Name
Abstract | ||
|---|---|---|
We present a framework for margin based active learning of linear separators. We instantiate it for a few important cases, some of which have been previously considered in the literature.We analyze the effectiveness of our framework both in the realizable case and in a specific noisy setting related to the Tsybakov small noise condition. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-72927-3_5 | COLT |
Keywords | Field | DocType |
linear separator,important case,active learning,specific noisy,tsybakov small noise condition,realizable case | Active learning,Margin (machine learning),Active learning (machine learning),Computer science,Artificial intelligence,Sample complexity,Machine learning,Unit sphere | Conference |
Volume | ISSN | Citations |
4539 | 0302-9743 | 67 |
PageRank | References | Authors |
2.97 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maria-Florina Balcan | 1 | 1445 | 105.01 |
| Andrei Broder | 2 | 7357 | 920.20 |
| Zhang, Tong | 3 | 7126 | 611.43 |