In this paper, we show that any n point metric space can be embedded into a distribution over dominating tree metrics such that the expected stretch of any edge is O(log n). This ...
We present a method for training a similarity metric from data. The method can be used for recognition or verification applications where the number of categories is very large an...
This paper introduces improvements in partitioning schemes for multiprocessor real-time systems which allow higher processor utilization and enhanced schedulability by using exact...
Vector quantization methods are confronted with a model selection problem, namely the number of prototypical feature representatives to model each class. In this paper we present a...
Alexander Denecke, Heiko Wersing, Jochen J. Steil,...
We propose an unsupervised “local learning” algorithm for learning a metric in the input space. Geometrically, for a given query point, the algorithm finds the minimum volume ...