This paper adds a number of novel concepts into global s/t cut methods improving their efficiency and making them relevant for a wider class of applications in vision where algor...
Handling large amounts of data, such as large image databases, requires the use of approximate nearest neighbor search techniques. Recently, Hamming embedding methods such as spec...
Mathematical programs with nonlinear complementarity constraints are reformulated using better-posed but nonsmooth constraints. We introduce a class of functions, parameterized by...
Discovery of association rules is an important problem in database mining. In this paper we present new algorithms for fast association mining, which scan the database only once, ...
Mohammed Javeed Zaki, Srinivasan Parthasarathy, Mi...
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...