270 search results - page 48 / 54 » Large-Scale Many-Class Learning |
ICDM
2009
IEEE
14 years 4 months ago
2009
IEEE
Abstract -- Detection of execution anomalies is very important for the maintenance, development, and performance refinement of large scale distributed systems. Execution anomalies ...
MM
2006
ACM
14 years 3 months ago
2006
ACM
Labeling objects in images is an essential prerequisite for many visual learning and recognition applications that depend on training data, such as image retrieval, object detecti...
SIGIR
2010
ACM
14 years 1 months ago
2010
ACM
The ability of fast similarity search at large scale is of great importance to many Information Retrieval (IR) applications. A promising way to accelerate similarity search is sem...
PRL
2010
13 years 8 months ago
2010
: Organizing data into sensible groupings is one of the most fundamental modes of understanding and learning. As an example, a common scheme of scientific classification puts organ...
WWW
2011
ACM
13 years 4 months ago
2011
ACM
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...