Seminar on Internet Technologies (Winter 2016/2017): Difference between revisions
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| '''Learning from Imbalanced Data''' | | '''Learning from Imbalanced Data (assigned to Oleh Astappiev)''' | ||
When building and training classifiers for classification problems, one commonly encountered problem is that of imbalanced data. For instance, in the case of a binary classifier, this means that one class is hugely overrepresented in the data available. Training classifiers for this kind of datasets has been a problem for some time. In this work, your task is to i) precisely introduce the imbalanced data problem, ii) discuss the state of the art of approaches for mitigating this problem (both from the perspective of learning algorithms and data manipulation techniques) and iii) find out what issues still remain open until today. Note that this topic requires a background in data science, and in particular in classification algorithms. Also, this topic requires a comparatively high reading effort. | When building and training classifiers for classification problems, one commonly encountered problem is that of imbalanced data. For instance, in the case of a binary classifier, this means that one class is hugely overrepresented in the data available. Training classifiers for this kind of datasets has been a problem for some time. In this work, your task is to i) precisely introduce the imbalanced data problem, ii) discuss the state of the art of approaches for mitigating this problem (both from the perspective of learning algorithms and data manipulation techniques) and iii) find out what issues still remain open until today. Note that this topic requires a background in data science, and in particular in classification algorithms. Also, this topic requires a comparatively high reading effort. | ||
| [https://www.net.informatik.uni-goettingen.de/people/David_Koll David Koll ] | | [https://www.net.informatik.uni-goettingen.de/people/David_Koll David Koll ] |
Revision as of 16:24, 20 October 2016
Details
Workload/ECTS Credits: | 5 ECTS (BSc/MSc AI); 5 (ITIS) |
Module: | M.Inf.1124 -or- B.Inf.1207/1208; ITIS Module 3.16: Selected Topics in Internet Technologies |
Lecturer: | Dr. Hong Huang |
Teaching assistant: | Tao Zhao |
Time: | Oct 20, 16:00ct: Introduction Meeting |
Place: | IFI Building, Room 3.101 |
UniVZ | [1] |
Course description
This course covers selected topics on the up-to-date Internet technologies and research. Each student takes a topic, does a presentation and writes a report on it. Besides the introduction meeting, there are no regular meetings, lectures or classes for this course. The purpose of this course is to familiarize the students with new technologies, enable independent study of a specific topic, and train presentation and writing skills.
The informational meeting at the beginning of the course will cover some guidelines on scientific presenting and writing.
Passing requirements
- Actively and frequently participate in the project communication with your topic advisor
- This accounts for 20% of your grade.
- Present the selected topic (20 min. presentation + 10 min. Q&A).
- This accounts for 40% of your grade.
- Write a report on the selected topic (12-15 pages) (LaTeX Template:[2]).
- This accounts for 40% of your grade.
- Please check the #Schedule and adhere to it.
Schedule
- Oct. 20, 16:00ct: Introduction meeting
- TBA : Deadline for registration
- TBA : Presentations
- Mar. 31, 2017, 23:59: Deadline for submission of report (should be sent to the topic adviser!)
Topics
Workflow
1. Select a topic
A student picks a topic to work on. You can pick up a topic and start working at any time. However, make sure to notify the advisor of the topic before starting to work.
2. Get your work advised
For each topic, a topic advisor is available. He is your contact person for questions and problems regarding the topic. He supports you as much as you want, so please do not hesitate to approach him for any advice or with any questions you might have. It is recommended (and not mandatory) that you schedule a face-to-face meeting with him right after you select your topic.
3. Approach your topic
- By choosing a topic, you choose the direction of elaboration.
- You may work in different styles, for example:
- Survey: Basic introduction, overview of the field; general problems, methods, approaches.
- Specific problem: Detailed introduction, details about the problem and the solution.
- You should include your own thoughts on your topic.
4. Prepare your presentation
- Present your topic to the audience (in English).
- 20 minutes of presentation followed by 10 minutes discussion.
You present your topic to an audience of students and other interested people (usually the NET group members). Your presentation should give the audience a general idea of the topic and highlight interesting problems and solutions. You have 20 minutes to present your topic followed by 10 minutes of discussion. You must keep it within the time limit. Please send your slides to your topic advisor for any possible feedback before your presentation.
Hints for preparing the presentation: 20 minutes are too short to present a topic fully. It is alright to focus just on one certain important aspect. Limit the introduction of basics. Make sure to finish in time.
Suggestions for preparing the slides: No more than 20 pages/slides. Get your audiences to quickly understand the general idea. Figures, tables and animations are better than sentences. Summary of the topic: thinking in your own words.
5. Write your report
- Present the problem with its background.
- Detail the approaches, techniques, methods to handle the problem.
- Evaluate and assess those approaches (e.g., pros and cons).
- Give a short outlook on potential future developments.
The report must be written in English according to common guidelines for scientific papers, between 12 and 15 pages of content (excluding the table of content, bibliography, etc.).
6. Course schedule
There are no regular meetings, lectures or classes for this course. The work is expected to be done by yourself with the assistance of your topic advisor. Please follow the #Schedule to take appropriate actions.
Topic | Topic Advisor | Initial Readings |
Why deep learning is suddenly changing your life?- A survey (assigned to Sudhir Kumar Sah)
This study is to provide a comprehensive survey on the key enabling technologies for deep learning. |
Hong Huang | [3] |
Deep into Google Translate (assigned to Azadeh Amiri)
This study is to provide a comprehensive study of one of the Google products - Google translate and aim to understand the technologies behind it. |
Hong Huang | [4] |
Towards a Pricing Model in NFV (assigned to Saidul Islam)
One of the untouched research areas in Network Function Virtualization (NFV) is Accounting Management. Your task is firstly identify the current Management systems that used in Data centers and cloud computing environments and later to map what you think it might be useful to NFV area. You should support your statement with logical reasons so far. It is not required to conducted any empirical work. Your work should investigate in some depth the exact relationship between different factors not only describing them. |
Osamah Barakat | [5][6][7] |
Legacy support in SDN networks(assigned to Dorna Amiri)
Supporting legacy network is an active research area in SDN. You should survey all techniques used up to date to solve this problem. Details may be provided later. |
Osamah Barakat | TBD |
What is the current status and future of cloud related research? What are the main research problems that are currently being targeted? (assigned to Georgios Kaklamanos)
Cloud computing and cloud based services have become an integral part of the Internet. The aim of this work is to study what research problems exist and also identify promising solutions. Topics pertaining to Data Centers are also of relevance. |
Mayutan Arumaithurai | Take a look at recent papers in well known conferences/workshops. |
Sponsored Search Auctions in Internet (Online advertisements Google Ads)(assigned to Han)
Sponsored search auctions are widely used by search engines like Google, Microsoft, for displaying ads when an user perform keyword search in goole.com/bing.com. The application of sponsored search auctions in not only limited to search engine providers but also has popular with online markets like eBay. The goal is to perform survey on the latest advancements in this area. |
Abhinandan S Prasad | [8] [9][10] |
Service Plane for Network Functions: Network Service Headers and Other alternatives
Focus of this topic is to understand 'Service Function Chaining of Network Functions', the state-of-the-art proposals like Network Service Headers and related academic works. Reason and justify the need for service plane and then try to propose new mechanisms and design of the data plane to support network services, and the control plane functions necessary to manage these data plane functions. |
Sameer Kulkarni | [11] [12] [13] |
NFV state-of-the-art and Future trends - A survey
Study and Understand Network Function Virtualisation (NFV), the real world use cases and deployment trends of NFV in the Datacenter, telecommunication, private networks. Survey on the reports by standardisation committees and open workgroups like IEFT/ETSI/OPNFV, primarily the specification and requirements for the NFV, and the NFV deployment models. Compare with the available open-source/commercial products if any in the market and make the study of NFV characteristics, the Key Performance Index(KPIs) for NFV and identify the open issues and challenges towards adopting to NFV. Student can choose to carry out either breadth or in-depth on particular aspect of NFV. |
Sameer Kulkarni | [14] [15] [16] [17] [18] |
Green Energy Aware Provisioning for Datacenters (assigned to Rishita Kalyani)
With the advent of cloud computing especially Big data, service providers like Micorsoft, Google, etc are using more and more renewable energy in their data centers to minimize power cost and reduce carbon emission. It is one of the important area of research. The goal is to perform a survey on the state of the art technologies in this area. |
Abhinandan S Prasad | [19] [20] [21] |
Applications of Big Data and Smart Cities (assigned to Abdul Hadi)
Study how the applications of big data support smart cities. Investigate related applications. Study their benefits, challenges, approaches and technologies. Give a short outlook on potential future developments. |
Enhuan Dong | [22] [23] [24] [25] [26][27] |
Google Balloon project (assigned to Vaibhav Kasturia)
Project Loon is a research and development project being developed by Google X with the mission of providing Internet access to rural and remote areas. Provide a comprehensive study on it. Investigate related approaches, techniques, methods, etc. |
Enhuan Dong | [28] |
ICN - Information Centric Networking
Content Centric Networking (CCN) is a new ambitious proposal to replace the IP protocol. A better and faster content distribution, improved privacy, integrated cryptography and easy P2P communication are among the key elements of this architecture. On the other hand problems like efficiency and scalability of the name-based routing, support of existing application and new ones and the possibility to actually deploy this technology are still open and actively discussed, making CCN one of the most active research field in networking. By choosing this topic you will gain a general knowledge of the many architecture proposed for ICN and will have to gain insight into one of the problems like routing or security, or solutions (i.e. applications on top of NDN). - topics available: Routing and IoT with ICN - NDN technical report - ICN Base line scenarios |
Sripriya Adhatarao (adhatarao@cs.uni-goettingen.de) | For general introduction: |
Large-Scale Mobile Traffic Analysis - A Survey (assigned to Yasir Sohail)
This study is to provide a comprehensive study of large-scale mobile traffic analysis. |
Tao Zhao | [29] |
Understanding and modelling individual human mobility (assigned to Tetiana Tolmachova)
This study is to provide a comprehensive study of understanding and modelling individual human mobility. |
Tao Zhao | Take a look at related papers in well known conferences/workshops/journals, e.g., [30] |
Learning from Imbalanced Data (assigned to Oleh Astappiev)
When building and training classifiers for classification problems, one commonly encountered problem is that of imbalanced data. For instance, in the case of a binary classifier, this means that one class is hugely overrepresented in the data available. Training classifiers for this kind of datasets has been a problem for some time. In this work, your task is to i) precisely introduce the imbalanced data problem, ii) discuss the state of the art of approaches for mitigating this problem (both from the perspective of learning algorithms and data manipulation techniques) and iii) find out what issues still remain open until today. Note that this topic requires a background in data science, and in particular in classification algorithms. Also, this topic requires a comparatively high reading effort. |
David Koll | [31] |