Yexi Jiang

San Francisco Bay Area
3K followers 500+ connections

Join to view profile

About

Yexi brings a diverse set of experiences, combining software engineering, open-source…

Articles by Yexi

See all articles

Activity

Join now to see all activity

Experience & Education

  • Meta

View Yexi’s full experience

See their title, tenure and more.

or

By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.

Publications

  • Personalized Recommendation via Parameter-Free Contextual Bandits

    The 38th ACM SIGIR Conference

    Personalized recommendation services have gained increasing popularity and attention in recent years as most useful information can be accessed online in real-time. Most online recommender systems try to address the information needs of users by virtue of both user and content information. Despite extensive recent advances, the problem of personalized recommendation remains challenging for at least two reasons. First, the user and item repositories undergo frequent changes, which makes…

    Personalized recommendation services have gained increasing popularity and attention in recent years as most useful information can be accessed online in real-time. Most online recommender systems try to address the information needs of users by virtue of both user and content information. Despite extensive recent advances, the problem of personalized recommendation remains challenging for at least two reasons. First, the user and item repositories undergo frequent changes, which makes traditional recommendation algorithms ineffective. Second, the so-called cold-start problem is difficult to address, as the information for learning a recommendation model is limited for new items or new users. Both challenges are formed by the dilemma of exploration and exploitation.
    In this paper, we formulate personalized recommendation as a contextual bandit problem to solve the exploration/exploitation dilemma. Specifically in our work, we propose a parameter-free bandit strategy, which employs a principled resampling approach called online bootstrap, to derive the distribution of estimated models in an online manner. Under the paradigm of probability matching, the proposed algorithm randomly samples a model from the derived distribution for every recommendation. Extensive empirical experiments on two real-world collections of web data (including online advertising and news recommendation) demonstrate the effectiveness of the proposed algorithm in terms of the click-through rate. The experimental results also show that this proposed algorithm is robust in the cold-start situation, in which there is no sufficient data or knowledge to tune the parameters.

    Other authors
    See publication

  • Please check my Google Scholar profile for details

    -

    Paper published in ICDM, KDD, CIKM, SDM, RecSys, SIGIR, TKDE, SCC, etc.

    See publication

  • Program Committee Member of Top International Conferences in the Area of Data Science

    -

    - ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD)
    - ACM Conference on Recommender Systems (RecSys)
    - IEEE/ACM Conference on Advances in Social Networks Analysis and Mining (ASONAM)
    - International Workshop on Machine Learning, Optimization, and Big Data (MOD)
    - International Conference on Service Computing (SCC)

  • Reviewer of Top Academic Journals in the Area of Data Science

    -

    - IEEE Transactions on Knowledge and Data Engineering (TKDE)
    - ACM Transactions on Knowledge Discovery from Data (TKDD)
    - Knowledge and Information System (KAIS)
    - Information Sciences
    - IEEE Transactions on Cybernetics
    - Data and Knowledge Engineering (DKE)

Languages

  • Chinese

    Native or bilingual proficiency

  • English

    Full professional proficiency

  • Spanish

    Elementary proficiency

More activity by Yexi

View Yexi’s full profile

  • See who you know in common
  • Get introduced
  • Contact Yexi directly
Join to view full profile

Other similar profiles

Explore top content on LinkedIn

Find curated posts and insights for relevant topics all in one place.

View top content

Others named Yexi Jiang

6 others named Yexi Jiang are on LinkedIn

See others named Yexi Jiang

Add new skills with these courses

See all courses