基本信息
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职业迁徙
个人简介
My research lies on the intersection of machine learning and information retrieval, it primarily concerns learning from user interactions on rankings. In particular, I focus on methods that correct for the effects of interaction biases.
I’m passionate about research in Machine Learning and Information Retrieval; in particular how search and recommendation systems can learn from user interactions. While the goals of these systems is often to follow users’ preferences, the interactions of users are usually very affected by many other factors: e.g. what items are shown, the order in which they are shown, etc. As a result, these methods have to correct for these interaction biases. My research often uses theoretical methods for counterfactual estimation with machine learning approaches to optimize ranking systems.
研究兴趣
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Web Search and Data Miningpp.1118-1121, (2024)
arxiv(2024)
European Conference on Information Retrievalpp.384-402, (2024)
PROCEEDINGS OF THE 2023 ACM SIGIR INTERNATIONAL CONFERENCE ON THE THEORY OF INFORMATION RETRIEVAL, ICTIR 2023pp.87-93, (2023)
PROCEEDINGS OF THE 17TH ACM CONFERENCE ON RECOMMENDER SYSTEMS, RECSYS 2023pp.1223-1226, (2023)
PROCEEDINGS OF THE 46TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, SIGIR 2023 (2023): 249-258
Forum for Information Retrieval Evaluationpp.145-148, (2023)
PROCEEDINGS OF THE 17TH ACM CONFERENCE ON RECOMMENDER SYSTEMS, RECSYS 2023 (2023): 306-317
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