16 Search Results for "Franco, Juliana"


Volume

OASIcs, Volume 60

2017 Imperial College Computing Student Workshop (ICCSW 2017)

ICCSW 2017, September 26-27, 2017, London, UK

Editors: Fergus Leahy and Juliana Franco

Document
Artifact
Implementation of SHAPES Case Studies (Artifact)

Authors: Alexandros Tasos, Juliana Franco, Sophia Drossopoulou, Tobias Wrigstad, and Susan Eisenbach

Published in: DARTS, Volume 6, Issue 2, Special Issue of the 34th European Conference on Object-Oriented Programming (ECOOP 2020)


Abstract
Our main paper presents {SHAPES}, a language extension which offers developers fine-grained control over the placement of data in memory, whilst retaining both memory safety and object abstraction via pooling and clustering. As part of the development of {SHAPES}, we wanted to investigate the usefulness of the concepts {SHAPES} brings to the table. To that extent, we implemented five such case studies. This publication provides the corresponding code and instructions on how to run these case studies and derive the results we provide.

Cite as

Alexandros Tasos, Juliana Franco, Sophia Drossopoulou, Tobias Wrigstad, and Susan Eisenbach. Implementation of SHAPES Case Studies (Artifact). In Special Issue of the 34th European Conference on Object-Oriented Programming (ECOOP 2020). Dagstuhl Artifacts Series (DARTS), Volume 6, Issue 2, pp. 19:1-19:3, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2020)


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@Article{tasos_et_al:DARTS.6.2.19,
  author =	{Tasos, Alexandros and Franco, Juliana and Drossopoulou, Sophia and Wrigstad, Tobias and Eisenbach, Susan},
  title =	{{Implementation of SHAPES Case Studies (Artifact)}},
  pages =	{19:1--19:3},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2020},
  volume =	{6},
  number =	{2},
  editor =	{Tasos, Alexandros and Franco, Juliana and Drossopoulou, Sophia and Wrigstad, Tobias and Eisenbach, Susan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DARTS.6.2.19},
  URN =		{urn:nbn:de:0030-drops-132167},
  doi =		{10.4230/DARTS.6.2.19},
  annote =	{Keywords: Cache utilisation, Data representation, Memory safety}
}
Document
SCICO Journal-first
Reshape Your Layouts, Not Your Programs: A Safe Language Extension for Better Cache Locality (SCICO Journal-first)

Authors: Alexandros Tasos, Juliana Franco, Sophia Drossopoulou, Tobias Wrigstad, and Susan Eisenbach

Published in: LIPIcs, Volume 166, 34th European Conference on Object-Oriented Programming (ECOOP 2020)


Abstract
The vast gap between CPU and RAM speed means that on modern architectures, developers need to carefully consider data placement in memory to exploit spatial and temporal cache locality and use CPU caches effectively. To that extent, developers have devised various strategies regarding data placement; for objects that should be close in memory, a contiguous pool of objects is allocated and then new instances are constructed inside it; an array of objects is clustered into multiple arrays, each holding the values of a specific field of the objects. Such data placements, however, have to be performed manually, hence readability, maintainability, memory safety, and key OO concepts such as encapsulation and object identity need to be sacrificed and the business logic needs to be modified accordingly. We propose a language extension, SHAPES, which aims to offer developers high-level fine-grained control over data placement, whilst retaining memory safety and the look-and-feel of OO. SHAPES extends an OO language with the concepts of pools and layouts: Developers declare pools that contain objects of a specific type and specify the pool’s layout. A layout specifies how objects in a pool are laid out in memory. That is, it dictates how the values of the fields of the pool’s objects are grouped together into clusters. Objects stored in pools behave identically to ordinary, standalone objects; the type system allows the code to be oblivious to the layout being used. This means that the business logic is completely decoupled from any placement concerns and the developer need not deviate from the spirit of OO to better utilise the cache. In this paper, we present the features of SHAPES, as well as the design rationale behind each feature. We then showcase the merit of SHAPES through a sequence of case studies; we claim that, compared to the manual pooling and clustering of objects, we can observe improvement in readability and maintainability, and comparable (i.e., on par or better) performance. We also present SHAPES^h, an OO calculus which models the SHAPES ideas, we formalise the type system, and prove soundness. The SHAPES^h type system uses ideas from Ownership Types [Clarke et al., 2013] and Java Generics [Gosling et al., 2014]: In SHAPES^h, pools are part of the types; SHAPES^h class and type definitions are enriched with pool parameters. Moreover, class pool parameters are enriched with bounds, which is what allows the business logic of SHAPES to be oblivious to the layout being used. SHAPES^h types also enforce pool uniformity and homogeneity. A pool is uniform if it contains objects of the same class only; a pool is homogeneous if the corresponding fields of all its objects point to objects in the same pool. These properties allow for more efficient implementation. For performance considerations, we also designed SHAPES^l, an untyped, unsafe low-level language with no explicit support for objects or pools. We argue that it is possible to translate SHAPES^l into existing low-level intermediate representations, such as LLVM [Lattner and Adve, 2004], present the translation of SHAPES^h into SHAPES^l, and show its soundness. Thus, we expect SHAPES to offer developers more fine-grained control over data placement, without sacrificing memory safety or the OO look-and-feel.

Cite as

Alexandros Tasos, Juliana Franco, Sophia Drossopoulou, Tobias Wrigstad, and Susan Eisenbach. Reshape Your Layouts, Not Your Programs: A Safe Language Extension for Better Cache Locality (SCICO Journal-first). In 34th European Conference on Object-Oriented Programming (ECOOP 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 166, pp. 31:1-31:3, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2020)


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@InProceedings{tasos_et_al:LIPIcs.ECOOP.2020.31,
  author =	{Tasos, Alexandros and Franco, Juliana and Drossopoulou, Sophia and Wrigstad, Tobias and Eisenbach, Susan},
  title =	{{Reshape Your Layouts, Not Your Programs: A Safe Language Extension for Better Cache Locality}},
  booktitle =	{34th European Conference on Object-Oriented Programming (ECOOP 2020)},
  pages =	{31:1--31:3},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-154-2},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{166},
  editor =	{Hirschfeld, Robert and Pape, Tobias},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2020.31},
  URN =		{urn:nbn:de:0030-drops-131887},
  doi =		{10.4230/LIPIcs.ECOOP.2020.31},
  annote =	{Keywords: Cache utilisation, Data representation, Memory safety}
}
Document
DynaSOAr: A Parallel Memory Allocator for Object-Oriented Programming on GPUs with Efficient Memory Access

Authors: Matthias Springer and Hidehiko Masuhara

Published in: LIPIcs, Volume 134, 33rd European Conference on Object-Oriented Programming (ECOOP 2019)


Abstract
Object-oriented programming has long been regarded as too inefficient for SIMD high-performance computing, despite the fact that many important HPC applications have an inherent object structure. On SIMD accelerators, including GPUs, this is mainly due to performance problems with memory allocation and memory access: There are a few libraries that support parallel memory allocation directly on accelerator devices, but all of them suffer from uncoalesed memory accesses. We discovered a broad class of object-oriented programs with many important real-world applications that can be implemented efficiently on massively parallel SIMD accelerators. We call this class Single-Method Multiple-Objects (SMMO), because parallelism is expressed by running a method on all objects of a type. To make fast GPU programming available to domain experts who are less experienced in GPU programming, we developed DynaSOAr, a CUDA framework for SMMO applications. DynaSOAr consists of (1) a fully-parallel, lock-free, dynamic memory allocator, (2) a data layout DSL and (3) an efficient, parallel do-all operation. DynaSOAr achieves performance superior to state-of-the-art GPU memory allocators by controlling both memory allocation and memory access. DynaSOAr improves the usage of allocated memory with a Structure of Arrays (SOA) data layout and achieves low memory fragmentation through efficient management of free and allocated memory blocks with lock-free, hierarchical bitmaps. Contrary to other allocators, our design is heavily based on atomic operations, trading raw (de)allocation performance for better overall application performance. In our benchmarks, DynaSOAr achieves a speedup of application code of up to 3x over state-of-the-art allocators. Moreover, DynaSOAr manages heap memory more efficiently than other allocators, allowing programmers to run up to 2x larger problem sizes with the same amount of memory.

Cite as

Matthias Springer and Hidehiko Masuhara. DynaSOAr: A Parallel Memory Allocator for Object-Oriented Programming on GPUs with Efficient Memory Access. In 33rd European Conference on Object-Oriented Programming (ECOOP 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 134, pp. 17:1-17:37, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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@InProceedings{springer_et_al:LIPIcs.ECOOP.2019.17,
  author =	{Springer, Matthias and Masuhara, Hidehiko},
  title =	{{DynaSOAr: A Parallel Memory Allocator for Object-Oriented Programming on GPUs with Efficient Memory Access}},
  booktitle =	{33rd European Conference on Object-Oriented Programming (ECOOP 2019)},
  pages =	{17:1--17:37},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-111-5},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{134},
  editor =	{Donaldson, Alastair F.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2019.17},
  URN =		{urn:nbn:de:0030-drops-108098},
  doi =		{10.4230/LIPIcs.ECOOP.2019.17},
  annote =	{Keywords: CUDA, Data Layout, Dynamic Memory Allocation, GPUs, Object-oriented Programming, SIMD, Single-Instruction Multiple-Objects, Structure of Arrays}
}
Document
Complete Volume
OASIcs, Volume 60, ICCSW'17, Complete Volume

Authors: Fergus Leahy and Juliana Franco

Published in: OASIcs, Volume 60, 2017 Imperial College Computing Student Workshop (ICCSW 2017)


Abstract
OASIcs, Volume 60, ICCSW'17, Complete Volume

Cite as

Fergus Leahy and Juliana Franco. OASIcs, Volume 60, ICCSW'17, Complete Volume. In 2017 Imperial College Computing Student Workshop (ICCSW 2017). Open Access Series in Informatics (OASIcs), Volume 60, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)


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@Proceedings{leahy_et_al:OASIcs.ICCSW.2017,
  title =	{{OASIcs, Volume 60, ICCSW'17, Complete Volume}},
  booktitle =	{2017 Imperial College Computing Student Workshop (ICCSW 2017)},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-059-0},
  ISSN =	{2190-6807},
  year =	{2018},
  volume =	{60},
  editor =	{Leahy, Fergus and Franco, Juliana},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2017},
  URN =		{urn:nbn:de:0030-drops-85425},
  doi =		{10.4230/OASIcs.ICCSW.2017},
  annote =	{Keywords: Concurrent Programming, Design Tools and Techniques, Performance measures, Software Architectures, Language Constructs and Features}
}
Document
Front Matter
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Fergus Leahy and Juliana Franco

Published in: OASIcs, Volume 60, 2017 Imperial College Computing Student Workshop (ICCSW 2017)


Abstract
Front Matter, Table of Contents, Preface, Conference Organization

Cite as

Fergus Leahy and Juliana Franco. Front Matter, Table of Contents, Preface, Conference Organization. In 2017 Imperial College Computing Student Workshop (ICCSW 2017). Open Access Series in Informatics (OASIcs), Volume 60, pp. 0:i-0:xii, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)


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@InProceedings{leahy_et_al:OASIcs.ICCSW.2017.0,
  author =	{Leahy, Fergus and Franco, Juliana},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{2017 Imperial College Computing Student Workshop (ICCSW 2017)},
  pages =	{0:i--0:xii},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-059-0},
  ISSN =	{2190-6807},
  year =	{2018},
  volume =	{60},
  editor =	{Leahy, Fergus and Franco, Juliana},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2017.0},
  URN =		{urn:nbn:de:0030-drops-84421},
  doi =		{10.4230/OASIcs.ICCSW.2017.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization, External Reviewers}
}
Document
How to Write a Great Research Paper

Authors: Simon Peyton Jones

Published in: OASIcs, Volume 60, 2017 Imperial College Computing Student Workshop (ICCSW 2017)


Abstract
Writing papers is a core research skill for any researcher, but they aren't easy. Writing is not just a way to report on great research; it's a way to do great research. Yet many papers are so badly written that, even if they describe excellent work, the work has much less impact than it should. In this talk I'll give you seven simple, actionable guidelines that will, I hope, help you to write better papers, and have more fun at the same time. I don’t have all the answers—far from it—and I hope that the presentation will evolve into a discussion in which you share your own insights, rather than a lecture.

Cite as

Simon Peyton Jones. How to Write a Great Research Paper. In 2017 Imperial College Computing Student Workshop (ICCSW 2017). Open Access Series in Informatics (OASIcs), Volume 60, p. 1:1, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)


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@InProceedings{peytonjones:OASIcs.ICCSW.2017.1,
  author =	{Peyton Jones, Simon},
  title =	{{How to Write a Great Research Paper}},
  booktitle =	{2017 Imperial College Computing Student Workshop (ICCSW 2017)},
  pages =	{1:1--1:1},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-059-0},
  ISSN =	{2190-6807},
  year =	{2018},
  volume =	{60},
  editor =	{Leahy, Fergus and Franco, Juliana},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2017.1},
  URN =		{urn:nbn:de:0030-drops-84436},
  doi =		{10.4230/OASIcs.ICCSW.2017.1},
  annote =	{Keywords: Academia, Research, Writing}
}
Document
Optimizing the Unoptimizable: A Whirlwind Tour of JavaScript

Authors: Leszek Swirski

Published in: OASIcs, Volume 60, 2017 Imperial College Computing Student Workshop (ICCSW 2017)


Abstract
A whirlwind tour through the history and state-of-the-art of JavaScript execution and optimization, with a focus on the V8 engine used by Chrome and Node.js, and how a 10-day prototype became one of the most important programming languages in the world.

Cite as

Leszek Swirski. Optimizing the Unoptimizable: A Whirlwind Tour of JavaScript. In 2017 Imperial College Computing Student Workshop (ICCSW 2017). Open Access Series in Informatics (OASIcs), Volume 60, p. 2:1, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)


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@InProceedings{swirski:OASIcs.ICCSW.2017.2,
  author =	{Swirski, Leszek},
  title =	{{Optimizing the Unoptimizable: A Whirlwind Tour of JavaScript}},
  booktitle =	{2017 Imperial College Computing Student Workshop (ICCSW 2017)},
  pages =	{2:1--2:1},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-059-0},
  ISSN =	{2190-6807},
  year =	{2018},
  volume =	{60},
  editor =	{Leahy, Fergus and Franco, Juliana},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2017.2},
  URN =		{urn:nbn:de:0030-drops-84448},
  doi =		{10.4230/OASIcs.ICCSW.2017.2},
  annote =	{Keywords: Javascript, NodeJS}
}
Document
Improving the Latency and Throughput of ZooKeeper Atomic Broadcast

Authors: Ibrahim EL-Sanosi and Paul Ezhilchelvan

Published in: OASIcs, Volume 60, 2017 Imperial College Computing Student Workshop (ICCSW 2017)


Abstract
ZooKeeper is a crash-tolerant system that offers fundamental services to Internet-scale applications, thereby reducing the development and hosting of the latter. It consists of >3 servers that form a replicated state machine. Maintaining these replicas in a mutually consistent state requires executing an Atomic Broadcast Protocol, Zab, so that concurrent requests for state changes are serialised identically at all replicas before being acted upon. Thus, ZooKeeper performance for update operations is determined by Zab performance. We contribute by presenting two easy-to-implement Zab variants, called ZabAC and ZabAA. They are designed to offer small atomic-broadcast latencies and to reduce the processing load on the primary node that plays a leading role in Zab. The former improves ZooKeeper performance and the latter enables ZooKeeper to face more challenging load conditions.

Cite as

Ibrahim EL-Sanosi and Paul Ezhilchelvan. Improving the Latency and Throughput of ZooKeeper Atomic Broadcast. In 2017 Imperial College Computing Student Workshop (ICCSW 2017). Open Access Series in Informatics (OASIcs), Volume 60, pp. 3:1-3:10, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)


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@InProceedings{elsanosi_et_al:OASIcs.ICCSW.2017.3,
  author =	{EL-Sanosi, Ibrahim and Ezhilchelvan, Paul},
  title =	{{Improving the Latency and Throughput of ZooKeeper Atomic Broadcast}},
  booktitle =	{2017 Imperial College Computing Student Workshop (ICCSW 2017)},
  pages =	{3:1--3:10},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-059-0},
  ISSN =	{2190-6807},
  year =	{2018},
  volume =	{60},
  editor =	{Leahy, Fergus and Franco, Juliana},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2017.3},
  URN =		{urn:nbn:de:0030-drops-84452},
  doi =		{10.4230/OASIcs.ICCSW.2017.3},
  annote =	{Keywords: Atomic Broadcast, Server Replication, Protocol Latency, Throughput}
}
Document
Demand for Medical Care by the Elderly: A Nonparametric Variational Bayesian Mixture Approach

Authors: Christoph F. Kurz and Rolf Holle

Published in: OASIcs, Volume 60, 2017 Imperial College Computing Student Workshop (ICCSW 2017)


Abstract
Outpatient care is a large share of total health care spending, making analysis of data on outpatient utilization an important part of understanding patterns and drivers of health care spending growth. Common features of outpatient utilization measures include zero-inflation, over-dispersion, and skewness, all of which complicate statistical modeling. Mixture modeling is a popular approach because it can accommodate these features of health care utilization data. In this work, we add a nonparametric clustering component to such models. Our fully Bayesian model framework allows for an unknown number of mixing components, so that the data, rather than the researcher, determine the number of mixture components. We apply the modeling framework to data on visits to physicians by elderly individuals and show that each subgroup has different characteristics that allow easy interpretation and new insights.

Cite as

Christoph F. Kurz and Rolf Holle. Demand for Medical Care by the Elderly: A Nonparametric Variational Bayesian Mixture Approach. In 2017 Imperial College Computing Student Workshop (ICCSW 2017). Open Access Series in Informatics (OASIcs), Volume 60, pp. 4:1-4:7, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)


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@InProceedings{kurz_et_al:OASIcs.ICCSW.2017.4,
  author =	{Kurz, Christoph F. and Holle, Rolf},
  title =	{{Demand for Medical Care by the Elderly: A Nonparametric Variational Bayesian Mixture	Approach}},
  booktitle =	{2017 Imperial College Computing Student Workshop (ICCSW 2017)},
  pages =	{4:1--4:7},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-059-0},
  ISSN =	{2190-6807},
  year =	{2018},
  volume =	{60},
  editor =	{Leahy, Fergus and Franco, Juliana},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2017.4},
  URN =		{urn:nbn:de:0030-drops-84462},
  doi =		{10.4230/OASIcs.ICCSW.2017.4},
  annote =	{Keywords: machine learning, health care utilization, Bayesian statistics}
}
Document
Discriminative and Generative Models for Clinical Risk Estimation: An Empirical Comparison

Authors: John Stamford and Chandra Kambhampati

Published in: OASIcs, Volume 60, 2017 Imperial College Computing Student Workshop (ICCSW 2017)


Abstract
Linear discriminative models, in the form of Logistic Regression, are a popular choice within the clinical domain in the development of risk models. Logistic regression is commonly used as it offers explanatory information in addition to its predictive capabilities. In some examples the coefficients from these models have been used to determine overly simplified clinical risk scores. Such models are constrained to modeling linear relationships between the variables and the class despite it known that this relationship is not always linear. This paper compares the conditions under which linear discriminative and linear generative models perform best. This is done through comparing logistic regression and naïve Bayes on real clinical data. The work shows that generative models perform best when the internal representation of the data is closer to the true distribution of the data and when there is a very small difference between the means of the classes. When looking at variables such as sodium it is shown that logistic regression can not model the observed risk as it is non-linear in its nature, whereas naïve Bayes gives a better estimation of risk. The work concludes that the risk estimations derived from discriminative models such as logistic regression need to be considered in the wider context of the true risk observed within the dataset.

Cite as

John Stamford and Chandra Kambhampati. Discriminative and Generative Models for Clinical Risk Estimation: An Empirical Comparison. In 2017 Imperial College Computing Student Workshop (ICCSW 2017). Open Access Series in Informatics (OASIcs), Volume 60, pp. 5:1-5:9, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)


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@InProceedings{stamford_et_al:OASIcs.ICCSW.2017.5,
  author =	{Stamford, John and Kambhampati, Chandra},
  title =	{{Discriminative and Generative Models for Clinical Risk Estimation: An Empirical Comparison}},
  booktitle =	{2017 Imperial College Computing Student Workshop (ICCSW 2017)},
  pages =	{5:1--5:9},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-059-0},
  ISSN =	{2190-6807},
  year =	{2018},
  volume =	{60},
  editor =	{Leahy, Fergus and Franco, Juliana},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2017.5},
  URN =		{urn:nbn:de:0030-drops-84475},
  doi =		{10.4230/OASIcs.ICCSW.2017.5},
  annote =	{Keywords: Discriminative, Generative, Na\"{i}ve Bayes, Logistic Regression, Clinical Risk}
}
Document
Hey there's DALILA: a DictionAry LearnIng LibrAry

Authors: Veronica Tozzo, Vanessa D'Amario, and Annalisa Barla

Published in: OASIcs, Volume 60, 2017 Imperial College Computing Student Workshop (ICCSW 2017)


Abstract
Dictionary Learning and Representation Learning are machine learning methods for decomposition, denoising and reconstruction of data with a wide range of applications such as text recognition, image processing and biological processes understanding. In this work we present DALILA, a scientific Python library for regularised dictionary learning and regularised representation learning that allows to impose prior knowledge, if available. DALILA, differently from the others available libraries for this purpose, is flexible and modular. DALILA is designed to be easily extended for custom needs. Moreover, it is compliant with the most widespread ML Python library and this allows for a straightforward usage and integration. We here present and discuss the theoretical aspects and discuss its strength points and implementation.

Cite as

Veronica Tozzo, Vanessa D'Amario, and Annalisa Barla. Hey there's DALILA: a DictionAry LearnIng LibrAry. In 2017 Imperial College Computing Student Workshop (ICCSW 2017). Open Access Series in Informatics (OASIcs), Volume 60, pp. 6:1-6:14, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)


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@InProceedings{tozzo_et_al:OASIcs.ICCSW.2017.6,
  author =	{Tozzo, Veronica and D'Amario, Vanessa and Barla, Annalisa},
  title =	{{Hey there's DALILA: a DictionAry LearnIng LibrAry}},
  booktitle =	{2017 Imperial College Computing Student Workshop (ICCSW 2017)},
  pages =	{6:1--6:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-059-0},
  ISSN =	{2190-6807},
  year =	{2018},
  volume =	{60},
  editor =	{Leahy, Fergus and Franco, Juliana},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2017.6},
  URN =		{urn:nbn:de:0030-drops-84483},
  doi =		{10.4230/OASIcs.ICCSW.2017.6},
  annote =	{Keywords: Machine learning, dictionary learning, representation learning, alternating proximal gradient descent, parallel computing}
}
Document
Faster Concurrent Range Queries with Contention Adapting Search Trees Using Immutable Data

Authors: Kjell Winblad

Published in: OASIcs, Volume 60, 2017 Imperial College Computing Student Workshop (ICCSW 2017)


Abstract
The need for scalable concurrent ordered set data structures with linearizable range query support is increasing due to the rise of multicore computers, data processing platforms and in-memory databases. This paper presents a new concurrent ordered set with linearizable range query support. The new data structure is based on the contention adapting search tree and an immutable data structure. Experimental results show that the new data structure is as much as three times faster compared to related data structures. The data structure scales well due to its ability to adapt the sizes of its immutable parts to the contention level and the sizes of the range queries.

Cite as

Kjell Winblad. Faster Concurrent Range Queries with Contention Adapting Search Trees Using Immutable Data. In 2017 Imperial College Computing Student Workshop (ICCSW 2017). Open Access Series in Informatics (OASIcs), Volume 60, pp. 7:1-7:13, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)


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@InProceedings{winblad:OASIcs.ICCSW.2017.7,
  author =	{Winblad, Kjell},
  title =	{{Faster Concurrent Range Queries with Contention Adapting Search Trees Using Immutable Data}},
  booktitle =	{2017 Imperial College Computing Student Workshop (ICCSW 2017)},
  pages =	{7:1--7:13},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-059-0},
  ISSN =	{2190-6807},
  year =	{2018},
  volume =	{60},
  editor =	{Leahy, Fergus and Franco, Juliana},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2017.7},
  URN =		{urn:nbn:de:0030-drops-84492},
  doi =		{10.4230/OASIcs.ICCSW.2017.7},
  annote =	{Keywords: linearizability, concurrent data structures, treap}
}
Document
Gesture Recognition and Classification using Intelligent Systems

Authors: Norah Alnaim and Maysam Abbod

Published in: OASIcs, Volume 60, 2017 Imperial College Computing Student Workshop (ICCSW 2017)


Abstract
Gesture Recognition is defined as non-verbal human motions used as a method of communication in HCI interfaces. In a virtual reality system, gestures can be used to navigate, control, or interact with a computer. Having a person make gestures formed in specific ways to be detected by a device, like a camera, is the foundation of gesture recognition. Finger tracking is an interesting principle which deals with three primary parts of computer vision: segmentation of the finger, detection of finger parts, and tracking of the finger. Fingers are most commonly used in varying gesture recognition systems. Finger gestures can be detected using any type of camera; keeping in mind that different cameras will yield different resolution qualities. 2-dimensional cameras exhibit the ability to detect most finger motions in a constant surface called 2-D. While the image processes, the system prepares to receive the whole image so that it may be tracked using image processing tools. Artificial intelligence releases many classifiers, each one with the ability to classify data, that rely on its configuration and capabilities. In this work, the aim is to develop a system for finger motion acquisition in 2-D using feature extraction algorithms such as Wavelets transform (WL) and Empirical Mode Decomposition (EMD) plus Artificial Neural Network (ANN) classifier.

Cite as

Norah Alnaim and Maysam Abbod. Gesture Recognition and Classification using Intelligent Systems. In 2017 Imperial College Computing Student Workshop (ICCSW 2017). Open Access Series in Informatics (OASIcs), Volume 60, p. 8:1, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)


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@InProceedings{alnaim_et_al:OASIcs.ICCSW.2017.8,
  author =	{Alnaim, Norah and Abbod, Maysam},
  title =	{{Gesture Recognition and Classification using Intelligent Systems}},
  booktitle =	{2017 Imperial College Computing Student Workshop (ICCSW 2017)},
  pages =	{8:1--8:1},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-059-0},
  ISSN =	{2190-6807},
  year =	{2018},
  volume =	{60},
  editor =	{Leahy, Fergus and Franco, Juliana},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2017.8},
  URN =		{urn:nbn:de:0030-drops-84508},
  doi =		{10.4230/OASIcs.ICCSW.2017.8},
  annote =	{Keywords: Wavelets, Empirical Model Decomposition, Artificial Neural Network, Gesture Recognition, HCI}
}
Document
KubeNow: A Cloud Agnostic Platform for Microservice-Oriented Applications

Authors: Marco Capuccini, Anders Larsson, Salman Toor, and Ola Spjuth

Published in: OASIcs, Volume 60, 2017 Imperial College Computing Student Workshop (ICCSW 2017)


Abstract
KubeNow is a platform for rapid and continuous deployment of microservice-based applications over cloud infrastructure. Within the field of software engineering, the microservice-based architecture is a methodology in which complex applications are divided into smaller, more narrow services. These services are independently deployable and compatible with each other like building blocks. These blocks can be combined in multiple ways, according to specific use cases. Microservices are designed around a few concepts: they offer a minimal and complete set of features, they are portable and platform independent, they are accessible through language agnostic APIs and they are encouraged to use standard data formats. These characteristics promote separation of concerns, isolation and interoperability, while coupling nicely with test-driven development. Among many others, some well-known companies that build their software around microservices are: Google, Amazon, PayPal Holdings Inc. and Netflix [11].

Cite as

Marco Capuccini, Anders Larsson, Salman Toor, and Ola Spjuth. KubeNow: A Cloud Agnostic Platform for Microservice-Oriented Applications. In 2017 Imperial College Computing Student Workshop (ICCSW 2017). Open Access Series in Informatics (OASIcs), Volume 60, pp. 9:1-9:2, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)


Copy BibTex To Clipboard

@InProceedings{capuccini_et_al:OASIcs.ICCSW.2017.9,
  author =	{Capuccini, Marco and Larsson, Anders and Toor, Salman and Spjuth, Ola},
  title =	{{KubeNow: A Cloud Agnostic Platform for Microservice-Oriented Applications}},
  booktitle =	{2017 Imperial College Computing Student Workshop (ICCSW 2017)},
  pages =	{9:1--9:2},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-059-0},
  ISSN =	{2190-6807},
  year =	{2018},
  volume =	{60},
  editor =	{Leahy, Fergus and Franco, Juliana},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2017.9},
  URN =		{urn:nbn:de:0030-drops-84511},
  doi =		{10.4230/OASIcs.ICCSW.2017.9},
  annote =	{Keywords: Microservices, Cloud computing, Infrastructure as Code, Docker, Kubernetes}
}
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