Distributed Complementary Binary Quantization for Joint Hash Table Learning
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2020.2965992
Abstract: Building multiple hash tables serves as a very successful technique for gigantic data indexing, which can simultaneously guarantee both the search accuracy and efficiency. However, most of existing multitable indexing solutions, without informative hash codes… read more here.
Keywords: hash; complementary binary; quantization; cbq ... See more keywords
Binary Quantization Analysis of Neural Networks Weights on MNIST Dataset
Sign Up to like & getrecommendations! Published in 2021 at "Elektronika ir Elektrotechnika"
DOI: 10.5755/j02.eie.28881
Abstract: This paper considers the design of a binary scalar quantizer of Laplacian source and its application in compressed neural networks. The quantizer performance is investigated in a wide dynamic range of data variances, and for… read more here.
Keywords: networks weights; analysis neural; neural networks; weights mnist ... See more keywords