In this paper we propose a new information-theoretic divisive algorithm for word clustering applied to text classification. In previous work, such "distributional clustering" of features has been found to achieve improvements over feature selection in terms of classification accuracy, especially at lower number of features [2, 28]. However the existing clustering techniques are agglomerative in nature and result in (i) sub-optimal word clusters and (ii) high computational cost. In order to explicitly capture the optimality of word clusters in an information theoretic framework, we first derive a global criterion for feature clustering. We then present a fast, divisive algorithm that monotonically decreases this objective function value, thus converging to a local minimum. We show that our algorithm minimizes the "within-cluster Jensen-Shannon divergence" while simultaneously maximizing the "between-cluster Jensen-Shannon divergence". In comparison to the previously proposed agglomerative strategies our divisive algorithm achieves higher classification accuracy especially at lower number of features. We further show that feature clustering is an effective technique for building smaller class models in hierarchical classification. We present detailed experimental results using Naive Bayes and Support Vector Machines on the 20 Newsgroups data set and a 3-level hierarchy of HTML documents collected from Dmoz Open Directory.

The usual recursive summation technique is just one of several ways of computing the sum of n floating point numbers. Five summation methods and their variations are analyzed here. The accuracy of the methods is compared using rounding error analysis and numerical experiments. Four ofthe methods are shown to be special cases of a general class of methods, and an error analysis is given for this class. No one method is uniformly more accurate than the others, but some guidelines are givenon the choice of method in particular cases.

We describe a mechanically checked proof of the correctness of the kernel of the floating point division algorithm used on the AMD5K 86 microprocessor. The kernel is a non-restoring division algorithm that computes the floating point quotient of two double extended precision floating point numbers, p and d (d 6= 0), with respect to a rounding mode, mode. The algorithm is defined in terms of floating point addition and multiplication. First, two NewtonRaphson iterations are used to compute a floating point approximation of the reciprocal of d. The result is used to compute four floating point quotient digits in the 24,,17 format (24 bits of precision and 17 bit exponents) which are then summed using appropriate rounding modes. We prove that if p and d are 64,,15 (possibly denormal) floating point numbers, d 6= 0 and mode specifies one of six rounding procedures and a desired precision 0 ! n 64, then the output of the algorithm is p=d rounded according to mode. We prove that every int...

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The Table Maker's Dilemma is the problem of always getting correctly rounded results when computing the elementary functions. After a brief presentation of this problem, we present new developments that have helped us to solve this problem for the double-precision exponential function in a small domain. These new results show that this problem can be solved, at least for the double-precision format, for the most usual functions. Index Terms---Floating-point arithmetic, rounding, elementary functions, Table Maker's Dilemma. ------------------------------ ###p### ------------------------------ 1INTRODUCTION HE IEEE-754 standard for floating-point arithmetic [2], [11] requires that the results of the arithmetic operations should always be correctly rounded. That is, once a rounding mode is chosen among the four possible ones, the system must behave as if the result were first computed exactly, with infinite precision, then rounded. There is no similar requirement for the elementary...

. Intel is applying formal verification to various pieces of mathematical software used in Merced, the first implementation of the new IA-64 architecture. This paper discusses the development of a generic floating point library giving definitions of the fundamental terms and containing formal proofs of important lemmas. We also briefly describe how this has been used in the verification effort so far. 1 Introduction IA-64 is a new 64-bit computer architecture jointly developed by Hewlett-Packard and Intel, and the forthcoming Merced chip from Intel will be its first silicon implementation. To avoid some of the limitations of traditional architectures, IA-64 incorporates a unique combination of features, including an instruction format encoding parallelism explicitly, instruction predication, and speculative /advanced loads [4]. Nevertheless, it also offers full upwards-compatibility with IA-32 (x86) code. 1 IA-64 incorporates a number of floating point operations, the centerpi...

In this paper, we reexamine in the framework of robust computation the Bentley-Ottmann algorithm for reporting intersecting pairs of segments in the plane. This algorithm has been reported as being very sensitive to numerical errors. Indeed, a simple analysis reveals that it involves predicates of degree 5, presumably never evaluated exactly in most implementation. Within the exact-computation paradigm we introduce two models of computation aimed at replacing the conventional model of real-number arithmetic. The first model (predicate arithmetic) assumes the exact evaluation of the signs of algebraic expressions of some degree, and the second model (exact arithmetic) assumes the exact computation of the value of...

Since they often embody compact but mathematically sophisticated algorithms, operations for computing the common transcendental functions in floating point arithmetic seem good targets for formal verification using a mechanical theorem prover. We discuss some of the general issues that arise in verifications of this class, and then present a machine-checked verification of an algorithm for computing the exponential function in IEEE-754 standard binary floating point arithmetic. We confirm (indeed strengthen) the main result of a previously published error analysis, though we uncover a minor error in the hand proof and are forced to confront several subtle issues that might easily be overlooked informally. The development described here includes, apart from the proof itself, a formalization of IEEE arithmetic, a mathematical semantics for the programming language in which the algorithm is expressed, and the body of pure mathematics needed. All this is developed logically from first prin...

We present a method to verify the correctness of parallel programs that perform complex numerical computations, including computations involving floating-point arithmetic. The method requires that a sequential version of the program be provided, to serve as the specification for the parallel one. The key idea is to use model checking, together with symbolic execution, to establish the equivalence of the two programs.

: The inverse kinematics of serial manipulators is a central problem in the automatic control of robot manipulators. The main interest has been in inverse kinematics of a six revolute jointed manipulator with arbitrary geometry. It has been recently shown that the joints of a general 6R manipulator can orient themselves in 16 different configurations (at most), for a given pose of the end--effector. However, there are no good practical solutions available, which give a level of performance expected of industrial manipulators. In this paper, we present an algorithm and implementation for real time inverse kinematics for a general 6R manipulator. When stated mathematically, the problem reduces to solving a system of multivariate equations. We make use of the algebraic properties of the system and the techniques used for reducing the problem to solving a univariate polynomial. However, the polynomial is expressed as a matrix determinant and its roots are computed by reducing to an eigenva...