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» On low dimensional random projections and similarity search
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CORR
2010
Springer
249views Education» more  CORR 2010»
13 years 7 months ago
Lower Bounds on Near Neighbor Search via Metric Expansion
In this paper we show how the complexity of performing nearest neighbor (NNS) search on a metric space is related to the expansion of the metric space. Given a metric space we loo...
Rina Panigrahy, Kunal Talwar, Udi Wieder
CVPR
2010
IEEE
14 years 1 months ago
ARISTA - Image Search to Annotation on Billions of Web Photos
Though it has cost great research efforts for decades, object recognition is still a challenging problem. Traditional methods based on machine learning or computer vision are stil...
Xin-Jing Wang, Ming Liu, Lei Zhang, Yi Li, Wei-Yin...
SAC
2009
ACM
14 years 4 days ago
Incremental board: a grid-based space for visualizing dynamic data sets
In Information Visualization, adding and removing data elements can strongly impact the underlying visual space. We introduce a chess board analogy for displaying (projecting) obj...
Roberto Pinho, Maria Cristina Ferreira de Oliveira...
PVLDB
2010
150views more  PVLDB 2010»
13 years 5 months ago
Tree Indexing on Solid State Drives
Large flash disks, or solid state drives (SSDs), have become an attractive alternative to magnetic hard disks, due to their high random read performance, low energy consumption a...
Yinan Li, Bingsheng He, Jun Yang 0001, Qiong Luo, ...
ICMLA
2007
13 years 9 months ago
Scalable optimal linear representation for face and object recognition
Optimal Component Analysis (OCA) is a linear method for feature extraction and dimension reduction. It has been widely used in many applications such as face and object recognitio...
Yiming Wu, Xiuwen Liu, Washington Mio