Zobrazeno 1 - 10
of 180
pro vyhledávání: '"ŞAHİN, Cem"'
Publikováno v:
In Journal of Environmental Management November 2024 370
Decision making in crucial applications such as lending, hiring, and college admissions has witnessed increasing use of algorithmic models and techniques as a result of a confluence of factors such as ubiquitous connectivity, ability to collect, aggr
Externí odkaz:
http://arxiv.org/abs/2007.15270
Autor:
Koester, Evan, Sahin, Cem Safak
As Super-Resolution (SR) has matured as a research topic, it has been applied to additional topics beyond image reconstruction. In particular, combining classification or object detection tasks with a super-resolution preprocessing stage has yielded
Externí odkaz:
http://arxiv.org/abs/1907.05283
Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search
We present a framework for quantifying and mitigating algorithmic bias in mechanisms designed for ranking individuals, typically used as part of web-scale search and recommendation systems. We first propose complementary measures to quantify bias wit
Externí odkaz:
http://arxiv.org/abs/1905.01989
Previous efforts in recommendation of candidates for talent search followed the general pattern of receiving an initial search criteria and generating a set of candidates utilizing a pre-trained model. Traditionally, the generated recommendations are
Externí odkaz:
http://arxiv.org/abs/1809.06488
Autor:
Geyik, Sahin Cem, Guo, Qi, Hu, Bo, Ozcaglar, Cagri, Thakkar, Ketan, Wu, Xianren, Kenthapadi, Krishnaram
LinkedIn Talent Solutions business contributes to around 65% of LinkedIn's annual revenue, and provides tools for job providers to reach out to potential candidates and for job seekers to find suitable career opportunities. LinkedIn's job ecosystem h
Externí odkaz:
http://arxiv.org/abs/1809.06481
Autor:
Ramanath, Rohan, Inan, Hakan, Polatkan, Gungor, Hu, Bo, Guo, Qi, Ozcaglar, Cagri, Wu, Xianren, Kenthapadi, Krishnaram, Geyik, Sahin Cem
Talent search and recommendation systems at LinkedIn strive to match the potential candidates to the hiring needs of a recruiter or a hiring manager expressed in terms of a search query or a job posting. Recent work in this domain has mainly focused
Externí odkaz:
http://arxiv.org/abs/1809.06473
Publikováno v:
KDD 2016 Workshop on Enterprise Intelligence
In online advertising, our aim is to match the advertisers with the most relevant users to optimize the campaign performance. In the pursuit of achieving this goal, multiple data sources provided by the advertisers or third-party data providers are u
Externí odkaz:
http://arxiv.org/abs/1711.11175
Word embedding models offer continuous vector representations that can capture rich contextual semantics based on their word co-occurrence patterns. While these word vectors can provide very effective features used in many NLP tasks such as clusterin
Externí odkaz:
http://arxiv.org/abs/1702.07680
Although it is common for users to select bad passwords that can be easily cracked by attackers, password-based authentication remains the most widely-used method. To encourage users to select good passwords, enterprises often enforce policies. Such
Externí odkaz:
http://arxiv.org/abs/1512.05814