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Today's Topics:
1. SPAA 2017 and PODC 2017 Call for Workshops and Tutorials
(Suomela Jukka)
2. PhD studentship in optimization, Strathclyde Business School
(Glasgow, UK) (Kerem Akartunali)
3. 3 tenurable positions at UNSW, Sydney, Australia (Gary Froyland)
4. ES-Rank tool (An Efficient Tool for Classification and
Preference Ranking) (Ali)
5. Workshop on Multilevel Optimization (Kai Hennig)
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Message: 1
Date: Sun, 4 Dec 2016 15:56:14 +0000
From: Suomela Jukka <jukka.suomela@aalto.fi>
To: "DMANET@zpr.uni-koeln.de" <DMANET@zpr.uni-koeln.de>
Subject: [DMANET] SPAA 2017 and PODC 2017 Call for Workshops and
Tutorials
Message-ID: <0FD9B058-7E1B-4F67-ADC3-1F1F4F7F6A8C@aalto.fi>
Content-Type: text/plain; charset="us-ascii"
CALL FOR WORKSHOPS AND TUTORIALS
SPAA 2017 and PODC 2017
July 24-27, 2017, Washington, D.C., USA
http://spaa.acm.org/
http://www.podc.org/
The 29th ACM Symposium on Parallelism in Algorithms and Architecture (SPAA 2017) and the 36h Annual ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing (PODC 2017) invites proposals for half-day and full-day workshops and tutorials that are closely related to the current scope of the conference or are new emerging research fields complementing or extending it, including but not restricted to:
- distributed algorithms: design, analysis, and complexity
- communication networks: algorithms, architectures, services, protocols, applications
- multiprocessor and multi-core architectures and algorithms
- shared and transactional memory, synchronization protocols, concurrent programming
- fault-tolerance, reliability, availability, self-organization, self-stabilization
- codes and reliable communication
- Internet applications, social networks, recommendation systems
- dynamic, adaptive and machine learning based distributed algorithms
- distributed operating systems, middleware platforms, databases
- game-theoretic approaches to distributed computing
- distributed mechanisms design
- peer-to-peer systems, overlay networks, distributed data management
- high-performance, cluster, cloud and grid computing
- wireless networks, mobile computing, autonomous agents and robots
- context-aware distributed systems
- security in distributed computing, cryptographic protocols
- distributed cryptocurrencies and blockchain protocols
- quantum and optics based distributed algorithms
- nanonetworks
- biological distributed algorithms
- sensor, mesh, and ad hoc networks
- specification, semantics, verification of concurrent systems
Workshops and tutorials will be held in conjunction with SPAA and PODC on Sunday, July 23, 2017 and on Friday, July 28, 2017. Interested members of the community are invited to send proposals for workshops and tutorials by email to the workshops and tutorials coordinator:
Leonid Barenboim <leonidb@openu.ac.il>
The following are required in a workshop or a tutorial proposal:
- Title of the workshop or tutorial;
- An abstract describing the main focus of the workshop or tutorial and why it would be of interest to the SPAA and PODC community;
- Names and contact information of the organizers;
- The duration of the workshop or tutorial;
- For the workshops, we need the estimated number of submitted and accepted papers, and a brief description of the review process.
- Declare, if any, your preference regarding the date (Sunday, July 23, 2017 or Friday, July 28, 2017).
The proposals should be submitted to the workshops and tutorial coordinator as soon as possible, but no later than
Friday, January 6, 2017.
Decision on the proposals will be made no later than January 15, 2017. The organizers may opt to review and decide on the proposals on a first-come-first-served basis.
We are happy to announce that the following workshops have been already accepted to be collocated with PODC 2017.
- The 5th Workshop on Biological Distributed Algorithms (BDA 2017)
- The 4th Workshop on Adaptive Resource Management and Scheduling for Cloud Computing (DeMIST 2017)
------------------------------
Message: 2
Date: Sun, 4 Dec 2016 22:16:08 +0000
From: Kerem Akartunali <kerem.akartunali@strath.ac.uk>
To: "dmanet@zpr.uni-koeln.de" <dmanet@zpr.uni-koeln.de>
Subject: [DMANET] PhD studentship in optimization, Strathclyde
Business School (Glasgow, UK)
Message-ID:
<4B17C6D6A097C347A22F9A3FB601F5B953801A48@EX2010-MBX2.ds.strath.ac.uk>
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A PhD studentship in optimization is available at the Dept. of Management Science, University of Strathclyde Business School, Glasgow, UK. Funding is available to cover 3 years of tuition fees plus a tax free stipend (£14,653 for 2017-18, and projected to increase to £15,020 for 2018-19 and £15,395 for 2019-20).
The studentship is open to candidates from any nationality (UK/EU/international), and the project topic is entitled "Optimization of Offshore Renewable Energy Arrays for Minimal Life-Cycle Costs".
The application deadline is 31st January 2017 Tuesday.
ABOUT THE PROJECT
A fundamental difficulty in developing offshore renewable energy (ORE) sites is that the uncertain environmental conditions make accurately assessing the life-cycle costs of a site a challenging problem. In particular, logistical operations throughout the life of a site are subject to uncertain operating conditions, and it is therefore difficult to plan and schedule these operations, and to estimate the resulting durations and costs. Similarly, the generating potential throughout the operation of a given site is dependent on the realised weather as well as the availability of each asset, and uncertainties in each of these make it difficult to accurately predict the profits to be gained from energy production. Decisions on aspects such as the size, layout and composition of a site are therefore difficult to accurately quantify and compare.
This project will aim to develop optimisation models to identify the best strategy for designing an ORE site. A complimentary PhD project in the Dept. of Naval Architecture, Ocean and Marine Engineering at Strathclyde will take an alternative approach to the problem, and as both projects progress in parallel, mutual developments will feed into both projects. This will provide a cross-disciplinary approach to a challenging research problem with potential industry impact.
FUNDING AND ELIGIBILITY
Funding is available to cover 3 years of tuition fees for a UK/EU/international student, plus a tax free stipend of £14,653 for 2017-18, and projected to increase to £15,020 for 2018-19 and £15,395 for 2019-20. The student will be given opportunities to attend a conference and/or specialized training every year.
The PhD project requires a highly numerate graduate with interests in renewable energy. Candidates should have at least a strong Honours degree or equivalent (a strong 2:1 Honours degree, or a B.Sc. degree with 3.3 GPA in a 4.0 system), or preferably a Master's degree in a quantitative discipline such as industrial engineering, operations research, mathematics or computer science (amongst others). Experience in programming and fundamental knowledge in optimization are not essential but highly desirable. Candidates who are not native English speakers will be required to provide evidence for their English skills (such as by IELTS or similar tests that are approved by UKVI, or a degree completed in an English speaking country).
Applications are admitted until 31st January 2017 Tuesday, or until a suitable candidate is found thereafter.
HOW TO APPLY
All PhD applications are to be made online at http://pgr.strath.ac.uk/. All documents (including scans of original documents) can be uploaded during the online application process. Candidates are expected to submit a cover letter, CV, any university degree certificates and transcripts, English test results (if applicable), two recommendation letters (or contact details of two referees, if letters are not available to them), and any other supporting documents. In order to be considered for this studentship, candidates should specifically note the title of this project in their online application when prompted about funding and their source of finance, and they should notify Ms Alison Kerr via email (see below for details) when they have submitted their online application, noting that they are willing to apply to this specific studentship.
More information about the department can be found here: http://www.strath.ac.uk/business/managementscience/
Informal enquiries about the projects to Dr Kerem Akartunali (kerem.akartunali@strath.ac.uk) or Dr Euan Barlow (euan.barlow@strath.ac.uk).
Enquiries regarding applications (including notifying your scholarship application) to: Ms Alison Kerr (alison.kerr@strath.ac.uk)
------------------------------
Message: 3
Date: Sun, 4 Dec 2016 22:46:36 +0000
From: Gary Froyland <g.froyland@unsw.edu.au>
To: "dmanet@zpr.uni-koeln.de" <dmanet@zpr.uni-koeln.de>
Subject: [DMANET] 3 tenurable positions at UNSW, Sydney, Australia
Message-ID:
<SYXPR01MB1791B72D126E67EE487EDB83C9800@SYXPR01MB1791.ausprd01.prod.outlook.com>
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Job Title: Lecturer/Senior Lecturer (3 Positions)
Location: School of Mathematics and Statistics, University of New South Wales, Sydney, Australia
One of Australia's leading research & teaching universities
Vibrant campus life with a strong sense of community & inclusion
Enjoy a career that makes a difference by collaborating & learning from the best
At UNSW, we pride ourselves on being a workplace where the best people come to do their best work.
The School of Mathematics and Statistics is a major centre of research and teaching in the mathematical sciences. The School has notable strengths in fundamental research right through to cutting edge applications. It is seeking appointments at a Lecturer or Senior Lecturer level for candidates whose teaching and research interests align with one or more of its existing teaching and research programs (http://www.maths.unsw.edu.au).
About the role:
A$98K - A$137K per year (plus 17% superannuation and leave loading)
3 tenure track positions (5 years) with one position being in the area of Statistics
Applicants should have:
-PhD or equivalent qualification in a relevant mathematical science
-Demonstrated research ability in Applied Mathematics, Pure Mathematics, or Statistics, which align with the research strengths in the School
-Evidence of effective teaching experience
-Strong publication record in top, peer-reviewed journals
-A capacity to continue productive research at the international level
-A record of, or demonstrated potential for, success in external research funding
-Strong commitment to independent research and research leadership
-Additional criteria apply for the Senior Lecturer (Level C) position, please refer to the selection criteria in the position description.
Applicants may be required to undergo pre-employment checks prior to appointment to these roles. Applications should be made on-line and should systematically address the selection criteria in their applications. Women and people from EEO groups are particularly encouraged to apply.
Having read the documentation, you may direct any enquiries to:
Professor Bruce Henry
Email: b.henry@unsw.edu.au
Applications close 13 January 2017 (AEST)
For full details of this position and application procedure, go to http://www.jobs.unsw.edu.au/
Find out more about working at UNSW at https://www.maths.unsw.edu.au
UNSW is an equal opportunity employer committed to diversity
------------------------------
Message: 4
Date: Mon, 5 Dec 2016 14:29:34 +0000 (UTC)
From: Ali <oas_as@yahoo.com>
To: "dmanet@zpr.uni-koeln.de" <dmanet@zpr.uni-koeln.de>
Subject: [DMANET] ES-Rank tool (An Efficient Tool for Classification
and Preference Ranking)
Message-ID: <732864700.5966552.1480948174517@mail.yahoo.com>
Content-Type: text/plain; charset=UTF-8
ES-Rank
Osman Ali Sadek Ibrahim (Osman.Ibrahim@nottingham.ac.uk)
An Efficient Tool for Classification and Preference Ranking
Optimizing data features help to facilitate the parameter selection and analysis dataset for ranking and classification problems. Sometimes research problem such as ranking dataset instances in Medical Diagnosis, Classification and Information Retrieval require ranking model for the labels based on the importance of the features on the datasets. This tool is an efficient evolutionary computation (evolutionary strategy at the moment) tool that produce a ranking model based on the training dataset and evaluating the produced model on the training and test dataset.
Download: ES-Rank (under development for publishing):- last updated: 03 Dec. 16.
Download example files:1) train.txt and test.txt, OR2) train.txt and test.txt
This tool can be used for both Classification and Preference Learning To Rank. This tool uses 7 fitness evaluation metrics {Mean Average Precision (MAP), Discounted Cumulative Gain (DCG@K), Normalized Discounted Cumulative Gain (NDCG@K), Precision (P@K), Reciprocal Rank (RR@K), Best (BEST@K) and Error Rate (ERR@K)} with variable parameters. The default fitness evaluation function is MAP. The parameter k is the number of top-k retrieved instance from the ranking model by ES-Rank that requires measuring for them the evaluation metric value.
The training set and test set format can be in one of these two formats:
1) Label FeatureID:FeatureValue FeatureID:FeatureValueOR2) Label QueryID:QueryNo. FeatureID:FeatureValue FeatureID:FeatureValueExample for training and testing set are:1)7 1:0.3 2:1
10 1:0.6 2:1.2
11 1:3 2:82)7 qid:100 1:0.3 2:1
10 qid:100 1:0.6 2:1.2
11 qid:101 1:3 2:8
To transfer space, tab or comma delimited data files and convert them into the format required (the above format), you can use this EXE file (CSVtoLTR) in cmd command line.Example for conversion: c:\>CSVtoLTR.exe (then ENTER and follow the instructions).
To use the package in Windows command line or Linux Terminal, you can use the following command:java -jar ESRank.jar (Then ENTER to check the tool instruction and example).
For reference the tool, please use reference [1] at the moment.(Note: the tool under development).
References:
[1] ES-Rank: Evolution Strategy Learning to Rank Approach. Osman A. S. Ibrahim and Dario Landa-Silva. ACM Symposium on Applied Computing (SAC 2017), Marrakech, Morocco, April 03-07, 2017, ISBN: 978-1-4503-4486-9/17/04.
------------------------------
Message: 5
Date: Mon, 5 Dec 2016 16:19:36 +0100
From: Kai Hennig <hennig@zib.de>
To: dmanet@zpr.uni-koeln.de
Subject: [DMANET] Workshop on Multilevel Optimization
Message-ID: <95de45c7-6219-c6d7-0b2e-ab5cad8addf0@zib.de>
Content-Type: text/plain; charset=utf-8
Call for Participation
----------------------
Workshop on
"MULTILEVEL OPTIMIZATION"
16th of December 2016, Zuse Insitute Berlin (ZIB), Berlin, Germany
Description
------------
Traditional mathematical optimization models are premised on the assumption
that there is a single decision to be made at a fixed point in time with a
fixed objective and that the decision-maker (DM) has deterministic
knowledge of all problem inputs. Multilevel/multistage optimization is a
generalized framework that allows for multiple (possibly competing) DMs
acting at multiple points in time. The framework subsumes both game
theoretic models, in which multiple DMs with competing objectives make
decisions sequentially, and recourse models, in which a single DM must make a sequence
of decisions over time in order to react to changing conditions.
In this workshop, we'll discuss the basic concepts underlying this approach
to modeling real-world optimization problems, focusing particularly on the
challenging case in which the models involve discrete decisions. We'll
first discuss the modeling framework itself, what types of applications
it's appropriate for, and what makes solution of these problems inherently
challenging. We'll then discuss the underlying theory, especially the
duality theory that lies at the heart of solution algorithms. Finally,
we'll discuss practical solution algorithms.
Speaker
------------
This workshop is held by Ted Ralphs.
Ted Ralphs received his Ph.D. in Operations Research from Cornell
University in 1995. He is currently a professor in the Department of
Industrial and Systems Engineering (ISE) at Lehigh University, where he
is director of the Laboratory for Computational Optimization Research at
Lehigh (COR@L) and chair of Lehigh's Research Computing Steering
Committee. He is a co-founder of the COIN-OR Foundation, a non-profit
foundation promoting the development of open source software for
operations research and is currently chair of the Technical Leadership
Council and a member of the Strategic Leadership Board, as well as
project manager of a number of projects hosted in the COIN-OR open
source software repository. His research interests include development
of methodology for solving discrete optimization problems, including
those with multiple levels or multiple objectives; development of
parallel search algorithms; development of open source software; and
applications of discrete optimization.
Organization
------------
The workshop will take place in the main lecture hall of ZIB (www.zib.de),
start at 9:30 am, and finish around 2:00 pm. There will be a
break around noon.
Registration
------------
The number of participants is limited, so please send an E-Mail with the
subject "Registration Multilevel Optimization Workshop" to hennig@zib.de
containing your name and your affiliation.
------------------------------
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