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Simultaneous Localization, Calibration, and Tracking in an ad Hoc Sensor Network
(2005-04-26)
We introduce Simultaneous Localization and Tracking (SLAT), the problem of tracking a target in a sensor network while simultaneously localizing and calibrating the nodes of the network. Our proposed solution, LaSLAT, ...
Fast Rates for Regularized Least-squares Algorithm
(2005-04-14)
We develop a theoretical analysis of generalization performances of regularized least-squares on reproducing kernel Hilbert spaces for supervised learning. We show that the concept of effective dimension of an integral ...
Risk Bounds for Regularized Least-squares Algorithm with Operator-valued kernels
(2005-05-16)
We show that recent results in [3] on risk bounds for regularized least-squares on reproducing kernel Hilbert spaces can be straightforwardly extended to the vector-valued regression setting. We first briefly introduce ...
Learning From Snapshot Examples
(2005-04-13)
Examples are a powerful tool for teaching both humans and computers.In order to learn from examples, however, a student must first extractthe examples from its stream of perception. Snapshot learning is ageneral approach ...
Construction by robot swarms using extended stigmergy
(2005-04-08)
We describe a system in which simple, identical, autonomous robots assemble two-dimensional structures out of identical building blocks. We show that, in a system divided in this way into mobile units and structural units, ...
Identifying Expression Fingerprints using Linguistic Information
(2005-11-18)
This thesis presents a technology to complement taxation-based policy proposals aimed at addressing the digital copyright problem. Theapproach presented facilitates identification of intellectual propertyusing expression ...
Analysis of Perceptron-Based Active Learning
(2005-11-17)
We start by showing that in an active learning setting, the Perceptron algorithm needs $\Omega(\frac{1}{\epsilon^2})$ labels to learn linear separators within generalization error $\epsilon$. We then present a simple ...
Conditional Random People: Tracking Humans with CRFs and Grid Filters
(2005-12-01)
We describe a state-space tracking approach based on a Conditional Random Field(CRF) model, where the observation potentials are \emph{learned} from data. Wefind functions that embed both state and observation into a space ...
Online Learning of Non-stationary Sequences
(2005-11-17)
We consider an online learning scenario in which the learner can make predictions on the basis of a fixed set of experts. We derive upper and lower relative loss bounds for a class of universal learning algorithms involving ...
New LSH-based Algorithm for Approximate Nearest Neighbor
(2005-11-04)
We present an algorithm for c-approximate nearest neighbor problem in a d-dimensional Euclidean space, achieving query time ofO(dn^{1/c^2+o(1)}) and space O(dn + n^{1+1/c^2+o(1)}).