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- Batch Reinforcement Learning Description: Batch reinforcement learning is an approach within the field of reinforcement learning that allows agents to learn from multiple(...) Read more
- Batch Training Description: Batch training is a method used in machine learning, especially in the context of various architectures, where the model is updated(...) Read more
- Block-based Neural Network Description: A Block-Based Neural Network is a neural network architecture that organizes its components into modules or blocks, allowing for a(...) Read more
- Bidirectional RNN Description: Bidirectional Recurrent Neural Networks (BRNNs) are an advanced type of recurrent neural networks that allow for data processing in(...) Read more
- Bayesian Neural Networks Description: Bayesian neural networks are a type of neural network that incorporates Bayesian inference to model uncertainty in data. Unlike(...) Read more
- Backpropagation Through Time Description: Backpropagation Through Time (BPTT) is a training technique specifically used in recurrent neural networks (RNNs). This methodology(...) Read more
- Bilinear Layer Description: The Bilinear Layer is a component in neural networks that applies a bilinear transformation to the input data. This layer is(...) Read more
- Block Neural Network Description: A Block Neural Network is a neural network architecture composed of multiple interconnected blocks or modules, each of which(...) Read more
- Backpropagation Algorithm Description: The backpropagation algorithm is a fundamental method for training neural networks, based on minimizing error through an iterative(...) Read more
- Biologically Inspired Neural Networks Description: Biologically inspired neural networks are computational models designed to simulate the functioning of neural networks in the human(...) Read more
- Block Sparse Neural Networks Description: Block Sparse Neural Networks are a type of neural network architecture that focuses on computational efficiency and memory usage(...) Read more
- Boundary Representation Description: Boundary representation is a method for representing shapes using their boundaries instead of their volume. This approach focuses(...) Read more
- Backpropagation Error Description: Backpropagation error is a fundamental concept in training neural networks, referring to the calculation of the error at the(...) Read more
- Biased Estimator Description: A biased estimator is a concept in statistics that refers to an estimator whose expected value does not coincide with the true(...) Read more
- Boosted Trees Description: Boosted Trees are a type of ensemble learning method that combines multiple decision trees to improve predictive performance. This(...) Read more
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