random variable. DBNs generalize KFMs by allowing arbitrary probability distributions, not just (unimodal) linear-Gaussian. In this thesis, I will discuss how to represent many different kinds of models as DBNs, how to perform exact and approximate inference in DBNs, and how to learn DBN models from

In this paper we develop a new data structure for implementing heaps (priority queues). Our structure, Fibonacci heaps (abbreviated F-heaps), extends the binomial queues proposed by Vuillemin and studied further by Brown. F-heaps support arbitrary deletion from an n-item heap in qlogn) amortized

. Introduction The task of calculating posterior marginals on nodes in an arbitrary Bayesian network is known to be NP hard In this paper we investigate the approximation performance of "loopy belief propagation". This refers to using the well-known Pearl polytree algorithm [12] on a Bayesian network

machines with m unit-length tasks [3, 10]. After considering the case of arbitrary task lengths, we then consider the performance of uniform random assignment when task lengths are generated randomly according to an exponential distribution. We show that if the number of tasks exceeds mln

“bandlimited and sinc kernel ” case. In particular, we show how to sample and reconstruct periodic and finite-length streams of Diracs, nonuniform splines, and piecewise polynomials using sinc and Gaussian kernels. For infinite-length signals with finite local rate of innovation, we show local sampling

In speech analysis, a recurring acoustical problem is the estimation of resonant structure of a tube of non-uniform cross-sectional area. We model such tubes as a finite sequence of cylindrical tubes of arbitrary, non-uniform length. From this model, we derive a closed form expression

Given an error-correcting code over strings of length n and an arbitrary input string also of length n, the list decoding problem is that of finding all codewords within a specified Hamming distance from the input string. We present an improved list decoding algorithm for decoding Reed

. Given an arbitrary finite binary sequence, what is the length of the shortest program for calculating it? What are the properties of those binary sequences of a given length which require the longest programs? Do most of the binary sequences of a given length require programs of about the same length

--Zolotarev reduction, a concept introduced by Schnorr (1987). Empirical tests show that the strongest of these algorithms solves almost all subset sum problems with up to 66 random weights of arbitrary bit length within at most a few hours on a UNISYS 6000/70 or within a couple of minutes on a SPARC 1+ computer.

Doo-Sabin and Catmull-Clark subdivision surfaces are based on the notion of repeated knot insertion of uniform tensor product B-spline surfaces. This paper develops rules for non-uniform Doo-Sabin and Catmull-Clark surfaces that generalize non-uniform tensor product B-spline surfaces to arbitrary