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» Lossy Reduction for Very High Dimensional Data
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CISS
2011
IEEE
13 years 1 months ago
Characterizing multiplexing and diversity in visual MIMO
—Mobile optical wireless has so far been limited to very short ranges for high data rate systems. It may be feasible to overcome the data rate limitations over large transmission...
Ashwin Ashok, Marco Gruteser, Narayan B. Mandayam,...
ICMCS
2005
IEEE
111views Multimedia» more  ICMCS 2005»
14 years 3 months ago
Manifold learning, a promised land or work in progress?
ABSTRACT In this paper, we report our experiments using a realworld image dataset to examine the effectiveness of Isomap, LLE and KPCA. The 1,897-image dataset we used consists of ...
Mei-Chen Yeh, I-Hsiang Lee, Gang Wu, Yi Wu, Edward...
SI3D
2005
ACM
14 years 3 months ago
Texture sprites: texture elements splatted on surfaces
We present a new interactive method to texture complex geometries at very high resolution, while using little memory and without the need for a global planar parameterization. We ...
Sylvain Lefebvre, Samuel Hornus, Fabrice Neyret
NIPS
1996
13 years 11 months ago
Multidimensional Triangulation and Interpolation for Reinforcement Learning
Dynamic Programming, Q-learning and other discrete Markov Decision Process solvers can be applied to continuous d-dimensional state-spaces by quantizing the state space into an arr...
Scott Davies
CGF
2006
173views more  CGF 2006»
13 years 9 months ago
C-BDAM - Compressed Batched Dynamic Adaptive Meshes for Terrain Rendering
We describe a compressed multiresolution representation for supporting interactive rendering of very large planar and spherical terrain surfaces. The technique, called Compressed ...
Enrico Gobbetti, Fabio Marton, Paolo Cignoni, Marc...