Pairwise classification is a class binarization procedure that converts a multi-class problem into a series of two-class problems, one problem for each pair of classes. While it can be shown that for training, this procedure is more efficient than the more commonly used oneagainst-all approach, it still has to evaluate a quadratic number of classifiers when computing the predicted class for a g...

Most of the recent approaches to keyword search employ graph structured representation of data. Answers to queries are generally sub-structures of the graph, containing one or more keywords. While finding the nodes matching keywords is relatively easy, determining the connections between such nodes is a complex problem requiring onthe-fly time consuming graph exploration. Current techniques suf...

In the previous lecture, we discussed how to construct pseudorandom generators for any particular class given the existence of a function f with high average-case hardness for that class, and gave an explicit construction for the class Cr. In this lecture, we will finish the proof of its correctness, and also show that we can relax the hardness assumption we need from average-case to worst-case...

Abstract-Let X,. . ,X. be a sequence of independent Rd-valued random vectors with a common density f The following class of convex hull finding algorithms is considered: find the extrema in a finite number of carefully chosen directions; eliminate the Xi’s that belong to the interior of the polyhedron formed by these extrema; apply an O(A(n)) worst-case complexity algorithm to find the convex h...

We study the problem of guaranteeing deadlines of synchronous messages with their deadlines no more than periods in an FDDI network. In order to guarantee the transmission of a synchronous message before its deadline , a precise knowledge of the worst-case situation for such transmission is required. This paper studies the worst-case scenario for transmission of a synchronous message in an FDDI...

We study the complexity of a classical combinatorial problem of computing the period of a string. We investigate both the averageand the worst-case complexity of the problem. We deliver almost tight bounds for the average-case. We show that every algorithm computing the period must examine Ω( √ m) symbols of an input string of length m. On the other hand we present an algorithm that computes th...

Prior research has suggested that the failure rates of faults follow a log normal distribution. We propose a specific model where distributions close to a log normal arise naturally from the program structure. The log normal distribution presents a problem when used in reliability growth models as it is not mathematically tractable. However we demonstrate that a worst case bound can be estimate...

We develop an efficient incremental version of an existing cost-based filtering algorithm for the knapsack constraint. On a universe of n elements, m invocations of the algorithm require a total ofO(n log n+mk log(n/k)) time, where k ≤ n depends on the specific knapsack instance. We show that the expected value of k is significantly smaller than n on several interesting input distributions, hen...

We study a constrained version of the shortest path problem in simple polygons, in which the path must visit a given target polygon. We provide a worst-case optimal algorithm for this problem and also present a method to construct a subdivision of the simple polygon to efficiently answer queries to retrieve the shortest polygon-meeting paths from a single-source to the query point. The algorith...

We develop a novel description logic (DL) for representing and reasoning with contextual knowledge. Our approach descends from McCarthy’s tradition of treating contexts as formal objects over which one can quantify and express first-order properties. As a foundation we consider several common product-like combinations of DLs with multimodal logics and adopt the prominent (Kn)ALC . We then exten...