Random projection in dimensionality reduction: applications to image and text data

@inproceedings{citeulike:163241, abstract = {Random projections have recently emerged as a powerful method for dimensionality reduction. Theoretical results indicate that the method preserves distances quite nicely; however, empirical results are sparse. We present experimental results on using random projection as a dimensionality reduction tool in a number of cases, where the high dimensionality of the data would otherwise lead to burdensome computations. Our application areas are the processing of both noisy and noiseless images, and...}, author = {Bingham, Ella and Mannila, Heikki }, booktitle = {Knowledge Discovery and Data Mining}, citeulike-article-id = {163241}, keywords = {machine-learning}, pages = {245--250}, posted-at = {2008-05-08 11:01:02}, priority = {2}, title = {Random projection in dimensionality reduction: applications to image and text data}, url = {http://citeseer.ist.psu.edu/bingham01random.html}, year = {2001} }

TY - CONF ID - citeulike:163241 L3 - citeulike-article-id:163241 N2 - Random projections have recently emerged as a powerful method for dimensionality reduction. Theoretical results indicate that the method preserves distances quite nicely; however, empirical results are sparse. We present experimental results on using random projection as a dimensionality reduction tool in a number of cases, where the high dimensionality of the data would otherwise lead to burdensome computations. Our application areas are the processing of both noisy and noiseless images, and... EP - 250 TI - Random projection in dimensionality reduction: applications to image and text data T2 - Knowledge Discovery and Data Mining SP - 245 KW - machine-learning AU - Bingham, Ella AU - Mannila, Heikki PY - 2001/// UR - http://citeseer.ist.psu.edu/bingham01random.html ER -