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» Optimizing for parallelism and data locality
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81
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NIPS
2007
15 years 2 months ago
Colored Maximum Variance Unfolding
Maximum variance unfolding (MVU) is an effective heuristic for dimensionality reduction. It produces a low-dimensional representation of the data by maximizing the variance of the...
Le Song, Alex J. Smola, Karsten M. Borgwardt, Arth...
96
Voted
NIPS
2007
15 years 2 months ago
Nearest-Neighbor-Based Active Learning for Rare Category Detection
Rare category detection is an open challenge for active learning, especially in the de-novo case (no labeled examples), but of significant practical importance for data mining - ...
Jingrui He, Jaime G. Carbonell
IPPS
2003
IEEE
15 years 6 months ago
Autonomous Protocols for Bandwidth-Centric Scheduling of Independent-Task Applications
In this paper we investigate protocols for scheduling applications that consist of large numbers of identical, independent tasks on large-scale computing platforms. By imposing a ...
Barbara Kreaseck, Larry Carter, Henri Casanova, Je...
100
Voted
ICCS
2004
Springer
15 years 6 months ago
Chunking-Coordinated-Synthetic Approaches to Large-Scale Kernel Machines
We consider a kernel-based approach to nonlinear classification that coordinates the generation of “synthetic” points (to be used in the kernel) with “chunking” (working wi...
Francisco J. González-Castaño, Rober...
122
Voted
ECCV
2010
Springer
15 years 4 months ago
Practical Methods For Convex Multi-View Reconstruction
Globally optimal formulations of geometric computer vision problems comprise an exciting topic in multiple view geometry. These approaches are unaffected by the quality of a provid...