We consider the problem of using nearest neighbor methods to provide a conditional probability estimate, P (y|a), when the number of labels y is large and the labels share some underlying structure. We propose a method for learning label embeddings (similar to error-correcting output codes (ECOCs)) to model the similarity between labels within a nearest neighbor framework. The learned ECOCs and...

Collection of appropriate qualitative and quantitative data is necessary for proper management and planning. Used the suitable inventory methods is necessary and accuracy of sampling methods dependent the inventory net and number of sample point. Nearest neighbor sampling method is a one of distance methods and calculated by three equations (Byth and Riple, 1980; Cotam and Curtis, 1956 and Cota...

We contribute a 2D nearest-neighbor quantum architecture for Shor’s algorithm to factor an n-bit number in O(log2(n)) depth. Our implementation uses parallel phase estimation, constant-depth fanout and teleportation, and constant-depth carry-save modular addition. We derive upper bounds on the circuit resources of our architecture under a new 2D nearest-neighbor model which allows a classical c...

The two-dimensional Kondo lattice model with both nearest and next-nearest neighbor exchange interactions is studied within a mean-field approach and its phase diagram is determined. In particular, we allow for lattice translation symmetry breaking. We observe that the usual uniform intersite order parameter is never realized, being unstable towards other more complex types of order. When the n...

collection of appropriate qualitative and quantitative data is necessary for proper management and planning. used the suitable inventory methods is necessary and accuracy of sampling methods dependent the inventory net and number of sample point. nearest neighbor sampling method is a one of distance methods and calculated by three equations (byth and riple, 1980; cotam and curtis, 1956 and cota...