Effect of Feature Hashing on Fair Classification

2020 ◽  
Author(s):  
Ritik Dutta ◽  
Varun Gohil ◽  
Atishay Jain
Keyword(s):  
Feature Hashing

Local multi-feature hashing based fast matching for aerial images

2018 ◽  
Vol 442-443 ◽  
pp. 173-185 ◽  
Author(s):  
Suting Chen ◽  
Yunjiao Shi ◽  
Yanyan Zhang ◽  
Jiaojiao Zhao ◽  
Chuang Zhang ◽  
...  
Keyword(s):  
Aerial Images ◽  
Feature Hashing

scholarly journals Unsupervised Local Feature Hashing for Image Similarity Search

2016 ◽  
Vol 46 (11) ◽  
pp. 2548-2558 ◽  
Author(s):  
Li Liu ◽  
Mengyang Yu ◽  
Ling Shao
Keyword(s):  
Similarity Search ◽  
Local Feature ◽  
Image Similarity ◽  
Feature Hashing

scholarly journals Cuckoo Feature Hashing: Dynamic Weight Sharing for Sparse Analytics

2018 ◽  
Author(s):  
Jinyang Gao ◽  
Beng Chin Ooi ◽  
Yanyan Shen ◽  
Wang-Chien Lee
Keyword(s):  
Predictive Models ◽  
Large Scale ◽  
Model Performance ◽  
Experimental Results ◽  
Cuckoo Hashing ◽  
Dynamic Weight ◽  
Model Training ◽  
Sparse Features ◽  
Feature Hashing

Feature hashing is widely used to process large scale sparse features for learning of predictive models. Collisions inherently happen in the hashing process and hurt the model performance. In this paper, we develop a feature hashing scheme called Cuckoo Feature Hashing(CCFH) based on the principle behind Cuckoo hashing, a hashing scheme designed to resolve collisions. By providing multiple possible hash locations for each feature, CCFH prevents the collisions between predictive features by dynamically hashing them into alternative locations during model training. Experimental results on prediction tasks with hundred-millions of features demonstrate that CCFH can achieve the same level of performance by using only 15%-25% parameters compared with conventional feature hashing.

scholarly journals Feature Hashing for Language and Dialect Identification

2017 ◽  
Author(s):  
Shervin Malmasi ◽  
Mark Dras
Keyword(s):  
Feature Hashing
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