A randomized algorithm for closest-point queries
SIAM Journal on Computing
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Approximate nearest neighbors: towards removing the curse of dimensionality
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multidimensional binary search trees used for associative searching
Communications of the ACM
ACM Computing Surveys (CSUR)
Similarity estimation techniques from rounding algorithms
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
The K-D-B-tree: a search structure for large multidimensional dynamic indexes
SIGMOD '81 Proceedings of the 1981 ACM SIGMOD international conference on Management of data
Similarity Search in High Dimensions via Hashing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Locality-sensitive hashing scheme based on p-stable distributions
SCG '04 Proceedings of the twentieth annual symposium on Computational geometry
Indexing High-Dimensional Data for Efficient In-Memory Similarity Search
IEEE Transactions on Knowledge and Data Engineering
Content-based multimedia information retrieval: State of the art and challenges
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
A Unified Log-Based Relevance Feedback Scheme for Image Retrieval
IEEE Transactions on Knowledge and Data Engineering
On the Nyström Method for Approximating a Gram Matrix for Improved Kernel-Based Learning
The Journal of Machine Learning Research
Multi-probe LSH: efficient indexing for high-dimensional similarity search
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
SFCS '75 Proceedings of the 16th Annual Symposium on Foundations of Computer Science
Asymmetric distance estimation with sketches for similarity search in high-dimensional spaces
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Hamming Embedding and Weak Geometric Consistency for Large Scale Image Search
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Quality and efficiency in high dimensional nearest neighbor search
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Space-time tradeoffs for approximate nearest neighbor searching
Journal of the ACM (JACM)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-taught hashing for fast similarity search
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Scalable similarity search with optimized kernel hashing
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
S3MKL: scalable semi-supervised multiple kernel learning for image data mining
Proceedings of the international conference on Multimedia
Modeling social strength in social media community via kernel-based learning
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Compact hashing with joint optimization of search accuracy and time
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
An efficient indexing method for nearest neighbor searches inhigh-dirnensional image databases
IEEE Transactions on Multimedia
A Multimodal and Multilevel Ranking Scheme for Large-Scale Video Retrieval
IEEE Transactions on Multimedia
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
Semantic hashing using tags and topic modeling
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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Similarity search is a key challenge for multimedia retrieval applications where data are usually represented in high-dimensional space. Among various algorithms proposed for similarity search in high-dimensional space, Locality-Sensitive Hashing (LSH) is the most popular one, which recently has been extended to Kernelized Locality-Sensitive Hashing (KLSH) by exploiting kernel similarity for better retrieval efficacy. Typically, KLSH works only with a single kernel, which is often limited in real-world multimedia applications, where data may originate from multiple resources or can be represented in several different forms. For example, in content-based multimedia retrieval, a variety of features can be extracted to represent contents of an image. To overcome the limitation of regular KLSH, we propose a novel Boosting Multi-Kernel Locality-Sensitive Hashing (BMKLSH) scheme that significantly boosts the retrieval performance of KLSH by making use of multiple kernels. We conduct extensive experiments for large-scale content-based image retrieval, in which encouraging results show that the proposed method outperforms the state-of-the-art techniques.