We introduce Multi-Conditional Learning, a framework for optimizing graphical models based not on joint likelihood, or on conditional likelihood, but based on a product of several marginal conditional likelihoods each relying on common sets of parameters from an underlying joint model and predicting different subsets of variables conditioned on other subsets. When applied to undirected models w...

in this paper the conditional location problem is discussed. conditional location problems have a wide range of applications in location science. a new meta-heuristic algorithm for solving conditional p-median problems is proposed and results are compared to those of the previous studies. this algorithm produces much better results than the previous formulations.

Given a collection of random variables i ] i2N where N is a nite nonempty set, the corresponding multiinformation function ascribes the relative entropy of the joint distribution of i ] i2A with respect to the product of distributions of individual random variables i for i 2 A to every subset A N. We argue it is a useful tool for problems concerning stochastic (conditional) dependence and indep...

The optimization of biosensing efficiency on a diamond platform depends on the successful coupling of biomolecules on the surface, and also on effective signal transduction in the biorecognition events. In terms of biofunctionalization of diamond surfaces, surface electrochemical studies of diamond modified with undecylenic acid (UA), with and without headgroup protection, were performed. The d...

We discuss theoretical aspects of the product rule for classification problems in supervised machine learning for the case of combining classifiers. We show that (1) the product rule arises from the MAP classifier supposing equivalent priors and conditional independence given a class; (2) under some conditions, the product rule is equivalent to minimizing the sum of the squared distances to the...

This paper presents multi-conditional learning (MCL), a training criterion based on a product of multiple conditional likelihoods. When combining the traditional conditional probability of “label given input” with a generative probability of “input given label” the later acts as a surprisingly effective regularizer. When applied to models with latent variables, MCL combines the structure-discov...

A metal-based matrix is usually used for the fabrication of diamond bits in order to achieve favorable properties and easy processing. In the effort to reduce the cost and to attain the desired bit properties, researchers have brought more attention to diamond composites. In this paper, Fe-based impregnated diamond composites for drill bits were fabricated by using a pressureless infiltration s...

High aspect ratio diamond nanocone arrays are formed on freestanding diamond film by means of focused ion beam (FIB) milling technology and hot-filament chemical vapor deposition (HFCVD) method. The structure and phase purity of an individual diamond nanocone are characterized by scanning electron microscopy (SEM) and micro-Raman spectroscopy. The result indicates that the diamond cones with hi...

Precise readout of spin states is crucial for any approach toward physical realization of a spin-based quantum computer and for magnetometry with single spins. Here, we report a method to strongly improve the optical readout fidelity of electron spin states associated with single nitrogen-vacancy NV centers in diamond. The signal-to-noise ratio is enhanced significantly by performing conditiona...

The aim of this work is to analyze the micro mechanisms underlying the wear of macroscale tools during diamond machining of SiCp/Al6063 composites and to develop the mechanism-based diamond wear model in relation to the dominant wear behaviors. During drilling, high volume fraction SiCp/Al6063 composites containing Cu, the dominant wear mechanisms of diamond tool involve thermodynamically activ...