A new system of variational inclusions with (H,eta)-monotone operators in Hilbert spaces

In this paper, we introduce and study a new system of variational inclusions involving (H, eta)-monotone operators in Hilbert space. Using the resolvent operator associated with (H, eta)monotone operators, we prove the existence and uniqueness of solutions for this new system of variational inclusions. We also construct a new algorithm for approximating the solution of this system and discuss the convergence of the sequence of iterates generated by the algorithm. (c) 2005 Elsevier Ltd. All rights reserved.

Splines and vector splines

The thrust of this report concerns spline theory and some of the background to spline theory and follows the development in (Wahba, 1991). We also review methods for determining hyper-parameters, such as the smoothing parameter, by Generalised Cross Validation. Splines have an advantage over Gaussian Process based procedures in that we can readily impose atmospherically sensible smoothness constraints and maintain computational efficiency. Vector splines enable us to penalise gradients of vorticity and divergence in wind fields. Two similar techniques are summarised and improvements based on robust error functions and restricted numbers of basis functions given. A final, brief discussion of the application of vector splines to the problem of scatterometer data assimilation highlights the problems of ambiguous solutions.

On Structural Resource of Monotone Recognition

Algorithmic resources are considered for elaboration and identification of monotone functions and some alternate structures are brought, which are more explicit in sense of structure and quantities and which can serve as elements of practical identification algorithms. General monotone recognition is considered on multi- dimensional grid structure. Particular reconstructing problem is reduced to the monotone recognition through the multi-dimensional grid partitioning into the set of binary cubes.

A Recession Notion for a Class of Monotone Bivariate Functions

Using monotone bifunctions, we introduce a recession concept for general equilibrium problems relying on a variational convergence notion. The interesting purpose is to extend some results of P. L. Lions on variational problems. In the process we generalize some results by H. Brezis and H. Attouch relative to the convergence of the resolvents associated with maximal monotone operators.

Splines in Numerical Integration

AMS Subj. Classification: 65D07, 65D30.

Variational Principles for Monotone and Maximal Bifunctions

2000 Mathematics Subject Classification: 49J40, 49J35, 58E30, 47H05

Visualization and prediction of spatial deformation using thin-plate splines in the context of scoliosis

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Visualization and prediction of spatial deformation using thin-plate splines in the context of scoliosis

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Incomplete information games of conflict and collective action

My thesis consists of three essays that investigate strategic interactions between individuals engaging in risky collective action in uncertain environments. The first essay analyzes a broad class of incomplete information coordination games with a wide range of applications in economics and politics. The second essay draws from the general model developed in the first essay to study decisions by individuals of whether to engage in protest/revolution/coup/strike. The final essay explicitly integrates state response to the analysis. The first essay, Coordination Games with Strategic Delegation of Pivotality, exhaustively analyzes a class of binary action, two-player coordination games in which players receive stochastic payoffs only if both players take a ``stochastic-coordination action''. Players receive conditionally-independent noisy private signals about the normally distributed stochastic payoffs. With this structure, each player can exploit the information contained in the other player's action only when he takes the “pivotalizing action”. This feature has two consequences: (1) When the fear of miscoordination is not too large, in order to utilize the other player's information, each player takes the “pivotalizing action” more often than he would based solely on his private information, and (2) best responses feature both strategic complementarities and strategic substitutes, implying that the game is not supermodular nor a typical global game. This class of games has applications in a wide range of economic and political phenomena, including war and peace, protest/revolution/coup/ strike, interest groups lobbying, international trade, and adoption of a new technology. My second essay, Collective Action with Uncertain Payoffs, studies the decision problem of citizens who must decide whether to submit to the status quo or mount a revolution. If they coordinate, they can overthrow the status quo. Otherwise, the status quo is preserved and participants in a failed revolution are punished. Citizens face two types of uncertainty. (a) non-strategic: they are uncertain about the relative payoffs of the status quo and revolution, (b) strategic: they are uncertain about each other's assessments of the relative payoff. I draw on the existing literature and historical evidence to argue that the uncertainty in the payoffs of status quo and revolution is intrinsic in politics. Several counter-intuitive findings emerge: (1) Better communication between citizens can lower the likelihood of revolution. In fact, when the punishment for failed protest is not too harsh and citizens' private knowledge is accurate, then further communication reduces incentives to revolt. (2) Increasing strategic uncertainty can increase the likelihood of revolution attempts, and even the likelihood of successful revolution. In particular, revolt may be more likely when citizens privately obtain information than when they receive information from a common media source. (3) Two dilemmas arise concerning the intensity and frequency of punishment (repression), and the frequency of protest. Punishment Dilemma 1: harsher punishments may increase the probability that punishment is materialized. That is, as the state increases the punishment for dissent, it might also have to punish more dissidents. It is only when the punishment is sufficiently harsh, that harsher punishment reduces the frequency of its application. Punishment Dilemma 1 leads to Punishment Dilemma 2: the frequencies of repression and protest can be positively or negatively correlated depending on the intensity of repression. My third essay, The Repression Puzzle, investigates the relationship between the intensity of grievances and the likelihood of repression. First, I make the observation that the occurrence of state repression is a puzzle. If repression is to succeed, dissidents should not rebel. If it is to fail, the state should concede in order to save the costs of unsuccessful repression. I then propose an explanation for the “repression puzzle” that hinges on information asymmetries between the state and dissidents about the costs of repression to the state, and hence the likelihood of its application by the state. I present a formal model that combines the insights of grievance-based and political process theories to investigate the consequences of this information asymmetry for the dissidents' contentious actions and for the relationship between the magnitude of grievances (formulated here as the extent of inequality) and the likelihood of repression. The main contribution of the paper is to show that this relationship is non-monotone. That is, as the magnitude of grievances increases, the likelihood of repression might decrease. I investigate the relationship between inequality and the likelihood of repression in all country-years from 1981 to 1999. To mitigate specification problem, I estimate the probability of repression using a generalized additive model with thin-plate splines (GAM-TPS). This technique allows for flexible relationship between inequality, the proxy for the costs of repression and revolutions (income per capita), and the likelihood of repression. The empirical evidence support my prediction that the relationship between the magnitude of grievances and the likelihood of repression is non-monotone.

Isogeometric analysis of large-deformation thin shells using RHT-splines for multiple-patch coupling

We present an isogeometric thin shell formulation for multi-patches based on rational splines over hierarchical T-meshes (RHT-splines). Nitsche’s method is employed to efficiently couple the patches. The RHT-splines have the advantages of allowing a computationally feasible local refine- ment, are free from linear independence, possess high order continuity and satisfy the partition of unity and non-negativity, properties. In addition, C 1 continuity of the RHT-splines obviates to use of rotational degrees of freedom. The good performance of the present method is demonstrated by a number of numerical examples.

Variational Quantum Splines: Moving Beyond Linearity for Quantum Activation Functions

Activation functions within neural networks play a crucial role in Deep Learning since they allow to learn complex and non-trivial patterns in the data. However, the ability to approximate non-linear functions is a significant limitation when implementing neural networks in a quantum computer to solve typical machine learning tasks. The main burden lies in the unitarity constraint of quantum operators, which forbids non-linearity and poses a considerable obstacle to developing such non-linear functions in a quantum setting. Nevertheless, several attempts have been made to tackle the realization of the quantum activation function in the literature. Recently, the idea of the QSplines has been proposed to approximate a non-linear activation function by implementing the quantum version of the spline functions. Yet, QSplines suffers from various drawbacks. Firstly, the final function estimation requires a post-processing step; thus, the value of the activation function is not available directly as a quantum state. Secondly, QSplines need many error-corrected qubits and a very long quantum circuits to be executed. These constraints do not allow the adoption of the QSplines on near-term quantum devices and limit their generalization capabilities. This thesis aims to overcome these limitations by leveraging hybrid quantum-classical computation. In particular, a few different methods for Variational Quantum Splines are proposed and implemented, to pave the way for the development of complete quantum activation functions and unlock the full potential of quantum neural networks in the field of quantum machine learning.

The beta modified Weibull distribution

A five-parameter distribution so-called the beta modified Weibull distribution is defined and studied. The new distribution contains, as special submodels, several important distributions discussed in the literature, such as the generalized modified Weibull, beta Weibull, exponentiated Weibull, beta exponential, modified Weibull and Weibull distributions, among others. The new distribution can be used effectively in the analysis of survival data since it accommodates monotone, unimodal and bathtub-shaped hazard functions. We derive the moments and examine the order statistics and their moments. We propose the method of maximum likelihood for estimating the model parameters and obtain the observed information matrix. A real data set is used to illustrate the importance and flexibility of the new distribution.

Formulating Mixed Models for Experiments, Including Longitudinal Experiments

Mixed models have become important in analyzing the results of experiments, particularly those that require more complicated models (e.g., those that involve longitudinal data). This article describes a method for deriving the terms in a mixed model. Our approach extends an earlier method by Brien and Bailey to explicitly identify terms for which autocorrelation and smooth trend arising from longitudinal observations need to be incorporated in the model. At the same time we retain the principle that the model used should include, at least, all the terms that are justified by the randomization. This is done by dividing the factors into sets, called tiers, based on the randomization and determining the crossing and nesting relationships between factors. The method is applied to formulate mixed models for a wide range of examples. We also describe the mixed model analysis of data from a three-phase experiment to investigate the effect of time of refinement on Eucalyptus pulp from four different sources. Cubic smoothing splines are used to describe differences in the trend over time and unstructured covariance matrices between times are found to be necessary.

A generalized modified Weibull distribution for lifetime modeling

A four parameter generalization of the Weibull distribution capable of modeling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone as well as non-monotone failure rates, which are quite common in lifetime problems and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the Weibull, extreme value, exponentiated Weibull, generalized Rayleigh and modified Weibull distributions, among others. We derive two infinite sum representations for its moments. The density of the order statistics is obtained. The method of maximum likelihood is used for estimating the model parameters. Also, the observed information matrix is obtained. Two applications are presented to illustrate the proposed distribution. (C) 2008 Elsevier B.V. All rights reserved.