Random Noise and Random Walk algorithms are local search strategies that have been used for the problem of satisfiability testing (SAT). We present a Markov-chain based analysis o...
Bhaskar Krishnamachari, Xi Xie, Bart Selman, Steph...
The algorithm presented here, BCC, is an enhancement of the well known Backtrack used to solve constraint satisfaction problems. Though most backtrack improvements rely on propaga...
In this paper we consider the problem of actively learning the mean values of distributions associated with a finite number of options (arms). The algorithms can select which opti...
Many intellectual property protection (IPP) techniques have been proposed. Their primary objectives are providing convincible proof of authorship with least degradation of the qua...
Following the well-studied two-stage optimization framework for stochastic optimization [15, 18], we study approximation algorithms for robust two-stage optimization problems with ...
Uriel Feige, Kamal Jain, Mohammad Mahdian, Vahab S...