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Multiple Code Hashing for Efficient Image Retrieval
In this paper, we propose a novel hashing framework, called multiple code hashing (MCH), to improve the performance of hash bucket search.
Deep Multi-Index Hashing for Person Re-Identification
In this paper, we propose a novel hashing method, called deep multi-index hashing (DMIH), to improve both efficiency and accuracy for ReID.
On the Evaluation Metric for Hashing
Bucket search, also called hash lookup, can achieve fast query speed with a sub-linear time cost based on the inverted index table constructed from hash codes.
Proximal SCOPE for Distributed Sparse Learning
Based on the defined metric, we theoretically prove that pSCOPE is convergent with a linear convergence rate if the data partition is good enough.
Proximal SCOPE for Distributed Sparse Learning: Better Data Partition Implies Faster Convergence Rate
Based on the defined metric, we theoretically prove that pSCOPE is convergent with a linear convergence rate if the data partition is good enough.
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