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A new biologically motivated framework for robust object recognition
(2004-11-14)
In this paper, we introduce a novel set of features for robust object recognition, which exhibits outstanding performances on a variety ofobject categories while being capable of learning from only a fewtraining examples. ...
Learning with Matrix Factorizations
(2004-11-22)
Matrices that can be factored into a product of two simpler matricescan serve as a useful and often natural model in the analysis oftabulated or high-dimensional data. Models based on matrixfactorization (Factor Analysis, ...
Regularization Through Feature Knock Out
(2004-11-12)
In this paper, we present and analyze a novel regularization technique based on enhancing our dataset with corrupted copies of the original data. The motivation is that since the learning algorithm lacks information about ...
Simultaneous Localization and Tracking in Wireless Ad-hoc Sensor Networks
(2005-05-31)
In this thesis we present LaSLAT, a sensor network algorithm thatsimultaneously localizes sensors, calibrates sensing hardware, andtracks unconstrained moving targets using only range measurementsbetween the sensors and ...
Comparing Visual Features for Morphing Based Recognition
(2005-05-25)
This thesis presents a method of object classification using the idea of deformable shape matching. Three types of visual features, geometric blur, C1 and SIFT, are used to generate feature descriptors. These feature ...
A Novel Active Contour Framework. Multi-component Level Set Evolution under Topology Control
(2005-06-01)
We present a novel framework to exert a topology control over a level set evolution. Level set methods offer several advantages over parametric active contours, in particular automated topological changes. In some applications, ...
Lexical Chains and Sliding Locality Windows in Content-based Text Similarity Detection
(2005-05-19)
We present a system to determine content similarity of documents. More specifically, our goal is to identify book chapters that are translations of the same original chapter; this task requires identification of not only ...
Nonlinear Latent Variable Models for Video Sequences
(2005-06-06)
Many high-dimensional time-varying signals can be modeled as a sequence of noisy nonlinear observations of a low-dimensional dynamical process. Given high-dimensional observations and a distribution describing the ...
Empirical Effective Dimension and Optimal Rates for Regularized Least Squares Algorithm
(2005-05-27)
This paper presents an approach to model selection for regularized least-squares on reproducing kernel Hilbert spaces in the semi-supervised setting. The role of effective dimension was recently shown to be crucial in the ...
Some Properties of Empirical Risk Minimization over Donsker Classes
(2005-05-17)
We study properties of algorithms which minimize (or almost minimize) empirical error over a Donsker class of functions. We show that the L2-diameter of the set of almost-minimizers is converging to zero in probability. ...