About
Activity
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📣 Next Monday, I will be giving a tutorial at #ICML2024 on "𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐭𝐡𝐞 𝐑𝐨𝐥𝐞 𝐨𝐟 𝐋𝐋𝐌𝐬 𝐢𝐧 𝐏𝐥𝐚𝐧𝐧𝐢𝐧𝐠" (Lehar…
📣 Next Monday, I will be giving a tutorial at #ICML2024 on "𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐭𝐡𝐞 𝐑𝐨𝐥𝐞 𝐨𝐟 𝐋𝐋𝐌𝐬 𝐢𝐧 𝐏𝐥𝐚𝐧𝐧𝐢𝐧𝐠" (Lehar…
Liked by Lei Tang
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It’s almost my favorite time of year: hireEZ RecruitCon! https://bit.ly/3Wfpe0I Anytime we bring the recruitment community together to share…
It’s almost my favorite time of year: hireEZ RecruitCon! https://bit.ly/3Wfpe0I Anytime we bring the recruitment community together to share…
Liked by Lei Tang
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LinkedIn! I am immeasurably delighted to share that this week, I started as the first Head of Data Science at Captions! I couldn't be more grateful…
LinkedIn! I am immeasurably delighted to share that this week, I started as the first Head of Data Science at Captions! I couldn't be more grateful…
Liked by Lei Tang
Experience & Education
Publications
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Large Scale Behavioral Targeting with a Social Twist
CIKM
Behavioral targeting (BT) is a widely used technique for online advertising. It leverages information collected on an individual's web-browsing behavior, such as page views, search queries and ad clicks, to select the ads most relevant to user to display. With the proliferation of social networks, it is possible to relate the behavior of individuals and their social connections. Although the similarity among connected individuals are well established (i.e., homophily), it is still not clear…
Behavioral targeting (BT) is a widely used technique for online advertising. It leverages information collected on an individual's web-browsing behavior, such as page views, search queries and ad clicks, to select the ads most relevant to user to display. With the proliferation of social networks, it is possible to relate the behavior of individuals and their social connections. Although the similarity among connected individuals are well established (i.e., homophily), it is still not clear whether and how we can leverage the activities of one's friends for behavioral targeting; whether forecasts derived from such social information are more accurate than standard behavioral targeting models. In this paper, we strive to answer these questions by evaluating the predictive power of social data across 60 consumer domains on a large online network of over 180 million users in a period of two and a half months. To our best knowledge, this is the most comprehensive study of social data in the context of behavioral targeting on such an unprecedented scale. Our analysis offers interesting insights into the value of social data for developing the next generation of targeting services.
Other authorsSee publication -
Community Detection and Mining in Social Media
Morgan & Claypool Publishers
The past decade has witnessed the emergence of participatory Web and social media, bringing people together in many creative ways. Millions of users are playing, tagging, working, and socializing online, demonstrating new forms of collaboration, communication, and intelligence that were hardly imaginable just a short time ago. Social media also helps reshape business models, sway opinions and emotions, and opens up numerous possibilities to study human interaction and collective behavior in an…
The past decade has witnessed the emergence of participatory Web and social media, bringing people together in many creative ways. Millions of users are playing, tagging, working, and socializing online, demonstrating new forms of collaboration, communication, and intelligence that were hardly imaginable just a short time ago. Social media also helps reshape business models, sway opinions and emotions, and opens up numerous possibilities to study human interaction and collective behavior in an unparalleled scale. This lecture, from a data mining perspective, introduces characteristics of social media, reviews representative tasks of computing with social media, and illustrates associated challenges. It introduces basic concepts, presents state-of-the-art algorithms with easy-to-understand examples, and recommends effective evaluation methods. In particular, we discuss graph-based community detection techniques and many important extensions that handle dynamic, heterogeneous networks in social media. We also demonstrate how discovered patterns of communities can be used for social media mining. The concepts, algorithms, and methods presented in this lecture can help harness the power of social media and support building socially-intelligent systems. This book is an accessible introduction to the study of \emph{community detection and mining in social media}. It is an essential reading for students, researchers, and practitioners in disciplines and applications where social media is a key source of data that piques our curiosity to understand, manage, innovate, and excel.
This book is supported by additional materials, including lecture slides, the complete set of figures, key references, some toy data sets used in the book, and the source code of representative algorithms. The readers are encouraged to visit the book website
(http://dmml.asu.edu/cdm/) for the latest information.
Other authorsSee publication -
Large Scale Multi-Label Classification via MetaLabeler
WWW
The explosion of online content has made the management of such content non-trivial. Web-related tasks such as web page categorization, news filtering, query categorization, tag recommendation, etc. often involve the construction of multi-label categorization systems on a large scale. Existing multi-label classification methods either do not scale or have unsatisfactory performance. In this work, we propose MetaLabeler to automatically determine the relevant set of labels for each instance…
The explosion of online content has made the management of such content non-trivial. Web-related tasks such as web page categorization, news filtering, query categorization, tag recommendation, etc. often involve the construction of multi-label categorization systems on a large scale. Existing multi-label classification methods either do not scale or have unsatisfactory performance. In this work, we propose MetaLabeler to automatically determine the relevant set of labels for each instance without intensive human involvement or expensive cross-validation. Extensive experiments conducted on benchmark data show that the MetaLabeler tends to outperform existing methods. Moreover, MetaLabeler scales to millions of multi-labeled instances and can be deployed easily. This enables us to apply the MetaLabeler to a large scale query categorization problem in Yahoo!, yielding a significant improvement in performance.
Other authorsSee publication
Patents
More activity by Lei
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Compound AI Systems combine specialized models, retrievers, and external tools for specific tasks, offering greater flexibility and performance…
Compound AI Systems combine specialized models, retrievers, and external tools for specific tasks, offering greater flexibility and performance…
Liked by Lei Tang
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BIG NEWS: Data Council is headed BACK TO THE BAY baby. Since 2013 we've been bringing together the brightest minds in data to share their OSS tools,…
BIG NEWS: Data Council is headed BACK TO THE BAY baby. Since 2013 we've been bringing together the brightest minds in data to share their OSS tools,…
Liked by Lei Tang
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Amazing to see Nir Even-Chen delivering the latest Neuralink update next to Elon Musk. I remember a few months after him joining the research…
Amazing to see Nir Even-Chen delivering the latest Neuralink update next to Elon Musk. I remember a few months after him joining the research…
Liked by Lei Tang
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As AI's become agents, it will be critical they understand the large scale, long term effects of their behavior. Towards this, I've released a new…
As AI's become agents, it will be critical they understand the large scale, long term effects of their behavior. Towards this, I've released a new…
Liked by Lei Tang
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I'm thrilled to share that I have joined Ascendion as their Chief AI Officer! This is an incredible opportunity to leverage my experience in AI and…
I'm thrilled to share that I have joined Ascendion as their Chief AI Officer! This is an incredible opportunity to leverage my experience in AI and…
Liked by Lei Tang
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Asian American Scholar Forum organized the first Asian American Pioneer Medal Symposium to be held in Stanford Memorial Auditorium on July 27th 2024.…
Asian American Scholar Forum organized the first Asian American Pioneer Medal Symposium to be held in Stanford Memorial Auditorium on July 27th 2024.…
Liked by Lei Tang
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Upstart's Analytics team is hiring multiple positions leading strategic and highly visible initiatives to enable effortless credit based on true…
Upstart's Analytics team is hiring multiple positions leading strategic and highly visible initiatives to enable effortless credit based on true…
Liked by Lei Tang
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Some days I feel like a loser. This is not a post asking for pity. I'm just being honest about the ups and downs of life, in case someone out there…
Some days I feel like a loser. This is not a post asking for pity. I'm just being honest about the ups and downs of life, in case someone out there…
Liked by Lei Tang
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We are happy to share that we released Python Polars 1.0! Read more in our announcement post: https://lnkd.in/eXpqRpCn. To help you upgrade, read…
We are happy to share that we released Python Polars 1.0! Read more in our announcement post: https://lnkd.in/eXpqRpCn. To help you upgrade, read…
Liked by Lei Tang
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After an incredible journey spanning a little over two years, the time has come for me to bid farewell to NVIDIA. It has been an honor and privilege…
After an incredible journey spanning a little over two years, the time has come for me to bid farewell to NVIDIA. It has been an honor and privilege…
Liked by Lei Tang
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