Semih Cayci

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Semih Cayci (9)
Atilla Eryilmaz (8)
Rayadurgam Srikant (3)
Eryilmaz Atilla (1)
Gupta Abhishek (1)
Shroff Ness B (1)
Su Yu (1)
Swati Gupta (1)
Yilin Zheng (1)

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IEEE/ACM Transactions on Networking (2)
ACM SIGMETRICS Performance Evaluation Review (1)
Proceedings of the ACM on Measurement and Analysis of Computing Systems (1)

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2016 IEEE Global Communications Conference (GLOBECOM) (1)
NIPS '20: Proceedings of the 34th International Conference on Neural Information Processing Systems (1)
NIPS '23: Proceedings of the 37th International Conference on Neural Information Processing Systems (1)
Online Learning for Optimal Control of Communication and Computing Systems (1)
SIGMETRICS '19: Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems (1)

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Proceedings (4)
Journals (3)
Doctoral Theses (1)
Newsletters (1)

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Research Article (7)
Extended Abstract (1)

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Association for Computing Machinery (3)
IEEE Press (3)
Curran Associates Inc. (2)
The Ohio State University (1)

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research-article
Fast Online Learning of Vulnerabilities for Networks With Propagating Failures
- Yilin Zheng
  Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH, USA
  ,
- Semih Cayci
  Department of Mathematics, RWTH Aachen University, Aachen, Germany
  ,
- Atilla Eryilmaz
  Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH, USA
IEEE/ACM Transactions on Networking, Volume 32, Issue 5•Oct. 2024, pp 4025-4039 • https://doi.org/10.1109/TNET.2024.3405798
In real-world networks, we regularly face the effect of propagating failures over networks, for example, rumors spread over social networks, outages spread over power networks, viruses spread over communication and biological networks. Often, these ...
0Citation
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research-article
Provably robust temporal difference learning for heavy-tailed rewards
- Semih Cayci
  Department of Mathematics, RWTH Aachen University, Aachen, Germany
  ,
- Atilla Eryilmaz
  Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH
NIPS '23: Proceedings of the 37th International Conference on Neural Information Processing Systems•December 2023, Article No.: 1117, pp 25693-25711

In a broad class of reinforcement learning applications, stochastic rewards have heavy-tailed distributions, which lead to infinite second-order moments for stochastic (semi)gradients in policy evaluation and direct policy optimization. In such instances,...
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Supplementary Material
3666122.3667239_supp.pdf
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free
Group-fair online allocation in continuous time
- Semih Cayci
  Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL
  ,
- Swati Gupta
  H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA
  ,
- Atilla Eryilmaz
  Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH
NIPS '20: Proceedings of the 34th International Conference on Neural Information Processing Systems•December 2020, Article No.: 1153, pp 13750-13761

The theory of discrete-time online learning has been successfully applied in many problems that involve sequential decision-making under uncertainty. However, in many applications including contractual hiring in online freelancing platforms and server ...
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Doctoral Theses
Online Learning for Optimal Control of Communication and Computing Systems
- Semih Cayci
  The Ohio State University
  ,
- Eryilmaz, Atilla
  The Ohio State University
  ,
- Shroff, Ness B.
  The Ohio State University
  ,
- Gupta, Abhishek
  The Ohio State University
  ,
- Su, Yu
  The Ohio State University
Abstract
With the rapid advances in device technology and computational resources, the performance of communication and computing systems achieved a massive breakthrough recently. Proportional to these improvements, new services developed on these systems ...
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research-article
Published By ACM
Published By ACM
Learning to Control Renewal Processes with Bandit Feedback
- Semih Cayci
  The Ohio State University, Columbus, OH, USA
  ,
- Atilla Eryilmaz
  The Ohio State University, Columbus, OH, USA
  ,
- R. Srikant
  CSL and ECE, UIUC, Champaign, IL, USA
ACM SIGMETRICS Performance Evaluation Review, Volume 47, Issue 1•June 2019, pp 41-42 • https://doi.org/10.1145/3376930.3376957

We consider a bandit problem with K task types from which the controller activates one task at a time. Each task takes a random and possibly heavy-tailed completion time, and a reward is obtained only after the task is completed. The task types are ...
0Citation
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extended-abstract
Public Access
Published By ACM
Published By ACM
Learning to Control Renewal Processes with Bandit Feedback
- Semih Cayci
  The Ohio State University, Columbus, OH, USA
  ,
- Atilla Eryilmaz
  The Ohio State University, Columbus, OH, USA
  ,
- R. Srikant
  University of Illinois at Urbana-Champaign, Urbana, IL, USA
SIGMETRICS '19: Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems•June 2019, pp 41-42• https://doi.org/10.1145/3309697.3331515

We consider a bandit problem with K task types from which the controller activates one task at a time. Each task takes a random and possibly heavy-tailed completion time, and a reward is obtained only after the task is completed. The task types are ...
2Citation
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research-article
Public Access
Published By ACM
Published By ACM
Learning to Control Renewal Processes with Bandit Feedback
- Semih Cayci
  The Ohio State University, Columbus, OH, USA
  ,
- Atilla Eryilmaz
  The Ohio State University, Columbus, OH, USA
  ,
- R. Srikant
  University of Illinois at Urbana-Champaign, Urbana, IL, USA
Proceedings of the ACM on Measurement and Analysis of Computing Systems, Volume 3, Issue 2•June 2019, Article No.: 43, pp 1-32 • https://doi.org/10.1145/3341617.3326158

We consider a bandit problem with K task types from which the controller activates one task at a time. Each task takes a random and possibly heavy-tailed completion time, and a reward is obtained only after the task is completed. The task types are ...
12Citation
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research-article
Optimal Learning for Dynamic Coding in Deadline-Constrained Multi-Channel Networks
- Semih Cayci
  The Ohio State University, Columbus, OH, USA
  ,
- Atilla Eryilmaz
  The Ohio State University, Columbus, OH, USA
IEEE/ACM Transactions on Networking, Volume 27, Issue 3•June 2019, pp 1043-1054 • https://doi.org/10.1109/TNET.2019.2913666

We study the problem of serving randomly arriving and delay-sensitive traffic over a multi-channel communication system with time-varying channel states and unknown statistics. This problem deviates from the classical exploration-exploitation setting in ...
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research-article
On the Multi-Channel Capacity Gains of Millimeter-Wave Communication
- Semih Cayci,
- Atilla Eryilmaz
2016 IEEE Global Communications Conference (GLOBECOM)•December 2016, pp 1-6• https://doi.org/10.1109/GLOCOM.2016.7842058
Advances in millimeter-wave (mmW) communication open up a vast frequency band, from 30 - 300 GHz, for use in mobile communication systems. However, these new frequencies exhibit highly variable and intermittent channel characteristics. In this work, we ...
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Author Profile Pages

Description: The Author Profile Page initially collects all the professional information known about authors from the publications record as known by the ACM bibliographic database, the Guide. Coverage of ACM publications is comprehensive from the 1950's. Coverage of other publishers generally starts in the mid 1980's. The Author Profile Page supplies a quick snapshot of an author's contribution to the field and some rudimentary measures of influence upon it. Over time, the contents of the Author Profile page may expand at the direction of the community.
Please see the following 2007 Turing Award winners' profiles as examples:
History: Disambiguation of author names is of course required for precise identification of all the works, and only those works, by a unique individual. Of equal importance to ACM, author name normalization is also one critical prerequisite to building accurate citation and download statistics. For the past several years, ACM has worked to normalize author names, expand reference capture, and gather detailed usage statistics, all intended to provide the community with a robust set of publication metrics. The Author Profile Pages reveal the first result of these efforts.
Normalization: ACM uses normalization algorithms to weigh several types of evidence for merging and splitting names.
These include:
- co-authors: if we have two names and cannot disambiguate them based on name alone, then we see if they have a co-author in common. If so, this weighs towards the two names being the same person.
- affiliations: names in common with same affiliation weighs toward the two names being the same person.
- publication title: names in common whose works are published in same journal weighs toward the two names being the same person.
- keywords: names in common whose works address the same subject matter as determined from title and keywords, weigh toward being the same person.
The more conservative the merging algorithms, the more bits of evidence are required before a merge is made, resulting in greater precision but lower recall of works for a given Author Profile. Many bibliographic records have only author initials. Many names lack affiliations. With very common family names, typical in Asia, more liberal algorithms result in mistaken merges.

Automatic normalization of author names is not exact. Hence it is clear that manual intervention based on human knowledge is required to perfect algorithmic results. ACM is meeting this challenge, continuing to work to improve the automated merges by tweaking the weighting of the evidence in light of experience.
Bibliometrics: In 1926, Alfred Lotka formulated his power law (known as Lotka's Law) describing the frequency of publication by authors in a given field. According to this bibliometric law of scientific productivity, only a very small percentage (~6%) of authors in a field will produce more than 10 articles while the majority (perhaps 60%) will have but a single article published. With ACM's first cut at author name normalization in place, the distribution of our authors with 1, 2, 3..n publications does not match Lotka's Law precisely, but neither is the distribution curve far off. For a definition of ACM's first set of publication statistics, see Bibliometrics
Future Direction: The initial release of the Author Edit Screen is open to anyone in the community with an ACM account, but it is limited to personal information. An author's photograph, a Home Page URL, and an email may be added, deleted or edited. Changes are reviewed before they are made available on the live site.
ACM will expand this edit facility to accommodate more types of data and facilitate ease of community participation with appropriate safeguards. In particular, authors or members of the community will be able to indicate works in their profile that do not belong there and merge others that do belong but are currently missing.

A direct search interface for Author Profiles will be built.

An institutional view of works emerging from their faculty and researchers will be provided along with a relevant set of metrics.

It is possible, too, that the Author Profile page may evolve to allow interested authors to upload unpublished professional materials to an area available for search and free educational use, but distinct from the ACM Digital Library proper. It is hard to predict what shape such an area for user-generated content may take, but it carries interesting potential for input from the community.

Bibliometrics

The ACM DL is a comprehensive repository of publications from the entire field of computing.

It is ACM's intention to make the derivation of any publication statistics it generates clear to the user.

Average citations per article = The total Citation Count divided by the total Publication Count.
Citation Count = cumulative total number of times all authored works by this author were cited by other works within ACM's bibliographic database. Almost all reference lists in articles published by ACM have been captured. References lists from other publishers are less well-represented in the database. Unresolved references are not included in the Citation Count. The Citation Count is citations TO any type of work, but the references counted are only FROM journal and proceedings articles. Reference lists from books, dissertations, and technical reports have not generally been captured in the database. (Citation Counts for individual works are displayed with the individual record listed on the Author Page.)
Publication Count = all works of any genre within the universe of ACM's bibliographic database of computing literature of which this person was an author. Works where the person has role as editor, advisor, chair, etc. are listed on the page but are not part of the Publication Count.
Publication Years = the span from the earliest year of publication on a work by this author to the most recent year of publication of a work by this author captured within the ACM bibliographic database of computing literature (The ACM Guide to Computing Literature, also known as "the Guide".
Available for download = the total number of works by this author whose full texts may be downloaded from an ACM full-text article server. Downloads from external full-text sources linked to from within the ACM bibliographic space are not counted as 'available for download'.
Average downloads per article = The total number of cumulative downloads divided by the number of articles (including multimedia objects) available for download from ACM's servers.
Downloads (cumulative) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server since the downloads were first counted in May 2003. The counts displayed are updated monthly and are therefore 0-31 days behind the current date. Robotic activity is scrubbed from the download statistics.
Downloads (12 months) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server over the last 12-month period for which statistics are available. The counts displayed are usually 1-2 weeks behind the current date. (12-month download counts for individual works are displayed with the individual record.)
Downloads (6 weeks) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server over the last 6-week period for which statistics are available. The counts displayed are usually 1-2 weeks behind the current date. (6-week download counts for individual works are displayed with the individual record.)

ACM Author-Izer Service

Summary Description

ACM Author-Izer is a unique service that enables ACM authors to generate and post links on both their homepage and institutional repository for visitors to download the definitive version of their articles from the ACM Digital Library at no charge.

Downloads from these sites are captured in official ACM statistics, improving the accuracy of usage and impact measurements. Consistently linking to definitive version of ACM articles should reduce user confusion over article versioning.

ACM Author-Izer also extends ACM’s reputation as an innovative “Green Path” publisher, making ACM one of the first publishers of scholarly works to offer this model to its authors.

To access ACM Author-Izer, authors need to establish a free ACM web account. Should authors change institutions or sites, they can utilize the new ACM service to disable old links and re-authorize new links for free downloads from a different site.

How ACM Author-Izer Works

Authors may post ACM Author-Izer links in their own bibliographies maintained on their website and their own institution’s repository. The links take visitors to your page directly to the definitive version of individual articles inside the ACM Digital Library to download these articles for free.

The Service can be applied to all the articles you have ever published with ACM.

Depending on your previous activities within the ACM DL, you may need to take up to three steps to use ACM Author-Izer.

For authors who do not have a free ACM Web Account:

Go to the ACM DL http://dl.acm.org/ and click SIGN UP. Once your account is established, proceed to next step.

For authors who have an ACM web account, but have not edited their ACM Author Profile page:

Sign in to your ACM web account and go to your Author Profile page. Click "Add personal information" and add photograph, homepage address, etc. Click ADD AUTHOR INFORMATION to submit change. Once you receive email notification that your changes were accepted, you may utilize ACM Author-izer.

For authors who have an account and have already edited their Profile Page:

Sign in to your ACM web account, go to your Author Profile page in the Digital Library, look for the ACM Author-izer link below each ACM published article, and begin the authorization process. If you have published many ACM articles, you may find a batch Authorization process useful. It is labeled: "Export as: ACM Author-Izer Service"

ACM Author-Izer also provides code snippets for authors to display download and citation statistics for each “authorized” article on their personal pages. Downloads from these pages are captured in official ACM statistics, improving the accuracy of usage and impact measurements. Consistently linking to the definitive version of ACM articles should reduce user confusion over article versioning.

Note: You still retain the right to post your author-prepared preprint versions on your home pages and in your institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library. But any download of your preprint versions will not be counted in ACM usage statistics. If you use these AUTHOR-IZER links instead, usage by visitors to your page will be recorded in the ACM Digital Library and displayed on your page.

FAQ

Q. What is ACM Author-Izer?
A. ACM Author-Izer is a unique, link-based, self-archiving service that enables ACM authors to generate and post links on either their home page or institutional repository for visitors to download the definitive version of their articles for free.
Q. What articles are eligible for ACM Author-Izer?
A. ACM Author-Izer can be applied to all the articles authors have ever published with ACM. It is also available to authors who will have articles published in ACM publications in the future.

Q. Are there any restrictions on authors to use this service?
A. No. An author does not need to subscribe to the ACM Digital Library nor even be a member of ACM.

Q. What are the requirements to use this service?
A. To access ACM Author-Izer, authors need to have a free ACM web account, must have an ACM Author Profile page in the Digital Library, and must take ownership of their Author Profile page.

Q. What is an ACM Author Profile Page?
A. The Author Profile Page initially collects all the professional information known about authors from the publications record as known by the ACM Digital Library. The Author Profile Page supplies a quick snapshot of an author's contribution to the field and some rudimentary measures of influence upon it. Over time, the contents of the Author Profile page may expand at the direction of the community. Please visit the ACM Author Profile documentation page for more background information on these pages.

Q. How do I find my Author Profile page and take ownership?
A. You will need to take the following steps:
- Create a free ACM Web Account
- Sign-In to the ACM Digital Library
- Find your Author Profile Page by searching the ACM Digital Library for your name
- Find the result you authored (where your author name is a clickable link)
- Click on your name to go to the Author Profile Page
- Click the "Add Personal Information" link on the Author Profile Page
- Wait for ACM review and approval; generally less than 24 hours

Q. Why does my photo not appear?
A. Make sure that the image you submit is in .jpg or .gif format and that the file name does not contain special characters

Q. What if I cannot find the Add Personal Information function on my author page?
A. The ACM account linked to your profile page is different than the one you are logged into. Please logout and login to the account associated with your Author Profile Page.

Q. What happens if an author changes the location of his bibliography or moves to a new institution?
A. Should authors change institutions or sites, they can utilize ACM Author-Izer to disable old links and re-authorize new links for free downloads from a new location.

Q. What happens if an author provides a URL that redirects to the author’s personal bibliography page?
A. The service will not provide a free download from the ACM Digital Library. Instead the person who uses that link will simply go to the Citation Page for that article in the ACM Digital Library where the article may be accessed under the usual subscription rules.

However, if the author provides the target page URL, any link that redirects to that target page will enable a free download from the Service.

Q. What happens if the author’s bibliography lives on a page with several aliases?
A. Only one alias will work, whichever one is registered as the page containing the author’s bibliography. ACM has no technical solution to this problem at this time.

Q. Why should authors use ACM Author-Izer?
A. ACM Author-Izer lets visitors to authors’ personal home pages download articles for no charge from the ACM Digital Library. It allows authors to dynamically display real-time download and citation statistics for each “authorized” article on their personal site.

Q. Does ACM Author-Izer provide benefits for authors?
A. Downloads of definitive articles via Author-Izer links on the authors’ personal web page are captured in official ACM statistics to more accurately reflect usage and impact measurements.

Authors who do not use ACM Author-Izer links will not have downloads from their local, personal bibliographies counted. They do, however, retain the existing right to post author-prepared preprint versions on their home pages or institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library.

Q. How does ACM Author-Izer benefit the computing community?
A. ACM Author-Izer expands the visibility and dissemination of the definitive version of ACM articles. It is based on ACM’s strong belief that the computing community should have the widest possible access to the definitive versions of scholarly literature. By linking authors’ personal bibliography with the ACM Digital Library, user confusion over article versioning should be reduced over time.

In making ACM Author-Izer a free service to both authors and visitors to their websites, ACM is emphasizing its continuing commitment to the interests of its authors and to the computing community in ways that are consistent with its existing subscription-based access model.

Q. How do authors access ACM Author-Izer?
A. See How to Use

Q. Why can’t I find my most recent publication in my ACM Author Profile Page?
A. There is a time delay between publication and the process which associates that publication with an Author Profile Page. Right now, that process usually takes 4-8 weeks.

Q. How does ACM Author-Izer expand ACM’s “Green Path” Access Policies?
A. ACM Author-Izer extends the rights and permissions that authors retain even after copyright transfer to ACM, which has been among the “greenest” publishers. ACM enables its author community to retain a wide range of rights related to copyright and reuse of materials. They include:
- Posting rights that ensure free access to their work outside the ACM Digital Library and print publications
- Rights to reuse any portion of their work in new works that they may create
- Copyright to artistic images in ACM’s graphics-oriented publications that authors may want to exploit in commercial contexts
- All patent rights, which remain with the original owner