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TIT
2011
116views more  TIT 2011»
13 years 3 months ago
Convex Programming Upper Bounds on the Capacity of 2-D Constraints
—The capacity of 1-D constraints is given by the entropy of a corresponding stationary maxentropic Markov chain. Namely, the entropy is maximized over a set of probability distri...
Ido Tal, Ron M. Roth
CVPR
2011
IEEE
13 years 21 days ago
Earth Mover’s Prototypes: a Convex Learning Approach for Discovering Activity Patterns in Dynamic Scenes
We present a novel approach for automatically discovering spatio-temporal patterns in complex dynamic scenes. Similarly to recent non-object centric methods, we use low level visu...
Elisa Ricci, Gloria Zen
CORR
2011
Springer
214views Education» more  CORR 2011»
13 years 16 days ago
Convex Approaches to Model Wavelet Sparsity Patterns
Statistical dependencies among wavelet coefficients are commonly represented by graphical models such as hidden Markov trees (HMTs). However, in linear inverse problems such as d...
Nikhil S. Rao, Robert D. Nowak, Stephen J. Wright,...
NIPS
2008
13 years 10 months ago
On the Generalization Ability of Online Strongly Convex Programming Algorithms
This paper examines the generalization properties of online convex programming algorithms when the loss function is Lipschitz and strongly convex. Our main result is a sharp bound...
Sham M. Kakade, Ambuj Tewari
FLAIRS
2004
13 years 10 months ago
Blind Data Classification Using Hyper-Dimensional Convex Polytopes
A blind classification algorithm is presented that uses hyperdimensional geometric algorithms to locate a hypothesis, in the form of a convex polytope or hyper-sphere. The convex ...
Brent T. McBride, Gilbert L. Peterson