AI research is moving at breakneck pace. State-of-the-art methods seem to become obsolete almost as quickly as they are found - as practitioners, it’s important to stay on top of the field.

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I am doing a literature survey on CAPTCHAs. Can you guys point me in the direction of some seminal papers in the field?

Hi! We have this project on a course called Principles of Programming Languages where we have to create a PL that has unique principles(such as functions/staments/code) from other existing PLs.

Anyone who have some juices or suggestions? Please help this college kiddo here 🙏

http://www.cs.cmu.edu/~sandholm/onlineKidneyExchange.ijcai09.pdf

Abstract Kidneys are the most prevalent organ transplants, but demand dwarfs supply. Kidney exchanges enable willing but incompatible donor-patient pairs to swap donors. These swaps can include cycles longer than two pairs as well, and chains triggered by altruistic donors. Current kidney exchanges address clearing (deciding who gets kidneys from whom) as an offline problem: they optimize the current batch. In reality, clearing is an online problem where patient-donor pairs and altruistic donors appear and expire over time. In this paper, we study trajectory-based online stochastic optimization algorithms (which use a recent scalable optimal offline solver as a subroutine) for this. We identify tradeoffs in these algorithms between different parameters. We also uncover the need to set the batch size that the algorithms consider an atomic unit. We develop an experimental methodology for setting these parameters, and conduct experiments on real and generated data. We adapt the REGRETS algorithm of Bent and van Hentenryck for the setting. We then develop a better algorithm. We also show that the AMSAA algorithm of Mercier and van Hentenryck does not scale to the nationwide level. Our best online algorithm saves significantly more lives than the current practice of solving each batch separately.