In multi-receiver Bayesian persuasion, while characterizing feasible joint belief distributions unconditionally is complex, conditioning on the state reveals a simple structure: feasibility constraints apply only to individual receivers' marginals across states, allowing arbitrary correlation within a state. This insight leads to a novel primal-dual approach for solving persuasion problems, leveraging optimal transport theory and offering tractable solutions for specific classes of problems.
西班牙大學機構知識庫中的研究數據數量有限且分佈不均,突顯出該國在開放科學數據共享和管理政策方面存在落差,需進一步發展數據策展實務以促進數據共享和再利用。
스페인 대학 저장소의 연구 데이터 현황 분석 결과, 데이터 접근성이 제한적이고, 데이터 관리 정책이 미흡하며, 메타데이터 표준화가 부족한 것으로 드러났다.
Despite existing open access policies, Spanish university repositories show limited adoption and support for open research data, highlighting a crucial need for improved data management policies, infrastructure, and practices, particularly Data Curation, to realize the full potential of open science in Spain.
AI can revolutionize data repository management by enhancing efficiency, data quality, and accessibility, but successful implementation requires a balanced approach that combines AI and human expertise.
The rise of MDPI and other similar publishers is a symptom of a broken peer review system, where elitism, bias, and inefficiency drive researchers to seek faster and less critical publication venues.
This research paper investigates and derives the optimal mechanism for a seller who possesses private information about an item's quality, aiming to maximize revenue when selling to multiple potential buyers with private valuations.
Data, as a valuable resource in the digital economy, has led to the emergence of data markets, which facilitate the buying and selling of data products and raise important considerations regarding pricing, privacy, security, and regulation.
Colleges may adopt test-optional policies not just to enhance diversity, but also to minimize social pressure stemming from disagreements over the weight placed on standardized test scores versus other admission factors.
While naive compounding of yearly returns suggests an unrealistic annualized return of over 60% for the Medallion fund, a more accurate estimation based on fund sizes and trading profits reveals a still impressive but lower return of likely under 35%.