Vector Quantization in DeepLearning 参考文献 Overview What is the Quantization? Types of Quantization What's and How's of Vector Quantization? Vector Quantization in DeepLearning What is the Quantization? 定义:将采样后的离散信号按照某种标准(电平)进行划分归类 下面是一段语音模拟信号: 图1 数字模拟信...
Villmann, T., Bohnsack, A., Kaden, M.: Can learning vector quantization be an alternative to SVM and deep learning?-recent trends and advanced variants of learning vector quantization for classification learning. J. Artif. Intell. Softw. Comput. Res. 7(1), 65-81 (2017)...
Learnable product quantization for anomaly detectionAnomaly detectionDeep learningProduct quantizationQuantization error? 2024 Elsevier B.V.In many anomaly detection... S Zhang,W Chen,BLH Lu - 《Neurocomputing》 被引量: 0发表: 2024年 A deep learning based multi-image compression technique A multi-im...
[5] Yoojin Choi, Mostafa El-Khamy, and Jungwon Lee. Towards the limit of network quantization. arXiv preprint arXiv:1612.01543, 2016. [6] Matthieu Courbariaux, Yoshua Bengio, and Jean-Pierre David. Binaryconnect: Training deep neural networks with binary weights during propagations. In Advanc...
许多基于学习的二值化或产物量化方法可用,例如光谱哈希(Spectral Hashing,Weiss et al., 2008)、迭代量化(Iterative Quantization,Gong et al., 2012)和笛卡尔k-means(Cartesian k-means,Norouzi & Fleet, 2013)等。然而,它们不适用于这个特定任务,因为我们需要存储学习的参数矩阵(例如旋转矩阵),这非常大。出于这个...
We present a new approach to learn compressible representations in deep architectures with an end-to-end training strategy. Our method is based on a soft (continuous) relaxation of quantization and entropy, which we anneal to their discrete counterparts throughout training. We showcase this method...
Vector Quantization - Pytorch A vector quantization library originally transcribed from Deepmind's tensorflow implementation, made conveniently into a package. It uses exponential moving averages to update the dictionary. VQ has been successfully used by Deepmind and OpenAI for high quality generation of...
This paper compares the performance of classifiers that represent radar target signatures using vector quantization (VQ) and learning vector quantization (LVQ). The classifier performance is evaluated with a set of high resolution millimeter-wave radar data from four ground vehicles (Camaro, van,...
You might want to try the example programLearning Vector Quantization. It follows the discussion of training given above. Supplemental LVQ2.1 Learning Rule (learnlv2) The following learning rule is one that might be appliedafterfirst applying LVQ1. It can improve the result of the first learning...
The frequency sensitive competitive learning (FSCL) algorithm requires an excessive amount of training for vector quantizers with large codebooks. The authors present a possible solution to this problem through the application of the multiple stage vector quantization (MSVQ) technique to the FSCL vecto...