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Preprints.org
Residual Connection Learning by Contextual Modulation Training in Modern Deep Neural Networks
2025
Residual connections are a cornerstone of modern deep neural networks, facilitating stable gradient propagation and maintaining representational expressiveness. Conventional residual formulations typically combine identity mappings and functional transformati…
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Algorithm

Sequence of operations for a task

In mathematics and computer science, an algorithm ( ) is a finite sequence of mathematically rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing calculations and data processing. More advanced algorithms can use conditionals to divert the code execution through various routes (referred to as automated decision-making) and deduce valid inferences (referred to as automated reasoning).

In contrast, a heuristic is an approach to solving problems without well- defined correct or optimal results. For example, although social media recommender systems are commonly called "algorithms", they actually rely on heuristics as there is no truly "correct" recommendation.

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Preprints.org
Residual Connection Learning by Contextual Modulation Training in Modern Deep Neural Networks
2025
Residual connections are a cornerstone of modern deep neural networks, facilitating stable gradient propagation and maintaining representational expressiveness. Conventional residual formulations typically combine identity mappings and functional transformations with equal weight, without considering the input-dependent importance of each component. This uniformity restricts the model’s capability to adaptively regulate information flow. We propose a novel Contextual Modulation Training (CoMT) framework that intro…
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