Kernelization algorithms are polynomial-time reductions from a problem to itself that guarantee their output to have a size not exceeding some bound. For example, d-Set Matching f...
Optimized solvers for the Boolean Satisfiability (SAT) problem have many applications in areas such as hardware and software verification, FPGA routing, planning, etc. Further use...
Fadi A. Aloul, Arathi Ramani, Igor L. Markov, Kare...
This paper examines important factors for link prediction in networks and provides a general, high-performance framework for the prediction task. Link prediction in sparse network...
Ryan Lichtenwalter, Jake T. Lussier, Nitesh V. Cha...
In the course of developing a system for fitting smooth curves to camera input we have developed several direct (i.e. noniterative) methods for fitting a shape (line, circle, conic...
In supervised learning, a training set consisting of labeled instances is used by a learning algorithm for generating a model (classifier) that is subsequently employed for decidi...