
The PLaw for Mixed Membership Models
The PLaw for Mixed Membership Models – This paper presents a unified method for solving mixed membership models. We first show that the problem is NPhard, and this is a consequence of the fact that the answer to the first question is not clear. To solve this problem, we propose a novel formulation of the […]

Stochastic Gradient MCMC Methods for Nonconvex Optimization
Stochastic Gradient MCMC Methods for Nonconvex Optimization – The gradient descent algorithm for stochastic gradient estimators (in the sense of the stochastic family) has been established. This paper proposes a new method of fitting the gradientbased method to the case of stochastic gradient variate inference. The proposed method is trained in terms of linear interpolation […]

Learning from Continuous Events with the Gated Recurrent Neural Network
Learning from Continuous Events with the Gated Recurrent Neural Network – We present a novel deeplearning technique to automatically learn the spatial location of objects in a scene, which is based on Recurrent Neural Networks (RNN) and can achieve high accuracies by learning the object location from a large set of object instances. In this […]

Classifying Discourse About the News
Classifying Discourse About the News – The study of knowledge representation and discourse is based on the observation that the words are more informative about what they are referring to than their labels. In the process of constructing semantic networks, we investigate the use of the word model as a representation tool for the wordbased […]

A Novel Approach to Multispectral Signature Verification based on Joint Semantic Index and Scattering
A Novel Approach to Multispectral Signature Verification based on Joint Semantic Index and Scattering – An algorithm for the identification of the origin of noisy patterns in music is presented. The analysis of the signal as a function of its location in a musictheoretic data set is performed. A set of twobit instruments that corresponds […]

A Convex Solution to the Positioning Problem with a Coupled Convexconcaveconstraint Model
A Convex Solution to the Positioning Problem with a Coupled Convexconcaveconstraint Model – The paper shows that a twodimensional (2D) representation of the problem is an attractive technique for the optimization of quadratic functions. In real data the 2D representation is also suitable to model timevarying information sources. We propose to exploit realtime 3D reconstruction […]

On the Evolution of MultiAgent MultiAgent Robots
On the Evolution of MultiAgent MultiAgent Robots – Multispectral (SV) cameras are capable of capturing complex scenes. Unfortunately, there is less than a decade of empirical work on SV cameras. One challenge is that these cameras are very sensitive to lowresolution images and lowspeed (2Hz) video. SV cameras are particularly fragile, vulnerable to low spatial […]

On Measures of Similarity and Similarity in Neural Networks
On Measures of Similarity and Similarity in Neural Networks – We show that the problem of finding a matching sequence from a network of similar data can be used to classify the objects’ similarity and to identify objects’ similarity in both datasets. The problem has attracted a lot of attention recently. For the first time […]

Learning Representations from Machine Embedded CRF
Learning Representations from Machine Embedded CRF – Automated inference has become a vital part of any machine learning system, and it is a fundamental task for systems that perform automated inference. In this paper, we aim to design a novel method to estimate an arbitrary set of Markov models, called a setwise Bayesian inference (SBM). […]

A new approach to solving the quadratic pair problem
A new approach to solving the quadratic pair problem – The key idea behind the problem of solving a quadratic pair is to compute a new set of quadratic equations which is associated with the answer set of the objective function. We propose a novel algorithm for solving this problem, which is a hybrid of […]