Search results for "Maximization"
showing 10 items of 84 documents
Simulated one-pass list-mode: an approach to on-the-fly system matrix calculation.
2013
In the development of prototype systems for positron emission tomography a valid and robust image reconstruction algorithm is required. However, prototypes often employ novel detector and system geometries which may change rapidly under optimization. In addition, developing systems generally produce highly granular, or possibly continuous detection domains which require some level of on-the-fly calculation for retention of measurement precision. In this investigation a new method of on-the-fly system matrix calculation is proposed that provides advantages in application to such list-mode systems in terms of flexibility in system modeling. The new method is easily adaptable to complicated sy…
Online Metric Learning Methods Using Soft Margins and Least Squares Formulations
2012
Online metric learning using margin maximization has been introduced as a way to learn appropriate dissimilarity measures in an efficient way when information as pairs of examples is given to the learning system in a progressive way. These schemes have several practical advantages with regard to global ones in which a training set needs to be processed. On the other hand, they may suffer from a poor performance depending on the quality of the examples and the particular tuning or other implementation details. This paper formulates several online metric learning alternatives using a passive-aggressive schema. A new formulation of the online problem using least squares is also introduced. The…
The squared symmetric FastICA estimator
2017
In this paper we study the theoretical properties of the deflation-based FastICA method, the original symmetric FastICA method, and a modified symmetric FastICA method, here called the squared symmetric FastICA. This modification is obtained by replacing the absolute values in the FastICA objective function by their squares. In the deflation-based case this replacement has no effect on the estimate since the maximization problem stays the same. However, in the symmetric case we obtain a different estimate which has been mentioned in the literature, but its theoretical properties have not been studied at all. In the paper we review the classic deflation-based and symmetric FastICA approaches…
Seed Activation Scheduling for Influence Maximization in Social Networks
2018
This paper addresses the challenge of strategically maximizing the influence spread in a social network, by exploiting cascade propagators termed “seeds”. It introduces the Seed Activation Scheduling Problem (SASP) that chooses the timing of seed activation under a given budget, over a given time horizon, in the presence/absence of competition. The SASP is framed as a blogger-centric marketing problem on a two-level network, where the decisions are made to buy sponsored posts from prominent bloggers at calculated points in time. A Bayesian evidence diffusion model – the Partial Parallel Cascade (PPC) model – allows the network nodes to be partially activated, proportional to their accumulat…
Multiple imputation of rainfall missing data in the Iberian Mediterranean context
2017
Abstract Given the increasing need for complete rainfall data networks, in recent years have been proposed diverse methods for filling gaps in observed precipitation series, progressively more advanced that traditional approaches to overcome the problem. The present study has consisted in validate 10 methods (6 linear, 2 non-linear and 2 hybrid) that allow multiple imputation, i.e., fill at the same time missing data of multiple incomplete series in a dense network of neighboring stations. These were applied for daily and monthly rainfall in two sectors in the Jucar River Basin Authority (east Iberian Peninsula), which is characterized by a high spatial irregularity and difficulty of rainfa…
Revisiting the Mathematical Difficulties in Patinkin Cartel Model and Joint Profit Maximization
2015
We discuss the mathematical difficulties encountered in Patinkin's classical cartel model. It may be impossible to derive Patinkin's cartel by finding the reciprocal marginal cost functions: it could be impossible for cartel members to compute a solution, unless certain assumptions are made to simplify the problem, such as quasi-linear marginal costs or constant marginal costs. The total cost function is incoherent with respect to the sum of members' total cost. The model cannot handle constant marginal costs but we remind that de Mesnard's (2009, 2011) model of cartel with exogenous market shares allow solving the problem. We conclude that the Patinkin model of cartel is not so self-eviden…
Graph Topology Learning and Signal Recovery Via Bayesian Inference
2019
The estimation of a meaningful affinity graph has become a crucial task for representation of data, since the underlying structure is not readily available in many applications. In this paper, a topology inference framework, called Bayesian Topology Learning, is proposed to estimate the underlying graph topology from a given set of noisy measurements of signals. It is assumed that the graph signals are generated from Gaussian Markov Random Field processes. First, using a factor analysis model, the noisy measured data is represented in a latent space and its posterior probability density function is found. Thereafter, by utilizing the minimum mean square error estimator and the Expectation M…
Effective collecting area of lobster eye optics and optimal value of effective angle
2019
Effective collecting area represents one of principal parameters of optical systems. The common requirement is to obtain as large effective collecting area as it is possible. The paper presents an analytical method of calculating effective collecting length and its maximization for lobster eye optics. The results are applicable for a Schmidt as well as for an Angel lobster eye geometry used in an astronomical telescope where the source is at infinity such that the incoming rays are parallel. The dependence of effective collecting area vs. geometrical parameters is presented in a form of a simple compact equation. We show that the optimal ratio between mirrors depth and distance (effective a…
Visual aftereffects and sensory nonlinearities from a single statistical framework
2015
When adapted to a particular scenery our senses may fool us: colors are misinterpreted, certain spatial patterns seem to fade out, and static objects appear to move in reverse. A mere empirical description of the mechanisms tuned to color, texture, and motion may tell us where these visual illusions come from. However, such empirical models of gain control do not explain why these mechanisms work in this apparently dysfunctional manner. Current normative explanations of aftereffects based on scene statistics derive gain changes by (1) invoking decorrelation and linear manifold matching/equalization, or (2) using nonlinear divisive normalization obtained from parametric scene models. These p…
Multiphysics Optimization for First Wall Design Enhancement in Water-Cooled Breeding Blankets
2021
Abstract The commercial feasibility of the first fusion power plant generation adopting D-T plasma is strongly dependent upon the self-sustainability in terms of tritium fuelling. Within such a kind of reactor, the component selected to house the tritium breeding reactions is the breeding blanket, which is further assigned to heat power removal and radiation shielding functions. As a consequence of both its role and position, the breeding blanket is heavily exposed to both surface and volumetric heat loads and, hence, its design requires a typical multiphysics approach, from the neutronics to the thermo-mechanics. During last years, a great deal of effort has been put in the optimization of…