Learning Machines (LMs) are computational entities that rely one or more ML algorithm for performing a task for which they haven't been explicitly programmed to perform. In particular, LMs are capable of adjusting their behavior to their environment. In the context of LLNs, and more generally ...
We provide two types of CTC decoders:CTC greedy decoderandCTC beam search decoder. TheCTC greedy decoderis an implementation of the simple best-path decoding algorithm, selecting at each timestep the most likely token, thus being greedy and locally optimal. TheCTC beam search decoderotherwise uti...
The back-off timer is calculated based on each SN residual energy level within a grid. In several grid cluster protocols, the algorithm selects one CH per grid based on its energy level, this CH is kept until its energy is completely depleted. Grid-cluster protocols have been used to ...
python-louvain Louvain algorithm for community detection 17 marisa-trie Static memory-efficient and fast Trie-like structures for Python. 17 gymnasium A standard API for reinforcement learning and a diverse set of reference environments (formerly Gym). 17 h5netcdf netCDF4 via h5py 17 python-snappy...
RL Reinforcement Learning RTO Retransmission TimeOut RTT Retransmission Time SOA Service Oriented Architecture STOMP Simple/Streaming TextOriented Messaging Protocol SVD Singular Value Decomposition SVM Support Vector Machine TCP Transmission Control Protocol UDP User Datagram Protocol VBF Variable Backoff Factor...
The machine learning described herein may use any appropriate machine learning algorithm. In some non-limiting examples, the machine learning algorithm is a supervised learning algorithm, unsupervised learning algorithm, reinforcement learning algorithm, a deep learning algorithm, an artificial neural network...
Article: PageRank - How Eigenvectors Power the Algorithm Behind Google Search Article: Interactive Visualization of Why Eigenvectors Matter Book: Basics of Linear Algebra for Machine Learning Computational Linear Algebra for Coders 1. The Geometry of Linear Equations 0:39:49 ✓ 2. Elimination...
A supervised machine learning algorithm uses the kernel technique to convert the data and then uses these conversions to reach one final optimal boundary for the possible outputs. The kernel function maps the inputs to the high-dimensional feature space. SVM separates the data on the basis of ...