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Succinctness is a natural measure for comparing the strength of different logics. Intuitively, a logic L_1 is more succinct than another logic L_2 if all properties that can be expressed in L_2 can be expressed in L_1 by formulas of (approximately) the same size, but some properties can be expressed in L_1 by (significantly) smaller formulas.
We study the succinctness of logics on linear orders. Our first theorem is concerned with the finite variable fragments of first-order logic. We prove that:
(i) Up to a polynomial factor, the 2- and the 3-variable fragments of first-order logic on linear orders have the same succinctness. (ii) The 4-variable fragment is exponentially more succinct than the 3-variable fragment. Our second main result compares the succinctness of first-order logic on linear orders with that of monadic second-order logic. We prove that the fragment of monadic second-order logic that has the same expressiveness as first-order logic on linear orders is non-elementarily more succinct than first-order logic.
FIFO is the most prominent queueing strategy due to its simplicity and the fact that it only works with local information. Its analysis within the adversarial queueing theory however has shown, that there are networks that are not stable under the FIFO protocol, even at arbitrarily low rate. On the other hand there are networks that are universally stable, i.e., they are stable under every greedy protocol at any rate r < 1. The question as to which networks are stable under the FIFO protocol arises naturally. We offer the first polynomial time algorithm for deciding FIFO stability and simple-path FIFO stability of a directed network, answering an open question posed in [1, 4]. It turns out, that there are networks, that are FIFO stable but not universally stable, hence FIFO is not a worst case protocol in this sense. Our characterization of FIFO stability is constructive and disproves an open characterization in [4].
We present a biologically-inspired system for real-time, feed-forward object recognition in cluttered scenes. Our system utilizes a vocabulary of very sparse features that are shared between and within different object models. To detect objects in a novel scene, these features are located in the image, and each detected feature votes for all objects that are consistent with its presence. Due to the sharing of features between object models our approach is more scalable to large object databases than traditional methods. To demonstrate the utility of this approach, we train our system to recognize any of 50 objects in everyday cluttered scenes with substantial occlusion. Without further optimization we also demonstrate near-perfect recognition on a standard 3-D recognition problem. Our system has an interpretation as a sparsely connected feed-forward neural network, making it a viable model for fast, feed-forward object recognition in the primate visual system.
Static analysis of different non-strict functional programming languages makes use of set constants like Top, Inf, and Bot denoting all expressions, all lists without a last Nil as tail, and all non-terminating programs, respectively. We use a set language that permits union, constructors and recursive definition of set constants with a greatest fixpoint semantics. This paper proves decidability, in particular EXPTIMEcompleteness, of subset relationship of co-inductively defined sets by using algorithms and results from tree automata. This shows decidability of the test for set inclusion, which is required by certain strictness analysis algorithms in lazy functional programming languages.
In this dissertation a non-deterministic lambda-calculus with call-by-need evaluation is treated. Call-by-need means that subexpressions are evaluated at most once and only if their value must be known to compute the overall result. Also called "sharing", this technique is inevitable for an efficient implementation. In the lambda-ND calculus of chapter 3 sharing is represented explicitely by a let-construct. Above, the calculus has function application, lambda abstractions, sequential evaluation and pick for non-deterministic choice. Non-deterministic lambda calculi play a major role as a theoretical foundation for concurrent processes or side-effected input/output. In this work, non-determinism additionally makes visible when sharing is broken. Based on the bisimulation method this work develops a notion of equality which respects sharing. Using bisimulation to establish contextual equivalence requires substitutivity within contexts, i.e., the ability to "replace equals by equals" within every program or term. This property is called congruence or precongruence if it applies to a preorder. The open similarity of chapter 4 represents a new concept, insofar that the usual definition of a bisimulation is impossible in the lambda-ND calculus. So in section 3.2 a further calculus lambda-Approx has to be defined. Section 3.3 contains the proof of the so-called Approximation Theorem which states that the evaluation in lambda-ND and lambda-Approx agrees. The foundation for the non-trivial precongruence proof is set out in chapter 2 where the trailblazing method of Howe is extended to be capable with sharing. By the use of this (extended) method, the Precongruence Theorem proves open similarity to be a precongruence, involving the so-called precongruence candidate relation. Joining with the Approximation Theorem we obtain the Main Theorem which says that open similarity of the lambda-Approx calculus is contained within the contextual preorder of the lambda-ND calculus. However, this inclusion is strict, a property whose non-trivial proof involves the notion of syntactic continuity. Finally, chapter 6 discusses possible extensions of the base calculus such as recursive bindings or case and constructors. As a fundamental study the calculus lambda-ND provides neither of these concepts, since it was intentionally designed to keep the proofs as simple as possible. Section 6.1 illustrates that the addition case and constructors could be accomplished without big hurdles. However, recursive bindings cannot be represented simply by a fixed point combinator like Y, thus further investigations are necessary.
We study queueing strategies in the adversarial queueing model. Rather than discussing individual prominent queueing strategies we tackle the issue on a general level and analyze classes of queueing strategies. We introduce the class of queueing strategies that base their preferences on knowledge of the entire graph, the path of the packet and its progress. This restriction only rules out time keeping information like a packet’s age or its current waiting time.
We show that all strategies without time stamping have exponential queue sizes, suggesting that time keeping is necessary to obtain subexponential performance bounds. We further introduce a new method to prove stability for strategies without time stamping and show how it can be used to completely characterize a large class of strategies as to their 1-stability and universal stability.
Sharing of substructures like subterms and subcontexts in terms is a common method for space-efficient representation of terms, which allows for example to represent exponentially large terms in polynomial space, or to represent terms with iterated substructures in a compact form. We present singleton tree grammars as a general formalism for the treatment of sharing in terms. Singleton tree grammars (STG) are recursion-free context-free tree grammars without alternatives for non-terminals and at most unary second-order nonterminals. STGs generalize Plandowski's singleton context free grammars to terms (trees). We show that the test, whether two different nonterminals in an STG generate the same term can be done in polynomial time, which implies that the equality test of terms with shared terms and contexts, where composition of contexts is permitted, can be done in polynomial time in the size of the representation. This will allow polynomial-time algorithms for terms exploiting sharing. We hope that this technique will lead to improved upper complexity bounds for variants of second order unification algorithms, in particular for variants of context unification and bounded second order unification.
In the last years, much effort went into the design of robust anaphor resolution algorithms. Many algorithms are based on antecedent filtering and preference strategies that are manually designed. Along a different line of research, corpus-based approaches have been investigated that employ machine-learning techniques for deriving strategies automatically. Since the knowledge-engineering effort for designing and optimizing the strategies is reduced, the latter approaches are considered particularly attractive. Since, however, the hand-coding of robust antecedent filtering strategies such as syntactic disjoint reference and agreement in person, number, and gender constitutes a once-for-all effort, the question arises whether at all they should be derived automatically. In this paper, it is investigated what might be gained by combining the best of two worlds: designing the universally valid antecedent filtering strategies manually, in a once-for-all fashion, and deriving the (potentially genre-specific) antecedent selection strategies automatically by applying machine-learning techniques. An anaphor resolution system ROSANA-ML, which follows this paradigm, is designed and implemented. Through a series of formal evaluations, it is shown that, while exhibiting additional advantages, ROSANAML reaches a performance level that compares with the performance of its manually designed ancestor ROSANA.
With ubiquitous use of digital camera devices, especially in mobile phones, privacy is no longer threatened by governments and companies only. The new technology creates a new threat by ordinary people, who now have the means to take and distribute pictures of one’s face at no risk and little cost in any situation in public and private spaces. Fast distribution via web based photo albums, online communities and web pages expose an individual’s private life to the public in unpreceeded ways. Social and legal measures are increasingly taken to deal with this problem. In practice however, they lack efficiency, as they are hard to enforce in practice. In this paper, we discuss a supportive infrastructure aiming for the distribution channel; as soon as the picture is publicly available, the exposed individual has a chance to find it and take proper action.
This paper proves correctness of Nöcker's method of strictness analysis, implemented in the Clean compiler, which is an effective way for strictness analysis in lazy functional languages based on their operational semantics. We improve upon the work of Clark, Hankin and Hunt did on the correctness of the abstract reduction rules. Our method fully considers the cycle detection rules, which are the main strength of Nöcker's strictness analysis. Our algorithm SAL is a reformulation of Nöcker's strictness analysis algorithm in a higher-order call-by-need lambda-calculus with case, constructors, letrec, and seq, extended by set constants like Top or Inf, denoting sets of expressions. It is also possible to define new set constants by recursive equations with a greatest fixpoint semantics. The operational semantics is a small-step semantics. Equality of expressions is defined by a contextual semantics that observes termination of expressions. Basically, SAL is a non-termination checker. The proof of its correctness and hence of Nöcker's strictness analysis is based mainly on an exact analysis of the lengths of normal order reduction sequences. The main measure being the number of 'essential' reductions in a normal order reduction sequence. Our tools and results provide new insights into call-by-need lambda-calculi, the role of sharing in functional programming languages, and into strictness analysis in general. The correctness result provides a foundation for Nöcker's strictness analysis in Clean, and also for its use in Haskell.