No Atom Rendered Void: The Aerial and Alchemical Enchantment of Wuthering Heights

Anat Rosenberg, “Liberal Anguish: Wuthering Heights and the Structures of Liberal Thought” (pp. 1–25) After decades of sustained academic critiques along established lines, liberalism has recently attracted renewed evaluations. These readings treat complexity as inherent in liberalism, and proceed to explore its structures beyond suspicious hermeneutics. This essay argues that Emily Brontë’s Wuthering Heights (1847) constitutes an early and sophisticated argument about the structures of complexity in liberalism. Not only does Brontë’s novel merit entry into the discussion as a conceptual contribution, but it also offers an aesthetic enactment of the anguish that liberal structures of complexity were to evoke for generations to follow, an anguish experienced already at its troubled reception.

Dynamic and pointer-based data structures are widely used in symbolic or irregular C codes. However there is still a lack of compiler techniques to deal with the automatic optimization of such codes. In this paper we take a first step towards this final objective: the automatic identification of the data structure used in the code. More precisely, we describe the framework and the compiler we have implemented to capture complex data structures generated, traversed, and modified in C codes. Our method assigns a reduced set of reference shape graphs (RSRSG) to each sentence to approximate the shape of the data structure after the execution of such a sentence. With the properties and operations that define the behavior of our RSRSG, the method can accurately detect complex recursive data structures. The compiler makes a progressive analysis in which the level of detail is increased during the analysis when needed. Several experiments are carried out with complex data structures to validate the capabilities of our compiler.

In this paper, we focus on the task of generating compact binary templates for face image sets. Existing set-based templates are extracted from a high-dimensional real-value feature space, and sometimes with complex structure. The process is not very efficient for large-scale applications. Existing binary templates are generated via either a sequence or a tree of projections. The recursive tree structure achieves higher recognition performance, but the number of projections increases exponentially with the binary code length. Thus, we propose a recursive binary embedding algorithm exhibiting an increased recognition power while restricting the number of projections to increase linearly with the code length. Moreover, the proposed embedding can be easily plugged into the modern deep learning architectures for set-based face recognition. Experimental results using the challenge IJB-A dataset illustrate the effectiveness and efficiency of our proposed template for face verification, closed set identification, and open set identification.

Automatic parallelization of codes which use dynamic data structures is still a challenge. One of the first steps in such parallelization is the automatic detection of the dynamic data structure used in the code. In this paper we describe the framework and the compiler we have implemented to capture complex data structures generated, traversed, and modified in C codes. Our method assigns a Reduced Set of Reference Shape Graphs (RSRSG) to each sentence to approximate the shape of the data structure after the execution of such a sentence. With the properties and operations that define the behavior of our RSRSG, the method can accurately detect complex recursive data structures such as a doubly linked list of pointers to trees where the leaves point to additional lists. Other experiments are carried out with real codes to validate the capabilities of our compiler.

Multiple semantic processes at different levels of syntactic hierarchy: Does the higher-level process proceed in face of a lower-level failure?

Recursive compositional models (RCMs) are hierarchical models which enable us to represent the shape/geometry and visual appearance of objects and images at different scales. The key design principle is recursive compositionality. Objects are represented by RCMs in a hierarchical form where complex structures are composed of more elementary structures. Formally, they are represented by probability distributions defined over graphs with variable topology. Learning techniques are used to learn these models from a limited number of examples of the object by exploiting the recursive structure (some of our papers use supervised learning while others are unsupervised and induce the object structure). In addition, we can exploit this structure to develop algorithms that can perform inference on these RCMs to rapidly detect and recognize objects. This differs from more standard “flat models” of objects which have much less representational power if they wish to maintain efficient learning and inference. The basic properties of an RCM are illustrated in figures (1, 2). Because RCMs give a rich hierarchical description of objects and images they can be applied to a range of tasks including object detection, segmentation, parsing and image parsing. In all cases, we achieved state of the art results when evaluated on datasets with groundtruth.

Dependence information between program values is extensively used in many program optimization techniques. The ability to identify statements, calls and loop iterations that do not depend on each other enables many transformations which increase the instruction and thread-level parallelism in a program. When program variables contain complex data structures including arrays, records, and recursive data structures, the ability to precisely model data dependence based on heap structure remains a challenging problem. This paper presents a technique for precisely tracking heap based data dependence in non-trivial Java programs via static analysis. Using an abstract interpretation framework, the approach extends a shape analysis technique based on an existing graph model of heaps, by integrating read/write history information and intelligent memoization. The method has been implemented and its effectiveness and utility are demonstrated by computing detailed dependence information for two benchmarks (Em3d and BH from the JOlden suite) and using this information to parallelize the benchmarks.

Linear type systems permit programmers to deallocate or explicitly recycle memory, but are severely restricted by the fact that they admit no aliasing. This paper describes a pseudo-linear type system that allows a degree of aliasing and memory reuse as well as the ability to define complex recursive data structures. Our type system can encode conventional linear data structures such as linear lists and trees as well as more sophisticated data structures including cyclic and doubly-linked lists and trees. In the latter cases, our type system is expressive enough to represent pointer aliasing and yet safely permit destructive operations such as object deallocation.We demonstrate the flexibility of our type system by encoding two common space-conscious algorithms: destination-passing style and Deutsch-Schorr-Waite or “link-reversal” traversal algorithms.KeywordsType SystemOperational SemanticMemory ManagementMemory BlockMemory ObjectThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

A method for reducing sidelobes in processing echoes received in phase-coded pulse radars is proposed. A recursive stable time-variant filter structure is derived which approximates an inverse code filter according to a least-squares optimality criterion. The application to the case of phase coding with binary Barker sequences is examined in detail. Performance of less complex but suboptimal filter structures are also evaluated.

This paper presents novel designs of multi-output sinusoidal oscillators derived from recursive digital filter structures. Two methods to design a complex digital oscillator were developed. In the first approach we obtain the output signals as a result of using in the oscillator algorithm the desired rotation matrix elements, while in the second approach the recipe is opposite: based on the desired amplitudes and phases of sinusoidal signals we obtain the rotation matrix elements. The common feature of these two strategies is the rotation matrix ability to unify various complex oscillator structures. Detailed analysis of the complex oscillators yielded to design multi-output sinusoidal oscillators with waveforms of specified amplitudes and phases. The three-phase oscillator proposed here can be implemented with the aid of four multipliers having two different coefficient values, three adders, and three delay elements.

To successfully exploit all the possibilities of current computer/multicomputer architectures, optimization compiling techniques are a must. However, for codes based on pointers and dynamic data structures, these optimization techniques have to be necessarily carried out after identifying the characteristics and properties of the data structure used in the code. We describe the framework and the analyzer we have implemented to capture complex data structures generated, traversed, and modified in codes based on pointers. Our method assigns a reduced set of reference shape graph (RSRSG) to each statement to approximate the shape of the data structure after the execution of such a statement. With the properties and operations that define the behavior of our RSRSG, the method can accurately detect complex recursive data structures such as a doubly linked list of pointers to trees where the leaves point to additional lists. Several experiments are carried out with real codes to validate the capabilities of our analyzer.

The first part of the paper shows that previous theoretical work on the semantics of probabilistic programs (Kozen) and on the correctness of performance annotated programs (Ramshaw) can be used to automate the average-case analysis of simple programs containing assignments, conditionals, and loops. A performance compiler has been developed using this theoretical foundation. The compiler is described, and it is shown that special cases of symbolic simplifications of formulas play a major role in rendering the system usable. The performance compiler generates a system of recurrence equations derived from a given program whose efficiency one wishes to analyze. This generation is always possible, but the problem of solving the resulting equations may be complex. The second part of the paper presents an original method that generalizes the previous approach and is applicable to functional programs that make use of recursion and complex data structures. Several examples are presented, including an analysis of binary tree sort. A key feature of the analysis of such programs is that distributions on complex data structures are represented using attributed probabilistic grammars.

A method for reducing sidelobes in processing echoes received in phase-coded pulse radars is proposed. A recursive stable time-variant filter structure is derived which approximates an inverse code filter according to a least-squares optimality criterion. The application to the case of phase coding with binary Barker sequences is examined in detail. Performance of less complex but suboptimal filter structures are also evaluated.

5 - Advanced Data Structures

Full and double reduplication are found in Nez Perce (nimipuutímt), a Sahaptian language spoken in Idaho, Washington, and Oregon. Full reduplication is characteristic of many nouns and adjectives, while double reduplication occurs when fully-reduplicated forms are subject to an additional reduplicative process, a Ci- prefix indicating plural. This paper describes the quantity-sensitive primary stress pattern of fully- and doubly-reduplicated adjectives, demonstrating a systematic departure from the usual pattern of quantity-insensitive penultimate stress in Nez Perce. It then use patterns of vowel length and plural exponence to show that fully-reduplicated adjectives exhibit a bimoraic stem minimum (though fully-reduplicated nouns do not), and argues that these facts can be understood as a manifestation of a complex recursive prosodic word structure where each stem is its own prosodic word and the Ci- prefix is adjoined as an affixal clitic.