27175112
Learnability of Relatively Quantified Generalized Formulas
In this paper we study the learning complexity of a vast class of quantifed formulas called Relatively Quantified Generalized Formulas. This class of formulas is parameterized by a set of predicates, called a basis. We give a complete classification theorem, showing that every basis gives rise to quantified formulas that are either polynomially learnable with equivalence queries, or not polynomially predictable with membership queries under some cryptographic assumption. We also provide a simple criteria distinguishing the learnable cases from the non-learnable cases.
958592
Inverse Circumscription
Inverse (or identification) problems involve deciding whether or not an explicitly given set of data points have an implicit description, for instance, in the form of a constraint network. Such problems provide insight into the relationships among various representations of knowledge, which may have differing computational properties. This paper formalizes and studies the inverse circumscription problem, which (roughly speaking) is to decide, given a set of models, if there exists a formula whose circumscription describes the input set.
3265105
A coalgebraic approach to Kleene algebra with tests
Kleene algebra with tests is an extension of Kleene algebra, the algebra of regular expressions, which can be used to reason about programs. We develop a coalgebraic theory of Kleene algebra with Tests, along the lines of the coalgebraic theory of regular expressions based on deterministic automata. Since the known automata-theoretic presentation of Kleene algebra with tests does not lend itself to a coalgebraic theory, we define a new interpretation of Kleene algebra with tests expressions and a corresponding automata-theoretic presentation. One outcome of the theory is a coinductive proof principle, that can be used to establish equivalence of our Kleene algebra with tests expressions.
9351295
Looking Algebraically at Tractable Quantified Boolean Formulas
We make use of the algebraic theory that has been used to study the complexity of constraint satisfaction problems, to investigate tractable quantified boolean formulas. We present a pair of results: the first is a new and simple algebraic proof of the tractability of quantified 2-satisfiability; the second is a purely algebraic characterization of models for quantified Horn formulas that were given by Kleine Buning, Subramani, and Zhao, and described proof-theoretically.
6781537
Formal Models of Heavy-Tailed Behavior in Combinatorial Search
Recently, it has been found that the cost distributions of randomized backtrack search in combinatorial domains are often heavytailed. Such heavy-tailed distributions explain the high variability observed when using backtrack-style procedures. A good understanding of this phenomenon can lead to better search techniques. For example, restart strategies provide a good mechanism for eliminating the heavy-tailed behavior and boosting the overall search performance. Several state-of-the-art SAT solvers now incorporate such restart mechanisms. The study of heavy-tailed phenomena in combinatorial search has so far been been largely based on empirical data. We introduce several abstract tree search models, and show formally how heavy-tailed cost distribution can arise in backtrack search. We also discuss how these insights may facilitate the development of better combinatorial search methods.
675385
A Theory of Average-Case Compilability in Knowledge Representation
Compilability is a fundamental property of knowledge representation formalisms which captures how succinctly information can be expressed. A l though many results concerning compilability have been obtained, they are all "worst-case" results. We develop a theory of average-case compilability which allows for the formal comparison and classification of knowledge representation formalisms "on average."
6650752
Using Content-Based and Link-Based Analysis in Building Vertical Search Engines
This paper reports our research in the Web page filtering process in specialized search engine development. We propose a machine-learning-based approach that combines Web content analysis and Web structure analysis. Instead of a bag of words, each Web page is represented by a set of content-based and link-based features, which can be used as the input for various machine learning algorithms. The proposed approach was implemented using both a feedforward/backpropagation neural network and a support vector machine. An evaluation study was conducted and showed that the proposed approaches performed better than the benchmark approaches.
14347517
A Tiered System for Serving Differentiated Content
Contemporary Web sites typically consist of front–end Web servers, application servers, and back-end information systems such as database servers. There has been limited research on how to provide overload control and service differentiation for the back-end systems. In this paper we propose an architecture called tiered service (TS) for these purposes. In TS, there are several heterogeneous back-end systems to serve the Web applications. The Web applications communicate with a routing intermediary to intelligently route the queries to the appropriate back-end servers based on various policies such as client profiles and server load. In our system the back ends may store different qualities of data; lower quality data typically requires less overhead to serve. The main contributions of this paper include (i) a tiered content replication scheme that replicates tiered qualities of data on heterogeneous back ends with different capacity to satisfy clients with diverse requirements for latency and quality of data, and (ii) an application-transparent query routing architecture that automatically routes the queries to the appropriate back ends. The architecture was implemented in our test bed, and its performance was benchmarked. The experimental results demonstrate that TS offers significant performance improvement.
14259579
FTXI: fault tolerance XCS in integer
In the realm of data mining, several key issues exists in the traditional classification algorithms, such as low readability, large rule number, and low accuracy with information losing. In this paper, we propose a new classification methodology, called fault tolerance XCS in integer (FTXI), by extending XCS to handle conditions in integers and integrating the mechanism of fault tolerance in the context of data mining into the framework of XCS. We also design and generate appropriate artificial data sets for examining and verifying the proposed method. Our experiments indicate that FTXI can provide the least rule number, obtain high prediction accuracy, and offer rule readability, compared to C4.5 and XCS in integer without fault tolerance.
8488192
Session-based overload control in QoS-aware Web servers
With the explosive use of the Internet, contemporary Web servers are susceptible to overloads and their services deteriorate drastically and often cause denial of services. In this paper, we propose two methods to prevent and control overloads in Web servers by utilizing the session-based relationship among HTTP requests. We first exploited the dependence among session-based requests by analyzing and predicting the reference patterns. Using the dependency relationships, we have derived traffic conformation functions that can be used for capacity planning and overload prevention in Web servers. Second, we have proposed a dynamic weighted fair sharing (DWFS) scheduling algorithm to control overloads in Web servers. DWFS is distinguished from other scheduling algorithms in the sense that it aims to avoid processing of requests that belong to sessions that are likely to be aborted in the near future. The experimental results demonstrate that DWFS can improve server responsiveness by as high as 50% while providing QoS support through service differentiation for a class of application environment.
16294852
Interactive volume visualization on a heterogeneous message-passing multicomputer
This paper describes VOL2, an interactive general-purpose volume renderer based on ray casting and implemented on Pixel-Planes 5, a distributed-memory, message-passing multicomputer. VOL2 is a pipelined renderer using image-space task parallelism and object-space data partitioning. We describe the parallelization and load balancing techniques used in order to achieve interactive response and near-real-time frame rates. We also present a number of applications for our system and derive some general conclusions about operation of image-order rendering algorithms on message-passing multicomputers.