24 research outputs found
A picture is worth a thousand words : content-based image retrieval techniques
In my dissertation I investigate techniques for improving the state of the art in content-based image retrieval. To place my work into context, I highlight the current trends and challenges in my field by analyzing over 200 recent articles. Next, I propose a novel paradigm called __artificial imagination__, which gives the retrieval system the power to imagine and think along with the user in terms of what she is looking for. I then introduce a new user interface for visualizing and exploring image collections, empowering the user to navigate large collections based on her own needs and preferences, while simultaneously providing her with an accurate sense of what the database has to offer. In the later chapters I present work dealing with millions of images and focus in particular on high-performance techniques that minimize memory and computational use for both near-duplicate image detection and web search. Finally, I show early work on a scene completion-based image retrieval engine, which synthesizes realistic imagery that matches what the user has in mind.LEI Universiteit LeidenNWOImagin
Adventures in software engineering : plugging HCI & acessibility gaps with open source solutions
There has been a great deal of research undertaken in the field of Human-Computer Interfaces (HCI), input devices, and output modalities in recent years. From touch-based and voice control input mechanisms such as those found on modern smart-devices to the use of touch-free input through video-stream/image analysis (including depth streams and skeletal mapping) and the inclusion of gaze tracking, head tracking, virtual reality and beyond - the availability and variety of these I/O (Input/Output) mechanisms has increased tremendously and progressed both into our living rooms and into our lives in general. With regard to modern desktop computers and videogame consoles, at present many of these technologies are at a relatively immature stage of development - their use often limited to simple adjuncts to the staple input mechanisms of mouse, keyboard, or joystick / joypad inputs. In effect, we have these new input devices - but we're not quite sure how best to use them yet; that is, where their various strengths and weaknesses lie, and how or if they can be used to conveniently and reliably drive or augment applications in our everyday lives. In addition, much of this technology is provided by proprietary hardware and software, providing limited options for customisation or adaptation to better meet the needs of specific users. Therefore, this project investigated the development of open source software solutions to address various aspects of innovative user I/O in a flexible manner. Towards this end, a number of original software applications have been developed which incorporate functionality aimed at enhancing the current state of the art in these areas and making that software freely available for use by any who may find it beneficial.Doctor of Philosoph
Design revolutions: IASDR 2019 Conference Proceedings. Volume 3: People
In September 2019 Manchester School of Art at Manchester Metropolitan University was honoured to host the bi-annual conference of the International Association of Societies of Design Research (IASDR) under the unifying theme of DESIGN REVOLUTIONS. This was the first time the conference had been held in the UK. Through key research themes across nine conference tracks – Change, Learning, Living, Making, People, Technology, Thinking, Value and Voices – the conference opened up compelling, meaningful and radical dialogue of the role of design in addressing societal and organisational challenges. This Volume 3 includes papers from People track of the conference
Data and the city – accessibility and openness. a cybersalon paper on open data
This paper showcases examples of bottom–up open data and smart city applications and identifies lessons for future such efforts. Examples include Changify, a neighbourhood-based platform for residents, businesses, and companies; Open Sensors, which provides APIs to help businesses, startups, and individuals develop applications for the Internet of Things; and Cybersalon’s Hackney Treasures. a location-based mobile app that uses Wikipedia entries geolocated in Hackney borough to map notable local residents. Other experiments with sensors and open data by Cybersalon members include Ilze Black and Nanda Khaorapapong's The Breather, a "breathing" balloon that uses high-end, sophisticated sensors to make air quality visible; and James Moulding's AirPublic, which measures pollution levels. Based on Cybersalon's experience to date, getting data to the people is difficult, circuitous, and slow, requiring an intricate process of leadership, public relations, and perseverance. Although there are myriad tools and initiatives, there is no one solution for the actual transfer of that data
Recommended from our members
NBS monograph
From Introduction: "This report is the first of a series intended to provide a selective overview of research and development efforts and requirements in the somewhat overlapping fields of the computer and information sciences and technologies. The projected series of reports will attempt to outline the probable range of R & D activities in the computer and information sciences and technologies through selective reviews of the literature and to develop a reasonable consensus with respect to the opinions of workers in these and potentially related fields as to areas of continuing R & D concern for research program planning or review in these areas.
Collective intelligence: creating a prosperous world at peace
XXXII, 612 p. ; 24 cmLibro ElectrĂłnicoEn este documento se plantea un tema de interes general mas como lo es especificamente el tema de la evolucion de la sociedad en materia de industria y crecimiento de las actividades humanas en el aspecto de desarrollo de la creatividad enfocada a los mercadosedited by Mark Tovey ; foreword by Yochai Benkler (re-mixed by Hassan Masum) ; prefaces by Thomas Malone, Tom Atlee & Pierre Levy ; afterword by Paul Martin & Thomas Homer-Dixon.The era of collective intelligence has begun in earnest. While others have written about the wisdom of crowds, an army of Davids, and smart mobs, this collection of essays for the first time brings together fifty-five pioneers in the emerging discipline of collective intelligence. They provide a base of tools for connecting people, producing high-functioning teams, collaborating at multiple scales, and encouraging effective peer-production. Emerging models are explored for digital deliberative democracy, self-governance, legislative transparency, true-cost accounting, and the ethical use of open sources and methods. Collective Intelligence is the first of a series of six books, which will also include volumes on Peace Intelligence, Commercial Intelligence, Gift Intelligence, Cultural Intelligence, and Global Intelligence.Table of Contents
Dedication i
Publisher’s Preface iii
Foreword by Yochai Benkler Remix Hassan Masum xi
The Wealth of Networks: Highlights remixed
Editor’s Preface xxi
Table of Contents xxv
A What is collective intelligence and what will we do 1
about it? (Thomas W. Malone, MIT Center for
Collective Intelligence)
B Co-Intelligence, collective intelligence, and conscious 5
evolution (Tom Atlee, Co-Intelligence Institute)
C A metalanguage for computer augmented collective 15
intelligence (Prof. Pierre LĂ©vy, Canada Research
Chair in Collective Intelligence, FRSC)
I INDIVIDUALS & GROUPS I-01 Foresight I-01-01 Safety Glass (Karl Schroeder, science fiction author 23
and foresight consultant)
I-01-02 2007 State of the Future (Jerome C. Glenn & 29
Theodore J. Gordon, United Nations Millennium
Project)
I-02 Dialogue & Deliberation I-02-01 Thinking together without ego: Collective intelligence 39
as an evolutionary catalyst (Craig Hamilton and Claire
Zammit, Collective-Intelligence.US)
I-02-02 The World Café: Awakening collective intelligence 47
and committed action (Juanita Brown, David Isaacs
and the World Café Community)
I-02-03 Collective intelligence and the emergence of 55
wholeness (Peggy Holman, Nexus for Change, The
Change Handbook)
I-02-04 Knowledge creation in collective intelligence (Bruce 65
LaDuke, Fortune 500, HyperAdvance.com)
I-02-05 The Circle Organization: Structuring for collective 75
wisdom (Jim Rough, Dynamic Facilitation & The
Center for Wise Democracy)
I-03 Civic Intelligence I-03-01 Civic intelligence and the public sphere (Douglas 83
Schuler, Evergreen State College, Public Sphere
Project)
I-03-02 Civic intelligence and the security of the homeland 95
(John Kesler with Carole and David Schwinn,
IngeniusOnline)
I-03-03 Creating a Smart Nation (Robert Steele, OSS.Net) 107
I-03-04 University 2.0: Informing our collective intelligence 131
(Nancy Glock-Grueneich, HIGHEREdge.org)
I-03-05 Producing communities of communications and 145
foreknowledge (Jason “JZ” Liszkiewicz,
Reconfigure.org)
I-03-06 Global Vitality Report 2025: Learning to transform I-04 Electronic Communities & Distributed Cognition I-04-01 Attentional capital and the ecology of online social 163
conflict and think together effectively (Peter+Trudy networks (Derek Lomas, Social Movement Lab,
Johnson-Lenz, Johnson-Lenz.com ) UCSD)
I-04-02 A slice of life in my virtual community (Howard 173
Rheingold, Whole Earth Review, Author & Educator)
I-04-03 Shared imagination (Dr. Douglas C. Engelbart, 197
Bootstrap)
I-05 Privacy & Openness I-05-01 We’re all swimming in media: End-users must be able 201
to keep secrets (Mitch Ratcliffe, BuzzLogic &
Tetriad)
I-05-02 Working openly (Lion Kimbro, Programmer and 205
Activist)
I-06 Integral Approaches & Global Contexts I-06-01 Meta-intelligence for analyses, decisions, policy, and 213
action: The Integral Process for working on complex
issues (Sara Nora Ross, Ph.D. ARINA & Integral
Review)
I-06-02 Collective intelligence: From pyramidal to global 225
(Jean-Francois Noubel, The Transitioner)
I-06-03 Cultivating collective intelligence: A core leadership 235
competence in a complex world (George PĂłr, Fellow
at Universiteit van Amsterdam)
II LARGE-SCALE COLLABORATION II-01 Altruism, Group IQ, and Adaptation II-01-01 Empowering individuals towards collective online 245
production (Keith Hopper, KeithHopper.com)
II-01-02 Who’s smarter: chimps, baboons or bacteria? The 251
power of Group IQ (Howard Bloom, author)
II-01-03 A collectively generated model of the world (Marko 261
A. Rodriguez, Los Alamos National Laboratory)
II-02 Crowd Wisdom and Cognitive Bias II-02-01 Science of CI: Resources for change (Norman L 265
Johnson, Chief Scientist at Referentia Systems, former
LANL)
II-02-02 Collectively intelligent systems (Jennifer H. Watkins, 275
Los Alamos National Laboratory)
II-02-03 A contrarian view (Jaron Lanier, scholar-in-residence, 279
CET, UC Berkeley & Discover Magazine)
II-03 Semantic Structures & The Semantic Web II-03-01 Information Economy Meta Language (Interview with 283
Professor Pierre LĂ©vy, by George PĂłr)
II-03-02 Harnessing the collective intelligence of the World- 293
Wide Web (Nova Spivack, RadarNetworks, Web 3.0)
II-03-03 The emergence of a global brain (Francis Heylighen, 305
Free University of Brussels)
II-04 Information Networks II-04-01 Networking and mobilizing collective intelligence (G.
Parker Rossman, Future of Learning Pioneer)
II-04-02 Toward high-performance organizations: A strategic 333
role for Groupware (Douglas C. Engelbart, Bootstrap)
II-04-03 Search panacea or ploy: Can collective intelligence 375
improve findability? (Stephen E. Arnold, Arnold IT,
Inc.)
II-05 Global Games, Local Economies, & WISER II-05-01 World Brain as EarthGame (Robert Steele and many 389
others, Earth Intelligence Network)
II-05-02 The Interra Project (Jon Ramer and many others) 399
II-05-03 From corporate responsibility to Backstory 409
Management (Alex Steffen, Executive Editor,
Worldchanging.com)
II-05-04 World Index of Environmental & Social 413
Responsibility (WISER)
By the Natural Capital Institute
II-06 Peer-Production & Open Source Hardware II-06-01 The Makers’ Bill of Rights (Jalopy, Torrone, and Hill) 421
II-06-02 3D Printing and open source design (James Duncan, 423
VP of Technology at Marketingisland)
II-06-03 REBEARTHTM: 425
II-07 Free Wireless, Open Spectrum, and Peer-to-Peer II-07-01 Montréal Community Wi-Fi (Île Sans Fil) (Interview 433
with Michael Lenczner by Mark Tovey)
II-07-02 The power of the peer-to-peer future (Jock Gill, 441
Founder, Penfield Gill Inc.)
Growing a world 6.6 billion people
would want to live in (Marc Stamos, B-Comm, LL.B)
II-07-03 Open spectrum (David Weinberger)
II-08 Mass Collaboration & Large-Scale Argumentation II-08-01 Mass collaboration, open source, and social 455
entrepreneurship (Mark Tovey, Advanced Cognitive
Engineering Lab, Institute of Cognitive Science,
Carleton University)
II-08-02 Interview with Thomas Homer-Dixon (Hassan 467
Masum, McLaughlin-Rotman Center for Global
Health)
II-08-03 Achieving collective intelligence via large-scale
argumentation (Mark Klein, MIT Center for
Collective Intelligence)
II-08-04 Scaling up open problem solving (Hassan Masum & 485
Mark Tovey)
D Afterword: The Internet and the revitalization of 495
democracy (The Rt. Honourable Paul Martin &
Thomas Homer-Dixon)
E Epilogue by Tom Atlee 513
F Three Lists 515
1. Strategic Reading Categories
2. Synopsis of the New Progressives
3. Fifty-Two Questions that Matter
G Glossary 519
H Index 52
Deep Neural Networks and Tabular Data: Inference, Generation, and Explainability
Over the last decade, deep neural networks have enabled remarkable technological advancements, potentially transforming a wide range of aspects of our lives in the future. It is becoming increasingly common for deep-learning models to be used in a variety of situations in the modern life, ranging from search and recommendations to financial and healthcare solutions, and the number of applications utilizing deep neural networks is still on the rise.
However, a lot of recent research efforts in deep learning have focused primarily on neural networks and domains in which they excel. This includes computer vision, audio processing, and natural language processing. It is a general tendency for data in these areas to be homogeneous, whereas heterogeneous tabular datasets have received relatively scant attention despite the fact that they are extremely prevalent. In fact, more than half of the datasets on the Google dataset platform are structured and can be represented in a tabular form.
The first aim of this study is to provide a thoughtful and comprehensive analysis of deep neural networks' application to modeling and generating tabular data. Apart from that, an open-source performance benchmark on tabular data is presented, where we thoroughly compare over twenty machine and deep learning models on heterogeneous tabular datasets.
The second contribution relates to synthetic tabular data generation. Inspired by their success in other homogeneous data modalities, deep generative models such as variational autoencoders and generative adversarial networks are also commonly applied for tabular data generation. However, the use of Transformer-based large language models (which are also generative) for tabular data generation have been received scant research attention. Our contribution to this literature consists of the development of a novel method for generating tabular data based on this family of autoregressive generative models that, on multiple challenging benchmarks, outperformed the current state-of-the-art methods for tabular data generation.
Another crucial aspect for a deep-learning data system is that it needs to be reliable and trustworthy to gain broader acceptance in practice, especially in life-critical fields. One of the possible ways to bring trust into a data-driven system is to use explainable machine-learning methods.
In spite of this, the current explanation methods often fail to provide robust explanations due to their high sensitivity to the hyperparameter selection or even changes of the random seed. Furthermore, most of these methods are based on feature-wise importance, ignoring the crucial relationship between variables in a sample. The third aim of this work is to address both of these issues by offering more robust and stable explanations, as well as taking into account the relationships between variables using a graph structure.
In summary, this thesis made a significant contribution that touched many areas related to deep neural networks and heterogeneous tabular data as well as the usage of explainable machine learning methods
Hands-on Science. Advancing Science. Improving Education
The book herein aims to contribute to the advancement of Science to the
improvement of Science Education and to an effective implementation of a
sound widespread scientific literacy at all levels of society. Its chapters reunite
a variety of diverse and valuable works presented in this line of thought at the
15th International Conference on Hands-on Science “Advancing Science.
Improving Education