4 papers
Sampling via Rejection-Free Partial Neighbor Search
Sigeng Chen, Jeffrey S. Rosenthal, Aki Dote +2
The Metropolis algorithm involves producing a Markov chain to converge to a specified target density . In order to improve its efficiency, we can use the Rejection-Free version…
Derivation of QUBO formulations for sparse estimation
Tomohiro Yokota, Makiko Konoshima, Hirotaka Tamura +1
We propose a quadratic unconstrained binary optimization (QUBO) formulation of the l1-norm, which enables us to perform sparse estimation of Ising-type annealing methods such as qu…
Quadratic unconstrained binary optimization formulation for rectified-linear-unit-type functions
Go Sato, Makiko Konoshima, Takuya Ohwa +2
We propose a quadratic unconstrained binary optimization (QUBO) formulation of rectified linear unit (ReLU) type functions. Different from the q-loss function proposed by Denchev e…
Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer
Maliheh Aramon, Gili Rosenberg, Elisabetta Valiante +3
The Fujitsu Digital Annealer (DA) is designed to solve fully connected quadratic unconstrained binary optimization (QUBO) problems. It is implemented on application-specific CMOS h…