For a graph G(V,E) and a vertex s ∈ V , a weighting scheme (w : E → N) is called a min-unique (resp. max-unique) weighting scheme, if for any vertex v of the graph G, there is a unique path of minimum(resp. maximum) weight1 from s to v. Instead, if the number of paths of minimum(resp. maximum) weight is bounded by n for some constant c, then the weighting scheme is called a min-poly (resp. max-...

In this paper, we consider online prediction from expert advice in a situation where each expert observes its own loss at each time while the loss cannot be disclosed to others for reasons of privacy or confidentiality preservation. Our secure exponential weighting scheme enables exploitation of such private loss values by making use of cryptographic tools. We proved that the regret bound of th...

This paper presents a new random weighting method for estimation of Poisson distributions. A theory is established for random weighting estimation of the population parameters of two Poisson distributions with partially missing data. The strong convergence of the random weighting estimation is rigorously proved under the condition of 1 1 E X     (0 1)    . The random weighting estimation...

In a network, a distributed consensus algorithm is fully characterized by its weighting matrix. Although there exist numerical methods for obtaining the optimal weighting matrix, we have not found an in-network implementation of any of these methods that works for all network topologies. In this paper, we propose an in-network algorithm for finding such an optimal weighting matrix.

The effect of term weighting on selecting intrinsic dimensionality of data is discussed. Experiments are conducted, using different term weighting and dimensionality selection methods, on four testing document collections (namely Medline, Cranfield, CACM and CISI). The results point that transforming the data matrix using a term weighting scheme plays a vital role in identifying the intrinsic d...

I~AMANATHAN, N. L. A new weighting system for mean surface temperature of the human body. J. Appl. Physiol. 19(3): 531-533. 1g64.-On the basis of an analysis of the skin temperature data on three resting human subjects from I 12 experiments, a simple weighting system for computing the mean skin temperature from observations on four areas of the body, namely, chest, arms, thighs, and legs, has b...

In this paper, we present two novel class-based weighting methods for the Euclidean nearest neighbor algorithm and compare them with global weighting methods considering empirical results on a widely accepted time series classification benchmark dataset. Our methods provide higher accuracy than every global weighting in nearly half of the cases and they have better overall performance. We concl...

Text categorization is a task of automatically assigning documents to a set of predefined categories. Usually it involves a document representation method and term weighting scheme. This paper proposes a new term weighting scheme called Modified Inverse Document Frequency (MIDF) to improve the performance of text categorization. The document represented in MIDF is trained using the support vect...

The Miettinen & Nurminen (1985) method is often used for constructing confidence intervals of the difference in binomial proportions from stratified 2x2 samples. However, the weighting strategy proposed in their paper requires an iterative procedure to implement, which is nested within another iterative procedure for finding the confidence limits. This paper examines the Cochran-Mantel-Haenszel...

This paper presents a new random weighting method for estimation of one-sided confidence intervals in discrete distributions. It establishes random weighting estimations for the Wald and Score intervals. Based on this, a theorem of coverage probability is rigorously proved by using the Edgeworth expansion for random weighting estimation of the Wald interval. Experimental results demonstrate tha...