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Loss function

Known as: Zero-one loss, Loss, Risk function 
In mathematical optimization, statistics, decision theory and machine learning, a loss function or cost function is a function that maps an event or… Expand
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Related topics

Related topics

50 relations
Adaptive filterBackpropagationBootstrapping (statistics)Constrained optimization
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2020
Review
2020
Network Representation Learning: A Survey
With the widespread use of information technologies, information networks are becoming increasingly popular to capture complex… Expand
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Review
2019
Review
2019
A Survey on Network Embedding
Network embedding assigns nodes in a network to low-dimensional representations and effectively preserves the network structure… Expand
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Review
2018
Review
2018
An Introduction to Neural Information Retrieval
Neural models have been employed in many Information Retrieval scenarios, including ad-hoc retrieval, recommender systems, multi… Expand
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Review
2018
Review
2018
UnDeepVO: Monocular Visual Odometry Through Unsupervised Deep Learning
We propose a novel monocular visual odometry (VO) system called UnDeepVO in this paper. UnDeepVO is able to estimate the 6-DoF… Expand
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Review
2018
Review
2018
Using Deep Neural Networks for Inverse Problems in Imaging: Beyond Analytical Methods
Traditionally, analytical methods have been used to solve imaging problems such as image restoration, inpainting, and… Expand
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Review
2018
Review
2018
WaterGAN: Unsupervised Generative Network to Enable Real-Time Color Correction of Monocular Underwater Images
This letter reports on WaterGAN, a generative adversarial network (GAN) for generating realistic underwater images from in-air… Expand
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Review
2018
Review
2018
Recent advances in convolutional neural networks
In the last few years, deep learning has led to very good performance on a variety of problems, such as visual recognition… Expand
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Review
2017
Review
2017
Fixing Weight Decay Regularization in Adam
We note that common implementations of adaptive gradient algorithms, such as Adam, limit the potential benefit of weight decay… Expand
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Review
2016
Review
2016
Deep Learning in Natural Language Processing
Deep learning has emerged as a highly efficient technique in machine learning to perform text analytics, which includes text… Expand
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Highly Cited
2016
Highly Cited
2016
Person Re-identification by Multi-Channel Parts-Based CNN with Improved Triplet Loss Function
Person re-identification across cameras remains a very challenging problem, especially when there are no overlapping fields of… Expand
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