35154734
Isolation and the Jump Operator
18609322
On the Quotient Structure of Computably Enumerable Degrees Modulo the Noncuppable Ideal
We show that minimal pairs exist in the quotient structure of $\mathcal{R}$ modulo the ideal of noncuppable degrees.
7723209
1-Generic splittings of computably enumerable degrees
Say a set G⊆ω is 1-generic if for any e∈ω, there is a string σ⊂G such that {e}σ(e)↓ or ∀τ⊇σ({e}τ(e)↑). It is known that 0′ can be split into two 1-generic degrees. In this paper, we generalize this and prove that any nonzero computably enumerable degree can be split into two 1-generic degrees. As a corollary, no two computably enumerable degrees bound the same class of 1-generic degrees.
35293254
Quasi-complements of the cappable degrees
Say that a nonzero c. e. degree b is a quasi-complement of a c. e. degree a if a ∩ b = 0 and a ∪ b is high. It is well-known (due to Shore) that each cappable degree has a high quasi-complement. However, by the existence of the almost deep degrees, there are nonzero cappable degrees having no low quasi-complements. In this paper, we prove that any nonzero cappable degree has a low2 quasi-complement. (© 2004 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
1961392
Degrees of Weakly Computable Reals
This paper studies the degrees of weakly computable reals. It is shown that certain types of limit-recursive reals are Turing incomparable to all weakly computable reals except the recursive and complete ones. Furthermore, it is shown that an r.e. Turing degree is array-recursive iff every real in it is weakly computable.
1638130
Bounding computably enumerable degrees in the Ershov hierarchy
Nanyang Technol Univ, Sch Math & Phys Sci, Div Math Sci, Singapore 639798, Singapore. Chinese Acad Sci, Inst Software, Beijing 100080, Peoples R China. Natl Univ Singapore, Dept Math, Singapore 119260, Singapore.
2439726
Concept boundary detection for speeding up SVMs
Support Vector Machines (SVMs) suffer from an O(n2) training cost, where n denotes the number of training instances. In this paper, we propose an algorithm to select boundary instances as training data to substantially reduce n. Our proposed algorithm is motivated by the result of (Burges, 1999) that, removing non-support vectors from the training set does not change SVM training results. Our algorithm eliminates instances that are likely to be non-support vectors. In the concept-independent preprocessing step of our algorithm, we prepare nearest-neighbor lists for training instances. In the concept-specific sampling step, we can then effectively select useful training data for each target concept. Empirical studies show our algorithm to be effective in reducing n, outperforming other competing downsampling algorithms without significantly compromising testing accuracy.
17031172
Predictive buffer control in delivering remotely stored video using proxy servers
We study the problem of using proxy servers to stream video stored at a geographically separate location. The separation of the server and the storage introduces a non-negligible delay in retrieving video frames in real time. We assume an additive-increase/multiplicative-decrease transport protocol to support the streaming process and develop an effective scheme to achieve consistent, high streaming quality. The heart of the scheme is the control of buffer occupancy at the proxy server. We model the buffer as a bilinear dynamical system disturbed by a point process with stochastic state-dependent intensity. We first develop a buffer controller that does not exploit this model. Then, using the buffer model, we construct a second controller based on an optimal-control analysis for the case without retrieval delay. Extending these two controllers, we subsequently synthesize two controllers based on prediction of future system states using the model, taking into account both the delay and the state-dependent disturbance intensity. Our empirical study illustrates the effectiveness of the streaming scheme. We further find that the controllers exploiting the buffer model demonstrate performance significantly superior to that of the model-free controller in overcoming the adverse impact of the retrieval delay. We also conduct limited experiments to study the impact of variable retrieval delays.
1677219
Application of Smodels in Quartet Based Phylogeny Construction
Evolution is an important sub-area of study in biological science, where given a set of taxa, the goal is to reconstruct their evolutionary history, or phylogeny. One very recent approach is to predict a local phylogeny for every subset of 4 taxa, called a quartet topology, and then to assemble a phylogeny for the whole set of taxa satisfying these predicted quartet topologies. In general, the predicted quartet topologies might not always agree with each other, and thus the objective function becomes to satisfy a maximum number of them. This is the well known Maximum Quartet Consistency (MQC) problem. In the past, the MQC problem has been solved by dynamic programming and the so-called fixed-parameter method. Recently, we have proposed to solve the MQC in answer set programming. In this note, we summarize the theoretical results of this approach and report new experimental results for the purpose of comparison, which show that our approach in answer set programming is favored over the existing approaches based on dynamic programming and fixed-parameter method. In particular, some of the hard instances (where the error ratio is high) that were not reported to be solved in other approaches can now be solved in our approach.
4178545
Data placement and query processing based on RPE parallelisms
The basic idea behind parallel database systems is to perform operations in parallel to reduce the response time and improve the system throughput. Data placement is a key factor on the performance of parallel database systems. This paper proposes two data partition strategies to decluster XML documents with very large size, path schema based path instance balancing (PSPIB) strategy, in which all path instances with the same path schema in a data tree are declustered evenly over all sites, and node schema based node round-robin (NSNRR) strategy, in which all node objects with the same node schema in a data tree are declustered over all sites in a round-robin way. Accordingly, two query processing algorithms are proposed based on the two partition methods, parallel path merge (PPM) algorithm and parallel pipelining path join (PPPJ) algorithm. The performance analysis and evaluation on the two data placement strategies and corresponding query processing algorithms are given in this paper.
858614
Formulating context-dependent similarity functions
Tasks of information retrieval depend on a good distance function for measuring similarity between data instances. The most effective distance function must be formulated in a context-dependent (also application-, data-, and user-dependent) way. In this paper, we present a novel method, which learns a distance function by capturing the nonlinear relationships among contextual information provided by the application, data, or user. We show that through a process called the "kernel trick," such nonlinear relationships can be learned efficiently in a projected space. In addition to using the kernel trick, we propose two algorithms to further enhance efficiency and effectiveness of function learning. For efficiency, we propose a SMO-like solver to achieve O(N2) learning performance. For effectiveness, we propose using unsupervised learning in an innovative way to address the challenge of lack of labeled data (contextual information). Theoretically, we substantiate that our method is both sound and optimal. Empirically, we demonstrate that our method is effective and useful.