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 ...

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 ...

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 ...

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 ...

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. ...

A service-providing system consists of hosts that provide services such as data, content, computational and memory resources and data-based services to other entities in the system. Consumers that wish to use services ...

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 ...

Executing untrusted code while preserving security requiresenforcement of memory and control-flow safety policies:untrusted code must be prevented from modifying memory orexecuting code except as explicitly allowed. ...

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, ...

In human-human dialogues, face-to-face meetings are often preferred over phone conversations.One explanation is that non-verbal modalities such as gesture provide additionalinformation, making communication more efficient ...

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 ...

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 ...

A major obstacle in photography is the presence of distracting elements that pull attention away from the main subject and clutter the composition. In this article, we present a new image-processing technique that reduces ...

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, ...

We describe how a virtual node abstraction layer can be used to coordinate the motion of real mobile nodes in a region of 2-space. In particular, we consider how nodes in a mobile ad hoc network can arrange themselves along ...

We present a technique that enables the use of finite modelfinding to check the satisfiability of certain formulaswhose intended models are infinite. Such formulas arisewhen using the language of sets and relations to ...

We present a simple, efficient, and self-contained construction of a wait-free regular register from Byzantine storage components. Our construction utilizes a novel building block, called 1-regular register, which can be ...

This paper presents a statistical framework which combines the registration of an atlas with the segmentation of MR images. We use an Expectation Maximization-based algorithm to find a solution within the model, which ...

This paper bridges the gap between variable selection methods (e.g., Pearson coefficients, KS test) and dimensionality reductionalgorithms (e.g., PCA, LDA). Variable selection algorithms encounter difficulties dealing with ...

We present two new results for the problem of approximating a given real m by n matrix A by a rank-k matrix D, where k < min{m, n}, so as to minimize ||A-D||_F^2. It is known that bysampling O(k/eps) rows of the matrix, ...