We present a stream algorithm for the Singular-Value Decomposition (SVD) of anM X N matrix A. Our algorithm trades speed of numerical convergence for parallelism,and derives from a one-sided, cyclic-by-rows Hestenes SVD. ...

We build on the work of Micali, Rabin, and Killian [4] to introduce zero-knowledge sets and databases that may be updated in a desirable way. In particular, in order to make an update the owner of the set must publish a ...

We prove correctness of a Byzantine-fault-tolerant replication algorithm for a read/writeatomic memory that supports a dynamic replica set.

The question of how shape is represented is of central interest to understanding visual processing in cortex. While tuning properties of the cells in early part of the ventral visual stream, thought to be responsible for ...

An emerging trend in processor design is the incorporation of short vector instructions into the ISA. In fact, vector extensions have appeared in most general-purpose microprocessors. To utilize these instructions, ...

We present a mathematical state-machine model, the Dynamic I/O Automaton (DIOA) model, for defining and analyzing dynamic systems of interacting components. The systems we consider are dynamic in two senses: (1) components ...

We present a technique that enables the focused applicationof multiple analyses to di erent modules in thesame program. In our approach, each module encapsulatesone or more data structures and uses membershipin abstract ...

Discriminative learning is challenging when examples are setsof local image features, and the sets vary in cardinality and lackany sort of meaningful ordering. Kernel-based classificationmethods can learn complex decision ...

Throughout biological, chemical, and pharmaceutical research,conformational searches are used to explore the possiblethree-dimensional configurations of molecules. This thesis describesa new systematic method for ...

Upgrading the software of long-lived, highly-available distributedsystems is difficult. It is not possible to upgrade all the nodes in asystem at once, since some nodes may be unavailable and halting thesystem for an ...

While single neurons in inferior temporal (IT) cortex show differential responses to distinct complex stimuli, little is known about the responses of populations of neurons in IT. We recorded single electrode data, including ...

The interval programming model (IvP) is a mathematical programmingmodel for representing and solving multi-objective optimizationproblems. The central characteristic of the model is the use ofpiecewise linearly defined ...

Quorum systems are commonly used to maintain the consistency of replicated data in adistributed system. Much research has been devoted to developing quorum systems with good theoreticalproperties, such as fault tolerance ...

This paper describes a technique that helps a test engineerselect, from a large set of randomly generated testinputs, a small subset likely to reveal faults in the softwareunder test. The technique takes a program or ...

This report describes the aims, functions, and organization of the MAITAsystem for knowledge-based construction, adaptation, and control of networks of monitoringprocesses.

This document is a report about the capabilities and performance of the IOA Toolkit, and in particularthe tools that provide support for implementing and running distributed systems (checker,composer, code generator). The ...

Alternative pre-messenger RNA splicing affects a majority of human genes and plays important roles in development and disease. Alternative splicing (AS) events conserved since the divergence of human and mouse are likely ...

In this short technical report, we present a simple yet effective reliable broadcast protocol for sensor networks. This protocol disseminates packets throughout the sensor network by flooding and recovers from losses ...

Shape analysis is a promising technique for statically verifyingand extracting properties of programs that manipulatecomplex data structures. We introduce a new characterizationof constraints that arise in parametric ...

We introduce and explore an approach to estimating statisticalsignificance of classification accuracy, which is particularly usefulin scientific applications of machine learning where highdimensionality of the data and the ...