395 search results - page 21 / 79 » Learning to rank with partially-labeled data |
108
Voted
NIPS
2007
15 years 3 months ago
2007
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
124
click to vote
ICWSM
2009
14 years 11 months ago
2009
User generated content is extremely valuable for mining market intelligence because it is unsolicited. We study the problem of analyzing users' sentiment and opinion in their...
147
click to vote
KDD
2009
ACM
16 years 2 months ago
2009
ACM
Tag recommendation is the task of predicting a personalized list of tags for a user given an item. This is important for many websites with tagging capabilities like last.fm or de...
110
click to vote
WWW
2007
ACM
16 years 2 months ago
2007
ACM
This paper is concerned with rank aggregation, the task of combining the ranking results of individual rankers at meta-search. Previously, rank aggregation was performed mainly by...
105
click to vote
ICML
2010
IEEE
15 years 2 months ago
2010
IEEE
We propose low-rank representation (LRR) to segment data drawn from a union of multiple linear (or affine) subspaces. Given a set of data vectors, LRR seeks the lowestrank represe...