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Adversarial combinatorial bandits for imperfect-information sequential games


Abstract: This talk will focus on learning policies for tree-form decision problems (extensive-form games) from adversarial feedback. In principle, one could convert learning in any extensive-form game (EFG) into learning in an equivalent normal-form game (NFG), that is, a multi-armed bandit problem with one arm per tree-form policy. However, doing so comes at the cost of an exponential blowup of the strategy space. So, progress on NFGs and EFGs has historically followed separate tracks, with the EFG community often having…

Matrix displacement convexity and intrinsic dimensionality


Abstract: The space of probability measures endowed with the optimal transport metric has a rich structure with applications in probability, analysis, and geometry. The notion of (displacement) convexity in this space was discovered by McCann, and forms the backbone of this theory.  I will introduce a new, and stronger, notion of displacement convexity which operates on the matrix level. The motivation behind this definition is to capture the intrinsic dimensionality of probability measures which could have very different behaviors along…

Clean Electricity and the Path to Net Zero: Methods and Insights


Abstract: The electricity sector is the linchpin in any path to net-zero greenhouse gas emissions. Electricity sector emissions must fall faster and deeper than any other sector, while simultaneously expanding to power greater shares of energy consumption in transportation, heating, industry and the production of clean fuels. How do we build the grid we need to decarbonize the economy? Prof. Jenkins will share insights from a decade of research on low-carbon electricity systems and pathways to a net-zero America and discuss novel methods…

MIT Institute for Data, Systems, and Society
Massachusetts Institute of Technology
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Cambridge, MA 02139-4307