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...oreover, this randomized algorithm plays against adaptive adversaries. Our algorithms are the first to break the <math>O(mn)</math> bound with adaptive adversari ...supervised by Professor Hanpin Wang. His research focuses on approximation algorithms for counting and sampling problems. Typical problems include computing marg ...

...oreover, this randomized algorithm plays against adaptive adversaries. Our algorithms are the first to break the <math>O(mn)</math> bound with adaptive adversari ...supervised by Professor Hanpin Wang. His research focuses on approximation algorithms for counting and sampling problems. Typical problems include computing marg ...

...ople's incentives can affect the learning problems, and to design reliable algorithms that perform well in these strategic environments. ...discuss two lines of my work that address these challenges: designing fast algorithms that are provably robust for several fundamental problems in machine learni ...

....cs.umd.edu/~amchilds/qa/qa.pdf Andrew M. Childs. Lecture Notes on Quantum Algorithms. 30 May 2017] ...

...n.jpeg|border|100px]]||P. J. Cameron. ''Combinatorics: Topics, Techniques, Algorithms.'' Cambridge University Press, 1995. ...

...oreover, this randomized algorithm plays against adaptive adversaries. Our algorithms are the first to break the <math>O(mn)</math> bound with adaptive adversari ...supervised by Professor Hanpin Wang. His research focuses on approximation algorithms for counting and sampling problems. Typical problems include computing marg ...

This course will study ''Randomized Algorithms'', the algorithms that use randomness in computation. * Randomized algorithms can be simpler than deterministic ones. ...

This course will study ''Randomized Algorithms'', the algorithms that use randomness in computation. * Randomized algorithms can be simpler than deterministic ones. ...

[[Category:Randomised algorithms]] ...

;Oblivious routing algorithms ...ven more oblivious than this standard definition.) Compared to the routing algorithms which are adaptive to the path that the packet traversed, oblivious routing ...

...ized algorithms look like. Two basic principles are used to analyze these algorithms: linearity of expectations, and independence of events. ...ant classes of randomized algorithms: Las Vegas algorithms and Monte Carlo algorithms. I will introduce their definitions at the end of this lecture. ...

: Efficient Algorithms and Data Structures for Geometric Computing [https://www.amazon.com/Distributed-Algorithms-Kaufmann-Management-Systems/dp/1558603484 Book Chapter 6.7], [https://group ...

...has been successfully applied in the analysis of many approximate counting algorithms. In this talk, I will demostrate the general idea behind this technique and ...

== Distributed algorithms == ...

...]]. Some people like trying to find big primes. Since there are tricks and algorithms to finding Mersenne primes quickly, the largest known primes are also Merse ...

:<font size=3>'''Title''': Data Driven Algorithms for Assortment Planning</font> ...ly learn consumers’ model and optimize assortment selection decisions. Our algorithms’ performance guarantees surprisingly do not depend on the number of candida ...

...raphs] have found extensive applications in computer science, in designing algorithms, [http://en.wikipedia.org/wiki/Error_correcting_code error correcting codes ...te. Studies of these two problems revolutionized the area of approximation algorithms. ...

== Algorithms == ...

...ction estimation is the most important part of most reinforcement learning algorithms. ...

...i> T.H. Cormen， C.E. Leiserson， R.L. Rivest， and C. Stein. Introduction to Algorithms.] .... A Reliable Randomized Algorithm for the Closest-Pair Problem. Journal of Algorithms， 25(1):19{51， 1997.] ...