Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Adith Swaminathan"'
Publikováno v:
AI Magazine; Vol. 42 No. 3: Fall 2021; 19-30
In recent years, a new line of research has taken an interventional view of recommender systems, where recommendations are viewed as actions that the system takes to have a desired effect. This interventional view has led to the development of counte
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4efedfdd0f6251f6bebbfbc82b9eb287
https://ojs.aaai.org/index.php/aimagazine/article/view/18141
https://ojs.aaai.org/index.php/aimagazine/article/view/18141
Publikováno v:
AAAI
The potential for using machine learning algorithms as a tool for suggesting optimal interventions has fueled significant interest in developing methods for estimating heterogeneous or individual treatment effects (ITEs) from observational data. Whil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76d28a50fd406269e8b3bdc40ef7833f
https://doi.org/10.1609/aaai.v33i01.33014544
https://doi.org/10.1609/aaai.v33i01.33014544
Autor:
Adith Swaminathan, Maria Dimakopoulou, Flavian Vasile, Thorsten Joachims, Olivier Koch, Yves Raimond
Publikováno v:
RecSys
The REVEAL workshop1 focuses on framing the recommendation problem as a one of making personalized interventions, e.g. deciding to recommend a particular item to a particular user. Moreover, these interventions sometimes depend on each other, where a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bb37c2d3f4281e6bd64cad4d09626e37
https://doi.org/10.1145/3383313.3411536
https://doi.org/10.1145/3383313.3411536
Publikováno v:
SIGMOD Conference
Recent research has shown promising results by using machine learning (ML) techniques to improve the performance of database systems, e.g., in query optimization or index recommendation. However, in many production deployments, the ML models' perform
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::131c214d9013132694eaa1757d5ff273
https://doi.org/10.1145/3318464.3389768
https://doi.org/10.1145/3318464.3389768
Autor:
Yves Raimond, Adith Swaminathan, Olivier Koch, Thorsten Joachims, Maria Dimakopoulou, Flavian Vasile
Publikováno v:
RecSys
The REVEAL workshop1 focuses on framing the recommendation problem as a one of making personalized interventions. Moreover, these interventions sometimes depend on each other, where a stream of interactions occurs between the user and the system, and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::44797b27ca885981cb1f1262e097b6a6
https://doi.org/10.1145/3298689.3346975
https://doi.org/10.1145/3298689.3346975
Autor:
Besmira Nushi, Adith Swaminathan, Eric Horvitz, Debadeepta Dey, Sean Andrist, Aditya Modi, Alekh Agarwal
Publikováno v:
AAAI
Assemblies of modular subsystems are being pressed into service to perform sensing, reasoning, and decision making in high-stakes, time-critical tasks in such areas as transportation, healthcare, and industrial automation. We address the opportunity
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::afc18f1f21071509ab9aa13f94fcfdd6
Publikováno v:
RecSys
The inaugural REVEAL workshop1 focuses on revisiting the offline evaluation problem for recommender systems. Being able to perform offline experiments is key to rapid innovation; however practitioners often observe significant differences between off
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a08f080b6a19a91d65fb5ad4573fc601
https://doi.org/10.1145/3240323.3240334
https://doi.org/10.1145/3240323.3240334
Publikováno v:
WSDM
IJCAI
IJCAI
Implicit feedback (e.g., clicks, dwell times, etc.) is an abundant source of data in human-interactive systems. While implicit feedback has many advantages (e.g., it is inexpensive to collect, user centric, and timely), its inherent biases are a key
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ae8ed1b2f551f71bb555983264654d5d
http://arxiv.org/abs/1608.04468
http://arxiv.org/abs/1608.04468
Autor:
Adith Swaminathan, Thorsten Joachims
Publikováno v:
SIGIR
Online metrics measured through A/B tests have become the gold standard for many evaluation questions. But can we get the same results as A/B tests without actually fielding a new system? And can we train systems to optimize online metrics without su
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2a6c72c53647b20c7f9782f56cbe5528
https://doi.org/10.1145/2911451.2914803
https://doi.org/10.1145/2911451.2914803
Publikováno v:
ICTIR
Eliciting relevance judgments for ranking evaluation is labor-intensive and costly, motivating careful selection of which documents to judge. Unlike traditional approaches that make this selection deterministically, probabilistic sampling has shown i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af05ab886b4968512de6f0084d9abe43
http://arxiv.org/abs/1604.07209
http://arxiv.org/abs/1604.07209