Pranking with ranking Export

@inproceedings{citeulike:3131711, abstract = {We discuss the problem of ranking instances. In our framework each instance is associated with a rank or a rating, which is an integer from 1 to k. Our goal is to nd a rank-prediction rule that assigns each instance a rank which is as close as possible to the instance\&\#039;s true rank. We describe a simple and ecient online algorithm, analyze its performance in the mistake bound model, and prove its correctness. We describe two sets of experiments, with synthetic data and with the EachMovie dataset for collaborative ltering. In the experiments we performed, our algorithm outperforms online algorithms for regression and classication applied to ranking. 1}, author = {Crammer, Koby and Singer, Yoram}, booktitle = {Advances in Neural Information Processing Systems 14}, citeulike-article-id = {3131711}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.20.378}, keywords = {learning2rank, prank}, pages = {641--647}, posted-at = {2009-05-24 14:02:54}, priority = {2}, title = {Pranking with ranking}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.20.378}, volume = {14}, year = {2002} }

TY - CONF ID - citeulike:3131711 L3 - citeulike-article-id:3131711 N2 - We discuss the problem of ranking instances. In our framework each instance is associated with a rank or a rating, which is an integer from 1 to k. Our goal is to nd a rank-prediction rule that assigns each instance a rank which is as close as possible to the instance's true rank. We describe a simple and ecient online algorithm, analyze its performance in the mistake bound model, and prove its correctness. We describe two sets of experiments, with synthetic data and with the EachMovie dataset for collaborative ltering. In the experiments we performed, our algorithm outperforms online algorithms for regression and classication applied to ranking. 1 EP - 647 TI - Pranking with ranking VL - 14 T2 - Advances in Neural Information Processing Systems 14 SP - 641 KW - learning2rank KW - prank AU - Crammer, Koby AU - Singer, Yoram PY - 2002/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.20.378 ER -