Nearest neighbor search is a problem of finding the data points from the database such that
the distances from them to the query point are the smallest. Learning to hash is one of the …

The explosive growth in Big Data has attracted much attention in designing efficient indexing
and search methods recently. In many critical applications such as large-scale search and …

Hashing has been extensively studied for large-scale cross-modal retrieval. However, there
are still some unexplored issues with existing methods. First, both the initially-provided …

Hashing method becomes popular for large scale similarity search due to its storage and
computational efficiency. Many machine learning techniques, ranging from unsupervised to …

Fashion outfit recommendation has attracted lots of attention recently. The problem becomes
even more interesting and challenging when considering users' personalized fashion …

Similarity search is an important technique in many large scale vision applications. Hashing
approach becomes popular for similarity search due to its computational and memory …

In recent years, content-based image retrieval has been of concern because of practical
needs on Internet services, especially methods that can improve retrieving speed and …

When reasoning about tasks that involve large amounts of data, a common approach is to
represent data items as objects in the Hamming space where operations can be done …