Thus, their solver was different from the traditional one. A tailor-made refrigerant mass induced iteration algorithm was developed to solve the internal coupled component ...
The rest of the paper is organized as follows: In “Related works” section, we examine various routing methods presented in FANETs. In “Basic concepts” section, we define the concepts related to the firefly algorithm, which is used in the proposed method. In “Network model” section, we...
Vegas an AutoML algorithm tool chain by Huawei Noah's Arb Lab. ⬆ back to ToC Optimizations ProjectDetailsRepository FeatherCNN FeatherCNN is a high performance inference engine for convolutional neural networks. Forward A library for high performance deep learning inference on NVIDIA GPUs. NCNN ncn...
1.1. Optimized Link State Routing Protocol The IETF community is credited for the design of the Optimized Link State Routing (OLSR) protocol, and it is mentioned as an experimental protocol in the Request for Comments 3626. It applies the shortest path routing algorithm, which is an extended tr...
Essentially, a constrained Nelder-Mead algorithm36 is carried out that performs an iterative projection-pursuit of the mixtures to search the optimised weighting vectors. The goal is to find the mixture that outputs a weighted addition (\(\Sigma {w}_{i}{s}_{i},{w}_{i}\in \left[-{{{...
2024-07-29, the EasyEdit has added a new model editing algorithm EMMET, which generalizes ROME to the batch setting. This essentially allows making batched edits using the ROME loss function. 2024-07-23, we release a new paper: "Knowledge Mechanisms in Large Language Models: A Survey and ...
Figure 2 (middle) shows a typical run of the algorithm for \(T=50\) iterations. Local DP is not shown as it diverges unless the learning rate is overly small. On the other hand, Gopa is able to decrease the objective function steadily, although we see some difference with the trusted ...
Only decomposing the adjacency matrix can only take into account the influence of the direct neighbor on the current node, which is very limited. Random walk is used to generate the context of nodes which makes up for the deficiency of matrix factorization. Then the node sequences can be trea...
Later, they extended this algorithm to deal with uncertainty in the robot states [79]. Chopra et al. [94] have solved a class of “spatiotemporal” multi-robot routing problems where a distributed version of the HA computes a sequence of assignments iteratively to obtain sub-optimal routes ...