Miracle-dz/UniFAR-FTUs huggingface dataset:
Approximation and Relaxation Approaches for Parallel and Distributed Machine Learning

OF THE DISSERTATION Approximation and Relaxation Approaches for Parallel and Distributed Machine Learning by Stephen W. Tyree Doctor of Philosophy in Computer Science Washington University in St. Louis, 2014 Professor Kilian Q. Weinberger, Chair Large scale machine learning requires tradeoffs. Commonly this tradeoff has led practitioners to choose simpler, less powerful models, e.g. linear models, in order to process more training examples in a limited time. In this work, we introduce parallelism to the training of non-linear models by leveraging a different tradeoff—approximation. We demonstrate various techniques by which non-linear models can be made amenable to larger data sets and significantly more training parallelism by strategically introducing approximation in certain optimization steps. For gradient boosted regression tree ensembles, we replace precise selection of tree splits with a coarse-grained, approximate split selection, yielding both faster sequential training and a significant increase in parallelism, in the distributed setting in particular. For metric learning with nearest neighbor classification, rather than explicitly train a neighborhood structure we leverage the implicit neighborhood structure induced by task-specific random forest classifiers, yielding a highly parallel method for metric learning. For support vector machines, we follow existing work to learn a reduced basis set with extremely high parallelism, particularly on GPUs, via existing linear algebra libraries.
Loop transformations for clustered vliw architectures

With increasing demands for performance by embedded systems, especially by digital signal processing (DSP) applications, embedded processors must increase available instruction-level parallelism (ILP) within significant constraints on power consumption and chip cost. Unfortunately, supporting a large amount of ILP on a processor while maintaining a single register file increases chip cost and potentially decreases overall performance due to increased cycle time. To address this problem, some modern embedded processors partition the register file into multiple low-ported register files, each directly connected with one or more functional units. These functional unit/register file groups are called clusters. Clustered VLIW (very long instruction word) architectures need extra copy operations or delays to transfer values among clusters. To take advantage of clustered architectures, the compiler must expose parallelism for maximal functional-unit utilization, and schedule instructions to reduce intercluster communication overhead. High-level loop transformations offer an excellent opportunity to enhance the abilities of low-level optimizers to generate code for clustered architectures. This dissertation investigates the effects of three loop transformations, i.e., loop fusion, loop unrolling, and unroll-and-jam, on clustered VLIW architectures. The objective is to achieve high performance with low communication overhead. This dissertation discusses the following techniques: (1) Loop fusion. This research examines the impact of loop fusion on clustered architectures. A metric based upon communication costs for guiding loop fusion is developed and tested on DSP benchmarks. (2) Unroll-and-jam and loop unrolling. A new method that integrates a communication cost model with an integer-optimization problem is developed to determine unroll amounts for loop unrolling and unroll-and-jam automatically for a specific loop on a specific architecture. These techniques have been implemented and tested using DSP benchmarks on simulated, clustered VLIW architectures and a real clustered, embedded processor, the TI TMS320C64X. The results show that the new techniques achieve an average speedup of 1.72–1.89 on five different clustered architectures.
Shallow-Parsing Stylebook for German

The presented system provides a shallow syntactic annotation for unrestricted German text. It requires POS-annotated text and annotates the layers of chunks, topological fields and clauses. This stylebook gives an overview of the various categories annotated in those different layers. The methodology of the annotation process is mentioned in those cases where it has an impact on the annotation scheme. Example sentences are taken from real language data, but were simplified where necessary.
An Efficient Algorithm for Large-Scale Text Categorization

The text categorization is a core technique in knowle dge mining field. Most of categorization methods are based on VSM in the current research, of which the widely-used method is kNN. But most of them are highly complicated on computation, and could hardly be used for classifying large-scale sample. Moreover, to them, the classifier must be rebuilt when adding or deleting the training samples, which make them poor in scalability. In this paper, based on Mutual Dependence and Equivalent Radius, a new categorization method (called MDER) is proposed. MDER can be used to classify large-scale sample and has good scalability. After a series of experiments of classifying Chinese texts, the conclusion are drawn that MDER outperforms kNN and CCC method, and can be used online to classify large-scale sample while keeping higher precision and recall.
An implementation of automatic transcription of monophonic music with a Blackboard system

A system is proposed for the automatic transcription of monophonic music. It consists of two main parts: the front end, using a segmentation system that detects the note onsets and offsets present in a musical track and performs the time-frequency analysis of the signal; and a blackboard system, that processes this data and obtains the pitch of each note working through an hypotheses hierarchy. Emphasis is given on the explanation of the latter, and satisfactory results are shown within a limited database of real-world sound samples.
The Use of Analogies in Human Tutoring Dialogues

This paper discusses the use of analogies in human tutoring dialogues. Our long-term goal is to implement analogies in the CIRCSIM-Tutor system, an intelligent tutoring system that carries on a natural language dialogue with the student. We need to analyze human tutoring strategies that make use of analogies and the language that supports these strategies, so that our system can propose analogies to students and follow them up appropriately. The system needs to be capable of recognizing student misunderstandings and remedying them. All this will require the use of a computational model of analogy, which may eventually allow our system to recognize analogies proposed by students as well.
Comparison of multi-fluid moment models with Particle-in-Cell simulations of collisionless magnetic reconnection

We introduce an extensible multi-fluid moment model in the context of collisionless magnetic reconnection. This model evolves full Maxwell equations, and simultaneously moments of the Vlasov-Maxwell equation for each species in the plasma. Effects like electron inertia and pressure gradient are self-consistently embedded in the resulting multi-fluid moment equations, without the need to explicitly solving a generalized Ohms's law. Two limits of the multi-fluid moment model are discussed, namely, the five-moment limit that evolves a scalar pressures for each species, and the ten-moment limit that evolves the full anisotropic, non-gyrotropic pressure tensor for each species. We first demonstrate, analytically and numerically, that the five-moment model reduces to the widely used Hall Magnetohydrodynamics (Hall MHD) model under the assumptions of vanishing electron inertia, infinite speed of light, and quasi-neutrality. Then, we compare ten-moment and fully kinetic Particle-In-Cell (PIC) simulations of a large scale Harris sheet reconnection problem, where the ten-moment equations are closed with a local linear collisionless approximation for the heat flux. The ten-moment simulation gives reasonable agreement with the PIC results regarding the structures and magnitudes of the electron flows, the polarities and magnitudes of elements of the electron pressure tensor, and the decomposition of the generalized Ohm's law. Possible ways to improve the simple local closure towards a nonlocal fully three-dimensional closure are also discussed.
Ergonomics of using a mouse or other non-keyboard input device

Findings from a two-year study investigating health problems associated with use of non-keyboard input devices (NKID) are presented. The research used a combination of methods to determine the extent to which different NKID are currently in use, how they are used and problems that result. Evidence was collected through a literature review; questionnaire survey of 128 IT and health and safety managers; workplace assessments involving interviews and observation with 45 users across 9 different companies; a questionnaire survey of 848 users (3500 questionnaires issued, 24% response rate); and laboratory work including an expert assessment of different devices, a laboratory trial comparing traditional and L-shaped desks with three different arm support conditions, and a case study investigating touch screen use. This report and the work it describes were funded by the Health and Safety Executive (HSE). Its contents, including any opinions and/or conclusions expressed, are those of the authors alone and do not necessarily reflect HSE policy. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means (electronic, mechanical, photocopying, recording or otherwise) without the prior written permission of the copyright owner. iii SUMMARY What were the aims of the study? The aims of the study were to: 1. Determine the extent to which different non-keyboard input devices (NKID) are used 2. Document patterns of NKID use i.e. tasks and proportion of time for which they are used 3. Describe the range of workstation configurations occurring in practice 4. Identify the extent of individual variation among NKID users in their manner of device operation 5. Measure prevalence of musculoskeletal and other complaints associated with NKID use 6. Examine differences in user behaviour when operating NKID that may have resulted from prior musculoskeletal problems 7. Identify desirable and undesirable aspects of NKID in respect of user comfort and health 8. Collate and validate best practice advice concerning use of NKID 9. Provide guidance, where feasible, on the suitability of different NKID for generic tasks (e.g. word processing, CAD) How was the study carried out? · Through a review of the literature relevant to the health of NKID users (Stage 1: Literature review) · Through a questionnaire survey of over 100 health and safety and information technology (IT) managers (Stage 2: Manager questionnaire survey) · By undertaking ergonomics work system assessments at nine locations, with 45 NKID users …
Automatic acquisition of Spanish LFG resources from the Cast3LB treebank

In this paper, we describe the automatic annotation of the Cast3LB Treebank with LFG f-structures for the subsequent extraction of Spanish probabilistic grammar and lexical resources. We adapt the approach and methodology of Cahill et al. (2004), O’Donovan et al. (2004) and elsewhere for English to Spanish and the Cast3LB treebank encoding. We report on the quality and coverage of the automatic f-structure annotation. Following the pipeline and integrated models of Cahill et al. (2004), we extract wide-coverage probabilistic LFG approximations and parse unseen Spanish text into f-structures. We also extend Bikel’s (2002) Multilingual Parse Engine to include a Spanish language module. Using the retrained Bikel parser in the pipeline model gives the best results against a manually constructed gold standard (73.20% predsonly f-score). We also extract Spanish lexical resources: 4090 semantic form types with 98 frame types. Subcategorised prepositions and particles are included in the frames.
Investigation of the Painting Idyll Attributed to Henryk Siemiradzki: The Unusual Technology of a Canvas Painting Executed on an Enlarged Photograph

ABSTRACT The subject of the research is an oil painting entitled Idyll created using an unusual technique. The painting layer was applied on canvas covered with photosensitive medium on which a photograph was developed. The results of the examination of Idyll in the context of its attribution to Henryk Siemiradzki (1843–1902) are discussed. Its atypical technology and the possibility of the artist having used the photographic technique are also considered. X-ray fluorescence spectroscopy, infrared spectroscopy, and scanning electron microscopy were performed to establish the technique and to characterize the pigments and materials used in the painting. The identified pigments and the information provided by analytical photography (UV, X-ray images) were compared with the results of the detailed examination of 56 of Siemiradzki’s oil paintings. Performed analyses revealed that the majority of the features identified in Idyll point to Henryk Siemiradski’s technique.
On the Feasibility of Large-Scale Wireless Sensor Networks

Construction of lattice codes for the problem of rate/distortion with side information—solves an open problem of Zamir and Shamai. Proof of asymptotic optimality—first codes ever shown to come arbitrarily close to Wyner's rate/distortion bound. Proof that arbitrarily accurate estimation is possible in large wireless networks—contradicts a folk theorem: " large networks are bad " .
Machine Learning in the Area of Image Analysis and Pattern Recognition

Introduction This project investigates the use of machine learning for image analysis and pattern recognition. Examples are shown using such a system in image content analysis and in making diagnoses and prognoses in the field of healthcare. Given a data set of images with known classifications, a system can predict the classification of new images. As an example, in the field of healthcare, given a data set of fine needle aspirate (FNA) images of breast masses that are each classified as benign or malignant, a new FNA of a breast mass can be classified as benign or malignant. There are at least two parts to any such system. The first part is an algorithm for creating a feature vector (also known as a data point) given an image. A feature vector consists of several numbers that are measured or calculated from the image. These features are then used by the second part of the system, a machine learning algorithm, to classify unknown feature vectors given a large database of feature vectors whose classifications are known. These two parts of such a system are not entirely independent – that is the design of the machine learning algorithm may benefit by knowing how the features are extracted from the image, and the feature extracting may be more successful if the type of machine learning algorithm to be used is known. However, in order to limit the scope of this project, only the second part of such a system is explored. That is, this project focuses on developing a system that uses machine learning to classify unknown images given a database of images and classifications, all of which have already been broken down into feature vectors by an image processing algorithm. a form of K-Nearest-Neighbors. The advantages of this type of algorithm are its transparency, quick training time, and the simplicity of outside parameters that must be adjusted for each data set. Furthermore, other researchers have had good results of classifying images with this algorithm, so this type of algorithm seemed like a good choice. The algorithm implemented in this project is a variant of the standard K-Nearest-Neighbor algorithm. To classify an unknown data point, K-Nearest Neighbor finds the k closest points in the set of training data. The definition of closest is discussed below. Of the k closest points, the algorithm returns the majority classification as the predicted classification of the unknown …
Automatic Transfer Function Design for Volumetric Data Visualization using Clustering on LH Space

Binh P. Nguyen Wei-Liang Tay Chee-Kong Chui Sim-Heng OngAbstract A major diculty in volumetric data ren-dering is nding good transfer functions to display theregions of interest within a volume. We introduce amethod that automatically detects boundaries, improvesthe segmentation of each boundary, and nally gener-ates a transfer function that minimizes occlusion of theboundaries. This method applies mean shift clusteringon LH space, and then generates polygons which ap-proximate the resulting clusters on the LH histogram.Each polygon represents a boundary surface of the vol-ume and can be easily modi ed to obtain the desired vi-sualization. A post-processing step using region growingfurther improves the segmentation result. The transferfunction is generated automatically based on the sizeand location of the boundaries to minimize occlusions.The e ectiveness of the proposed method is demon-strated in our experiments.Keywords Transfer function design Volume render-ing LH histogram Mean-shift clustering1 IntroductionDirect volume rendering is a powerful technique in sci-enti c visualization, especially in diagnostic imagingwhere images are volumetric data generated by CT andMR scanners. Volume rendering is a method that couldovercome the lack of spatial perception in the tradi-tional 2D slice-by-slice viewing. However, the eciency
CLASS-E - NEW CLASS OF HIGH-EFFICIENCY TUNED SINGLE-ENDED SWITCHING POWER AMPLIFIERS

The new class of amplifiers described is based on a load network synthesized to have a transient response which maximizes power efficiency even if the active device switching times are substantial fractions of the a.c. cycle. The new class of amplifiers, named `Class E,' is defined and is illustrated by a detailed description and a set of design equations for one simple member of the class. For that circuit the authors measured 96 percent transistor efficiency at 3.9 MHz at 26-W output from a pair of Motorola 2N3735 TO-5 transistors. Advantages of Class E are unusually high efficiency, a priori designability, large reduction in second-breakdown stress, low sensitivity to active-device characteristics, and potential for high-efficiency operation at higher frequencies than previously published Class-D circuits.
Dynamic characterization of a large Web graph

The Web is characterized by an extremely dynamic nature, as it is proved by the rapid and significant growth it has experimented in the last decade and by its continuous evolution through creation or deletion of pages and hyperlinks. Consequently, analyzing the temporal evolution of the Web has become a crucial task that can provide search engines with valuable information for refining crawling policies, improving ranking models or detecting spam. Understanding how the Web evolves over time is a delicate challenge that requires to integrate theoretical efforts of modelization and empirical results. Obtaining such findings is very expensive in terms of bandwidth, computation time and human intervention. Robust software is required to gather the data and provide easy access to the collected information. Apart for commercial engines, there have been only a few attempts to perform such task and to make the data available. Several previous works (e.g.,~\cite{ntoulas2004what,toyoda2006what}) analyzed a sequence of crawls, studying degree and frequency of change both in the content of Web pages and in the hyperlink structure to propose measures of their novelty. In this paper we study a temporal dataset~\cite{BSVLTAG} that has recently been made public. It is made of twelve 100M pages snapshots of the \texttt{. uk} domain. The Web graphs of the single snapshots have been merged into a global graph with labels that provide constant time access to temporal information. ~\cite{bordino2008temporal} describes the work done to assess the data and to study some aspects of its evolution at the level of Web pages. We now analyze the structure of this huge time-aware graph at the level of interconnection between hosts. We study the \emph{hostgraph}, i.e., the graph in which every node corresponds to a site, whereas a directed edge represents the existence of hyperlinks between pages belonging to two different hosts. Understanding the graph structure of the Web at this macroscopic level can provide valuable insights for improving Web site accessibility and navigation, or discovering related hosts. The notion of hostgraph was proposed by~\cite{bharat2001who}. A few studies analyzed hostgraphs (~\cite{baeza2005spain,liu2005china,toyoda2008thai}). ~\cite{baeza2007domain} presents a comparison among the results of twelve characterization studies of several national domains.
Synchronous Bandwidth Allocation for Time-Critical Communication

There is increasing use of distributed computer systems to support real-time applications. The key to successfully developing such systems is to have a communication network which supports the timely delivery of inter-task messages. The main focus of this research is to address some important issues related to guarantees of message deadlines in a communication network. Our effort has concentrated on the timed token ring networks, such as FDDI, where the timed token medium access control (MAC) protocol is employed. Specifically, we studied the problem of guaranteeing synchronous message deadlines by appropriate allocation of the synchronous bandwidths. Synchronous bandwidth, defined as the maximum time for which a node can transmit its synchronous messages every time it receives the token, is a key parameter in the control of synchronous message transmission. To ensure the transmission of synchronous messages before their deadlines, synchronous bandwidths must be properly allocated to individual nodes. In this study, we further examined the timing properties of the timed token protocol, which is essential for development of analysis of various synchronous bandwidth allocation (SBA) schemes. As a result, we extended the previous work on the bounded elapse time between any given number of successive token’s arrivals to a particular node. A tighter upper bound on the elapse time was derived. Based upon this result, a more exact expression of Xi (the minimum amount of time available for node i to transmit its synchronous messages during Di , the message (relative) deadline), necessary for testing whether synchronous message deadlines can be guaranteed by a given allocation of synchronous bandwidths, was derived. Schedulability tests that determine whether the time constraints of messages will be met were addressed. While the restriction of the minimum message deadline (D min) being no less than twice the target token rotation time (TTRT), has been generally accepted as a necessary condition for any synchronous message set to be guaranteed, our study shows that this is not always true. As a result, we first suggest a relaxation of this restriction to D min > TTRT to prevent a schedulable message set from being simply deemed as unschedulable. Two main SBA schemes, the local scheme ELA and the global optimal scheme EMCA, were developed in this research. Either of them performs best among existing/known SBA schemes of its type, in terms of the capability for guaranteeing synchronous messages with periods equal to deadlines. The proposed SBA schemes also differ significantly from previously reported SBA schemes by explicitly taking into account the synchronous bandwidth allocation for the message sets with D min < 2.TTRT and consequently can apply to any synchronous message sets (with D min > TTRT). The work presented in this thesis is compatible with the FDDI and SAFENET standards and therefore can be applied by engineers building real-time systems using these standards.