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A Deterministic Parallel Algorithm for Bipartite Perfect Matching

Communications of the ACM

A fundamental quest in the theory of computing is to understand the power of randomness. It is not known whether every problem with an efficient randomized algorithm also has one that does not use randomness. One of the extensively studied problems under this theme is that of perfect matching. The perfect matching problem has a randomized parallel (NC) algorithm based on the Isolation Lemma of Mulmuley, Vazirani, and Vazirani. It is a long-standing open question whether this algorithm can be derandomized.


Senior Machine Learning Engineer, Matching

#artificialintelligence

Beat is one of the most exciting companies to ever come out of the ride-hailing space. One city at a time, all across the globe we make transportation affordable, convenient, and safe for everyone. We also help hundreds of thousands of people earn extra income as drivers. Today we are the fastest-growing ride-hailing service in Latin America. But serving millions of rides every day pales in comparison to what lies ahead.


block storm http stresser

#artificialintelligence

LAYER 4 Protection is Possible on SSL? We will Block Stressers that will start to send millions of unique requests. We will block the following attack method type: GET HTTP/1.1 (Empty Requests) request-URI: / Most People say iptables can't match encrypted requests on SSL but it's not true...


An Ultimate Guide to Matching and Propensity Score Matching

#artificialintelligence

A/B tests) are the Gold Standard in identifying the causal relationship between an intervention and an outcome. RCT's high validity originates from its tight grip over the Data Generating Process (DGP) via a randomization process, rendering the experimental groups largely comparable. Thus, we can attribute any differences in the final metrics between the experimental groups to the intervention. The downside of it is RCT is not always feasible in real-world scenarios for practical reasons. Companies don't have the Experimentation infrastructure to facilitate large-scale tests.


[Perspective] Matching markets in the digital age

Science

Recent advances in information technology are enabling new markets and revolutionizing many existing markets. For example, taxicabs used to find passengers through chance drive-bys or slow central dispatching (see the photo). Location tracking, computer navigation, and dynamic pricing now enable ride-sharing services such as Uber to offer low and consistent delay times of only a few minutes. In a recent study, Cramer and Krueger (1) show that ride-sharing has dramatically increased the usage of drivers and their cars, cutting costs for riders. The results highlight the opportunities provided by digital markets.