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APPROX
2005
Springer
103views Algorithms» more  APPROX 2005»
14 years 1 months ago
Where's the Winner? Max-Finding and Sorting with Metric Costs
Traditionally, a fundamental assumption in evaluating the performance of algorithms for sorting and selection has been that comparing any two elements costs one unit (of time, work...
Anupam Gupta, Amit Kumar
SPIRE
2005
Springer
14 years 1 months ago
Using the k-Nearest Neighbor Graph for Proximity Searching in Metric Spaces
Proximity searching consists in retrieving from a database, objects that are close to a query. For this type of searching problem, the most general model is the metric space, where...
Rodrigo Paredes, Edgar Chávez
ICML
2007
IEEE
14 years 8 months ago
Information-theoretic metric learning
In this paper, we present an information-theoretic approach to learning a Mahalanobis distance function. We formulate the problem as that of minimizing the differential relative e...
Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit ...
SDM
2008
SIAM
140views Data Mining» more  SDM 2008»
13 years 9 months ago
Large-Scale Many-Class Learning
In many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. We invest...
Omid Madani, Michael Connor
CGO
2003
IEEE
13 years 11 months ago
METRIC: Tracking Down Inefficiencies in the Memory Hierarchy via Binary Rewriting
In this paper, we present METRIC, an environment for determining memory inefficiencies by examining data traces. METRIC is designed to alter the performance behavior of applicatio...
Jaydeep Marathe, Frank Mueller, Tushar Mohan, Bron...