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Algorithms
Data Science
Artificial Intelligence
Title: A Multi-Dimensional Online Contention Resolution Scheme for Revenue Maximization
Speaker: Dimitris Christou, PhD Student at UT Austin
Abstract: We study multi-buyer multi-item sequential item pricing mechanisms for online revenue maximization with the goal of approximating a natural fractional relaxation – the ex ante optimal revenue. We assume that buyers’ values are subadditive but make no assumptions on the value distributions. While the optimal revenue, and therefore also the ex ante benchmark, is inapproximable by any simple mechanism in this context, previous work has shown that a weaker benchmark that optimizes over so-called “buy-many” mechanisms can be approximated. Approximations are known, in particular, for settings with either a single buyer or many unit-demand buyers. We extend these results to the much broader setting of many subadditive buyers. We show that the ex ante buy-many revenue can be approximated via sequential item pricings to within an $O(log^2 m)$ factor, where m is the number of items. We also show that a logarithmic dependence on m is necessary. Our approximation is achieved through the construction of a new multi-dimensional Online Contention Resolution Scheme (OCRS), that provides an online rounding of the optimal ex ante solution.
Bio: Dimitris Christou is a 3rd year Computer Science PhD student at UT Austin. He is fortunate to be advised by Prof. Shuchi Chawla. Prior to joining UT Austin, he received a Diploma in Electrical and Computer Engineering from the National Technical University
of Athens, supervised by Prof. Dimitris Fotakis. During that time, he completed two research internships offered by the LIP6 Research Institute at Sorbonne University, France. His research interests lie in the intersection of Online Algorithms, Economics and
Data-Driven algorithmic design. His previous work resolves open questions for online decision making, server problems, multistage optimisation and learning-augmented algorithms. His current work focuses on problems in the intersection of Online Decision Making
and Economics, such as the Pandora’s Box problem and Online Revenue Maximization.
To position Greece as a leading player in AI and Data Science
To build an AI Excellence Hub in Greece where the international research community can connect, groundbreaking ideas can thrive, and the next generation of scientists emerges, shaping a brighter future for Greece and the world
Welcome to ARCHIMEDES, a vibrant research hub connecting the global AI and Data Science research community fostering groundbreaking research in Greece and beyond. Its dedicated core team, comprising lead researchers, affiliated researchers, Post-Docs, PhDs and interns, is committed to advancing basic and applied research in Artificial Intelligence and its supporting disciplines, including Algorithms, Statistics, Learning Theory, and Game Theory organized around 8 core research areas. By collaborating with Greek and Foreign Universities and Research Institutes, ARCHIMEDES disseminates its research findings fostering knowledge exchange and providing enriching opportunities for students. Leveraging AI to address real-world challenges, ARCHIMEDES promotes innovation within the Greek ecosystem and extends its societal impact. Established in January 2022, as a research unit of the Athena Research Center with support from the Committee Greece 2021, ARCHIMEDES is funded for its first four years by the EU Recovery and Resilience Facility (RRF).
The project “ARCHIMEDES Unit: Research in Artificial Intelligence, Data Science and Algorithms” with code OPS 5154714 is implemented by the National Recovery and Resilience Plan “Greece 2.0” and is funded by the European Union – NextGenerationEU.
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