1.3k citations · 2.8k across the 97 of their papers we have counts for
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On Lightweight Privacy-Preserving Collaborative Learning for IoT Objects
Linshan Jiang, Rui Tan, Xin Lou +1
The Internet of Things (IoT) will be a main data generation infrastructure for achieving better system intelligence. This paper considers the design and implementation of a practic…
Structured Learning of Binary Codes with Column Generation
Guosheng Lin, Fayao Liu, Chunhua Shen +2
Hashing methods aim to learn a set of hash functions which map the original features to compact binary codes with similarity preserving in the Hamming space. Hashing has proven a v…
Supervised Hashing Using Graph Cuts and Boosted Decision Trees
Guosheng Lin, Chunhua Shen, Anton van den Hengel
Embedding image features into a binary Hamming space can improve both the speed and accuracy of large-scale query-by-example image retrieval systems. Supervised hashing aims to map…
Optimizing Ranking Measures for Compact Binary Code Learning
Guosheng Lin, Chunhua Shen, Jianxin Wu
Hashing has proven a valuable tool for large-scale information retrieval. Despite much success, existing hashing methods optimize over simple objectives such as the reconstruction…
A General Two-Step Approach to Learning-Based Hashing
Guosheng Lin, Chunhua Shen, David Suter +1
Most existing approaches to hashing apply a single form of hash function, and an optimization process which is typically deeply coupled to this specific form. This tight coupling r…
StructBoost: Boosting Methods for Predicting Structured Output Variables
Chunhua Shen, Guosheng Lin, Anton van den Hengel
Boosting is a method for learning a single accurate predictor by linearly combining a set of less accurate weak learners. Recently, structured learning has found many applications…