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- Dongqing Zhang, Wu-Jun Li
- AAAI
- 2014

Due to its low storage cost and fast query speed, hashing has been widely adopted for similarity search in multimedia data. In particular, more and more attentions have been payed to multimodal hashing for search in multimedia data with multiple modalities, such as images with tags. Typically, supervised information of semantic labels is also available for… (More)

- Weihao Kong, Wu-Jun Li
- NIPS
- 2012

Most existing hashing methods adopt some projection functions to project the original data into several dimensions of real values, and then each of these projected dimensions is quantized into one bit (zero or one) by thresholding. Typically, the variances of different projected dimensions are different for existing projection functions such as principal… (More)

- Wu-Jun Li, Sheng Wang, Wang-Cheng Kang
- IJCAI
- 2016

Recent years have witnessed wide application of hashing for large-scale image retrieval. However, most existing hashing methods are based on hand-crafted features which might not be optimally compatible with the hashing procedure. Recently, deep hashing methods have been proposed to perform simultaneous feature learning and hashcode learning with deep… (More)

- Weihao Kong, Wu-Jun Li
- AAAI
- 2012

Hashing, which tries to learn similarity-preserving binary codes for data representation, has been widely used for efficient nearest neighbor search in massive databases due to its fast query speed and low storage cost. Because it is NP hard to directly compute the best binary codes for a given data set, mainstream hashing methods typically adopt a… (More)

- Wang-Cheng Kang, Wu-Jun Li, Zhi-Hua Zhou
- AAAI
- 2016

By leveraging semantic (label) information, supervised hashing has demonstrated better accuracy than unsupervised hashing in many real applications. Because the hashing-code learning problem is essentially a discrete optimization problem which is hard to solve, most existing supervised hashing methods try to solve a relaxed continuous optimization problem… (More)

- Yi Zhen, Wu-Jun Li, Dit-Yan Yeung
- RecSys
- 2009

Besides the rating information, an increasing number of modern recommender systems also allow the users to add personalized tags to the items. Such tagging information may provide very useful information for item recommendation, because the users' interests in items can be implicitly reflected by the tags that they often use. Although some content-based… (More)

- Wu-Jun Li, Dit-Yan Yeung
- IJCAI
- 2009

In many applications, the data, such as web pages and research papers, contain relation (link) structure among entities in addition to textual content information. Matrix factorization (MF) methods, such as latent semantic indexing (LSI), have been successfully used to map either content information or relation information into a lower-dimensional latent… (More)

- Wu-Jun Li, Dit-Yan Yeung
- IEEE Transactions on Knowledge and Data…
- 2010

In multiple-instance learning (MIL), an individual example is called an instance and a bag contains a single or multiple instances. The class labels available in the training set are associated with bags rather than instances. A bag is labeled positive if at least one of its instances is positive; otherwise, the bag is labeled negative. Since a positive bag… (More)

- Qing-Yuan Jiang, Wu-Jun Li
- IJCAI
- 2015

Hashing has been widely used for approximate nearest neighbor (ANN) search in big data applications because of its low storage cost and fast retrieval speed. The goal of hashing is to map the data points from the original space into a binary-code space where the similarity (neighborhood structure) in the original space is preserved. By directly exploiting… (More)

- Weihao Kong, Wu-Jun Li, Minyi Guo
- SIGIR
- 2012

Hashing is used to learn binary-code representation for data with expectation of preserving the neighborhood structure in the original feature space. Due to its fast query speed and reduced storage cost, hashing has been widely used for efficient nearest neighbor search in a large variety of applications like text and image retrieval. Most existing hashing… (More)