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» Making inferences with small numbers of training sets
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AAAI
2008
13 years 10 months ago
Make3D: Depth Perception from a Single Still Image
Humans have an amazing ability to perceive depth from a single still image; however, it remains a challenging problem for current computer vision systems. In this paper, we will p...
Ashutosh Saxena, Min Sun, Andrew Y. Ng
BIOCOMP
2006
13 years 9 months ago
Theoretical Bounds for the Number of Inferable Edges in Sparse Random Networks
Abstract-- The inference of a network structure from experimental data providing dynamical information about the underlying system of investigation is an important and still outsta...
Frank Emmert-Streib, Matthias Dehmer
IBPRIA
2003
Springer
14 years 23 days ago
Reducing Training Sets by NCN-based Exploratory Procedures
In this paper, a new approach to training set size reduction is presented. This scheme basically consists of defining a small number of prototypes that represent all the original ...
María Teresa Lozano, José Salvador S...
CAEPIA
2003
Springer
14 years 24 days ago
Using the Geometrical Distribution of Prototypes for Training Set Condensing
Abstract. In this paper, some new approaches to training set size reduction are presented. These schemes basically consist of defining a small number of prototypes that represent ...
María Teresa Lozano, José Salvador S...
FOCS
2004
IEEE
13 years 11 months ago
Triangulation and Embedding Using Small Sets of Beacons
Concurrent with recent theoretical interest in the problem of metric embedding, a growing body of research in the networking community has studied the distance matrix defined by n...
Jon M. Kleinberg, Aleksandrs Slivkins, Tom Wexler