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Unbiased Multilevel Monte Carlo: Stochastic Optimization, Steady-state Simulation, Quantiles, and Other ApplicationsApr 22 2019We present general principles for the design and analysis of unbiased Monte Carlo estimators in a wide range of settings. Our estimators posses finite work-normalized variance under mild regularity conditions. We apply our estimators to various settings ... More
A Unified Framework for Structured Graph Learning via Spectral ConstraintsApr 22 2019Graph learning from data represents a canonical problem that has received substantial attention in the literature. However, insufficient work has been done in incorporating prior structural knowledge onto the learning of underlying graphical models from ... More
Inducing Multi-Convexity in Path Constrained Trajectory Optimization for Mobile ManipulatorsApr 22 2019In this paper, we propose a novel trajectory optimization algorithm for mobile manipulators under end-effector path, collision avoidance and various kinematic constraints. Our key contribution lies in showing how this highly non-linear and non-convex ... More
Provable Bregman-divergence based Methods for Nonconvex and Non-Lipschitz ProblemsApr 22 2019The (global) Lipschitz smoothness condition is crucial in establishing the convergence theory for most optimization methods. Unfortunately, most machine learning and signal processing problems are not Lipschitz smooth. This motivates us to generalize ... More
A convex relaxation to compute the nearest structured rank deficient matrixApr 21 2019Given an affine space of matrices $L$ and a matrix $\theta \in L$, consider the problem of finding the closest rank deficient matrix to $\theta$ on $L$ with respect to the Frobenius norm. This is a nonconvex problem with several applications in estimation ... More
On Modification of an Adaptive Stochastic Mirror Descent Algorithm for Convex Optimization Problems with Functional ConstraintsApr 20 2019The paper is devoted to a new modification of recently proposed adaptive stochastic mirror descent algorithm for convex optimization problems in the case of several convex functional constraints. Algorithms, standard and its proposed modification, are ... More
Minimax Optimal Online Stochastic Learning for Sequences of Convex Functions under Sub-Gradient Observation FailuresApr 19 2019We study online convex optimization under stochastic sub-gradient observation faults, where we introduce adaptive algorithms with minimax optimal regret guarantees. We specifically study scenarios where our sub-gradient observations can be noisy or even ... More
Steepest Gradient-Based Orthogonal Precoder For Integer-Forcing MIMOApr 19 2019In this paper, we develop an orthogonal precoding scheme for integer-forcing (IF) linear receivers using the steepest gradient algorithm. Although this scheme can be viewed as a special case of the unitary precoded integer-forcing (UPIF), it has two major ... More
Submodular Maximization Beyond Non-negativity: Guarantees, Fast Algorithms, and ApplicationsApr 19 2019It is generally believed that submodular functions -- and the more general class of $\gamma$-weakly submodular functions -- may only be optimized under the non-negativity assumption $f(S) \geq 0$. In this paper, we show that once the function is expressed ... More
On the Convergence of Adam and BeyondApr 19 2019Several recently proposed stochastic optimization methods that have been successfully used in training deep networks such as RMSProp, Adam, Adadelta, Nadam are based on using gradient updates scaled by square roots of exponential moving averages of squared ... More
Dual Quaternion Based Powered Descent Guidance with State-Triggered ConstraintsApr 19 2019This paper presents a numerical algorithm for computing 6-degree-of-freedom free-final-time powered descent guidance trajectories. The trajectory generation problem is formulated using a unit dual quaternion representation of the rigid body dynamics, ... More
On a semismooth* Newton method for solving generalized equationsApr 19 2019In the paper, a Newton-type method for the solution of generalized equations (GEs) is derived, where the linearization concerns both the single-valued and the multi-valued part of the considered GE. The method is based on the new notion of semismoothness${}^*$ ... More
The Douglas-Rachford Algorithm for Convex and Nonconvex Feasibility ProblemsApr 19 2019The Douglas-Rachford method, a projection algorithm designed to solve continuous optimization problems, forms the basis of a useful heuristic for solving combinatorial optimization problems. In order to successfully use the method, it is necessary to ... More
From Static to Dynamic Anomaly Detection with Application to Power System Cyber SecurityApr 19 2019Developing advanced diagnosis tools to detect cyber attacks is the key to security of power systems. It has been shown that multivariate attacks can bypass bad data detection schemes typically built on static behavior of the systems, which misleads operators ... More
Direct Synthesis of Iterative Algorithms with Bounds on Achievable Worst-Case Convergence RateApr 19 2019Iterative first-order methods such as gradient descent and its variants are widely used for solving optimization and machine learning problems. There has been recent interest in analytic or numerically efficient methods for computing worst-case performance ... More
Differentiating Through a Conic ProgramApr 19 2019We consider the problem of efficiently computing the derivative of the solution map of a convex cone program, when it exists. We do this by implicitly differentiating the residual map for its homogeneous self-dual embedding, and solving the linear systems ... More
An Inexact Interior-Point Lagrangian Decomposition Algorithm with Inexact OraclesApr 18 2019We develop a new inexact interior-point Lagrangian decomposition method to solve a wide range class of constrained composite convex optimization problems. Our method relies on four techniques: Lagrangian dual decomposition, self-concordant barrier smoothing, ... More
A Julia Module for Polynomial Optimization with Complex Variables applied to Optimal Power FlowApr 18 2019Many optimization problems in power transmission networks can be formulated as polynomial problems with complex variables. A polynomial optimization problem with complex variables consists in optimizing a real-valued polynomial whose variables and coefficients ... More
Solvability of Power Flow Equations Through Existence and Uniqueness of Complex Fixed PointApr 18 2019Variations of loading level and changes in system topological property may cause the operating point of an electric power systems to move gradually towards the verge of its transmission capability, which can lead to catastrophic outcomes such as voltage ... More
Plug-and-play Solvability of the Power Flow Equations for Interconnected DC Microgrids with Constant Power LoadsApr 18 2019In this paper we study the DC power flow equations of a purely resistive DC power grid which consists of interconnected DC microgrids with constant-power loads. We present a condition on the power grid which guarantees the existence of a solution to the ... More
Adaptive Reconstruction for Electrical Impedance Tomography with a Piecewise Constant ConductivityApr 18 2019In this work we propose and analyze a numerical method for electrical impedance tomography of recovering a piecewise constant conductivity from boundary voltage measurements. It is based on standard Tikhonov regularization with a Modica-Mortola penalty ... More
Convergence analysis of a Lasserre hierarchy of upper bounds for polynomial minimization on the sphereApr 18 2019We study the convergence rate of a hierarchy of upper bounds for polynomial minimization problems, proposed by Lasserre [SIAM J. Optim. 21(3) (2011), pp. 864-885], for the special case when the feasible set is the unit (hyper)sphere. The upper bound at ... More
Uncrowded Hypervolume Improvement: COMO-CMA-ES and the Sofomore frameworkApr 18 2019We present a framework to build a multiobjective algorithm from single-objective ones. This framework addresses the $p \times n$-dimensional problem of finding p solutions in an n-dimensional search space, maximizing an indicator by dynamic subspace optimization. ... More
Optimal Control of Markov Regime-Switching Stochastic Recursive UtilitiesApr 18 2019In this paper, we establish a general stochastic maximum principle for optimal control for systems described by a continuous-time Markov regime-switching stochastic recursive utilities model. The control domain is postulated not to be convex, and the ... More
A Framework to Control Functional Connectivity in the Human BrainApr 18 2019Functional connectivity in the human brain can be measured as the correlation between cluster-synchronized oscillatory neural activity across different brain regions. By exploiting this notion, it is possible to distinguish between certain healthy and ... More
Resilient Distributed Field EstimationApr 18 2019We study resilient distributed field estimation under measurement attacks. A network of agents or devices measures a large, spatially distributed physical field parameter. An adversary arbitrarily manipulates the measurements of some of the agents. Each ... More
Sensitivity Analysis for Hybrid Systems and Systems with MemoryApr 18 2019We present an adjoint sensitivity method for hybrid discrete -- continuous systems, extending previously published forward sensitivity methods. We treat ordinary differential equations and differential-algebraic equations of index up to two (Hessenberg) ... More
Efficient Techniques for Shape Optimization with Variational Inequalities using AdjointsApr 18 2019In general, standard necessary optimality conditions cannot be formulated in a straightforward manner for semi-smooth shape optimization problems. In this paper, we consider shape optimization problems constrained by variational inequalities of the first ... More
Reducing Noise in GAN Training with Variance Reduced ExtragradientApr 18 2019Using large mini-batches when training generative adversarial networks (GANs) has been recently shown to significantly improve the quality of the generated samples. This can be seen as a simple but computationally expensive way of reducing the noise of ... More
Balancing Safety and Traffic Throughput in Cooperative Vehicle PlatooningApr 18 2019In this paper we propose a distributed model predictive control architecture to coordinate the longitudinal motion of a vehicle platoon at a signalized intersection. Our control approach is cooperative; we use vehicle-to-vehicle (V2V) communication in ... More
Convex Graph Invariant Relaxations For Graph Edit DistanceApr 18 2019The edit distance between two graphs is a widely used measure of similarity that evaluates the smallest number of vertex and edge deletions/insertions required to transform one graph to another. It is NP-hard to compute in general, and a large number ... More
On the Convergence of the Inexact Running Krasnosel'skii-Mann MethodApr 17 2019This paper leverages a framework based on averaged operators to tackle the problem of tracking fixed points associated with maps that evolve over time. In particular, the paper considers the Krasnosel'skii-Mann method in a settings where: (i) the underlying ... More
SACOBRA with Online Whitening for Solving Optimization Problems with High ConditioningApr 17 2019Real-world optimization problems often have expensive objective functions in terms of cost and time. It is desirable to find near-optimal solutions with very few function evaluations. Surrogate-assisted optimizers tend to reduce the required number of ... More
Spatial and Topological Interdiction for Transmission SystemsApr 17 2019This paper presents novel formulations and algorithms for the $N$-$k$ interdiction problem in transmission networks. In particular, it models two new classes of $N$-$k$ attacks: (i) Spatial $N$-$k$ attacks where the attack is constrained to be within ... More
The oriented mailing problem and its convex relaxationApr 17 2019In this note we introduce a new model for the mailing problem in branched transportation in order to allow the cost functional to take into account the orientation of the moving particles. This gives an effective answer to [Problem 15.9] of the book "Optimal ... More
Computation of the analytic center of the solution set of the linear matrix inequality arising in continuous- and discrete-time passivity analysisApr 17 2019In this paper formulas are derived for the analytic center of the solution set of linear matrix inequalities (LMIs) defining passive transfer functions. The algebraic Riccati equations that are usually associated with such systems are related to boundary ... More
Study of memory effect in an EOQ model for completely backlogged demand during shortageApr 17 2019The most commonly developed inventory models are the classical economic order quantity model, is governed by the integer order differential equations. We want to come out from the traditional thought i.e. classical order inventory model where the memory ... More
A Stackelberg Game of Backward Stochastic Differential Equations with ApplicationsApr 17 2019This paper is concerned with a Stackelberg game of backward stochastic differential equations (BSDEs), where the coefficients of the backward system and the cost functionals are deterministic, and the control domain is convex. Necessary and sufficient ... More
A Categorical Approach to L-ConvexityApr 17 2019We investigate an enriched-categorical approach to a field of discrete mathematics. The main result is a duality theorem between a class of enriched categories (called $\overline{\mathbb{Z}}$- or $\overline{\mathbb{R}}$-categories) and that of what we ... More
Resilience of Traffic Networks with Partially Controlled RoutingApr 17 2019This paper investigates the use of Infrastructure-To-Vehicle (I2V) communication to generate routing suggestions for drivers in transportation systems, with the goal of optimizing a measure of overall network congestion. We define link-wise levels of ... More
Distribution System State Estimation in the Presence of High Solar PenetrationApr 17 2019Low-to-medium voltage distribution networks are experiencing rising levels of distributed energy resources, including renewable generation, along with improved sensing, communication, and automation infrastructure. As such, state estimation methods for ... More
A QoS-Oriented Trajectory Optimization in Swarming Unmanned-Aerial-Vehicles CommunicationsApr 16 2019This letter aims to present a novel approach for unmanned aerial vehicles (UAV)' path planning with respect to certain quality of service requirements. More specifically, we study the max-min fairness problem in an air-to-ground communication system where ... More
Sum Throughput Maximization in Multi-Tag Backscattering to Multiantenna ReaderApr 16 2019Backscatter communication (BSC) is being realized as the core technology for pervasive sustainable Internet-of-Things applications. However, owing to the resource-limitations of passive tags, the efficient usage of multiple antennas at the reader is essential ... More
An Energy Sharing Game in Prosumers based on Generalized Demand Bidding: Model and PropertiesApr 16 2019The advent of energy "prosumers" that not only consume but also produce energy, advocates a sharing market to encourage energy exchange. Motivated by the recent technology of online platforms, this paper proposes a simple but effective mechanism for energy ... More
Power System Dispatch with Electrochemical Energy StorageApr 16 2019Battery storage is essential for the future smart grid. The inevitable battery degradation renders the battery lifetime volatile and highly dependent on battery dispatch, and thus incurs opportunity cost. This paper rigorously derives the degradation ... More
Numerical construction of spherical $t$-designs by Barzilai-Borwein methodApr 16 2019A point set $\mathrm X_N$ on the unit sphere is a spherical $t$-design is equivalent to the nonnegative quantity $A_{N,t+1}$ vanished. We show that if $\mathrm X_N$ is a stationary point set of $A_{N,t+1}$ and the minimal singular value of basis matrix ... More
Projection methods for solving split equilibrium problemsApr 16 2019The paper considers a split inverse problem involving component equilibrium problems in Hilbert spaces. This problem therefore is called the split equilibrium problem (SEP). It is known that almost solution methods for solving problem (SEP) are designed ... More
Golden ratio algorithms with new stepsize rules for variational inequalitiesApr 16 2019In this paper, we introduce two golden ratio algorithms with new stepsize rules for solving pseudomonotone and Lipschitz variational inequalities in finite dimensional Hilbert spaces. The presented stepsize rules allow the resulting algorithms to work ... More
Mean Field Linear Quadratic Control: FBSDE and Riccati Equation ApproachesApr 16 2019This paper studies social optima and Nash games for mean field linear quadratic control systems, where subsystems are coupled via dynamics and individual costs. For the social control problem, we first obtain a set of forward-backward stochastic differential ... More
A Revised Mehrotra Predictor-Corrector algorithm for Model Predictive ControlApr 16 2019Input constrained Model predictive control (MPC) includes an optimization problem which should iteratively be solved at each time-instance. The well-known drawback of model predictive control is the computational cost of the optimization problem. This ... More
Equilibria in a large production economy with an infinite dimensional commodity space and price dependent preferencesApr 16 2019We extend Greenberg et al. [7] to a production economy with infinitely many commodities and prove the existence of a competitive equilibrium for the economy. We employ a saturated measure space for the set of agents and apply recent results for an infinite ... More
A modified adaptive cubic regularization method for large-scale unconstrained optimization problemApr 16 2019In this paper, we modify the adaptive cubic regularization method for large-scale unconstrained optimization problem by using a real positive definite scalar matrix to approximate the exact Hessian. Combining with the nonmonotone technique, we also give ... More
A Triangle Algorithm for Semidefinite Version of Convex Hull Membership ProblemApr 16 2019Given a subset $\mathbf{S}=\{A_1, \dots, A_m\}$ of $\mathbb{S}^n$, the set of $n \times n$ real symmetric matrices, we define its {\it spectrahull} as the set $SH(\mathbf{S}) = \{p(X) \equiv (Tr(A_1 X), \dots, Tr(A_m X))^T : X \in \mathbf{\Delta}_n\}$, ... More
Non-Stochastic Hypothesis Testing with Application to Privacy Against Hypothesis-Testing AdversaryApr 16 2019In this paper, we consider privacy against hypothesis testing adversaries within a non-stochastic framework. We develop a theory of non-stochastic hypothesis testing by borrowing the notion of uncertain variables from non-stochastic information theory. ... More
Reinforcement Learning for Batch Bioprocess OptimizationApr 15 2019Apr 19 2019Bioprocesses have received a lot of attention to produce clean and sustainable alternatives to fossil-based materials. However, they are generally difficult to optimize due to their unsteady-state operation modes and stochastic behaviours. Furthermore, ... More
Reinforcement Learning for Batch Bioprocess OptimizationApr 15 2019Bioprocesses have received a lot of attention to produce clean and sustainable alternatives to fossil-based materials. However, they are generally difficult to optimize due to their unsteady-state operation modes and stochastic behaviours. Furthermore, ... More
The Landscape of the Planted Clique Problem: Dense subgraphs and the Overlap Gap PropertyApr 15 2019In this paper we study the computational-statistical gap of the planted clique problem, where a clique of size $k$ is planted in an Erdos Renyi graph $G(n,\frac{1}{2})$ resulting in a graph $G\left(n,\frac{1}{2},k\right)$. The goal is to recover the planted ... More
Burer-Monteiro guarantees for general semidefinite programsApr 15 2019Consider a semidefinite program (SDP) involving an $n\times n$ positive semidefinite matrix $X$. The Burer-Monteiro method consists in solving a nonconvex program in $Y$, where $Y$ is an $n\times p$ matrix such that $X=Y Y^T$. Despite nonconvexity, Boumal ... More
IP Solutions for International Kidney Exchange ProgrammesApr 15 2019Apr 19 2019In kidney exchange programmes patients with end-stage renal failure may exchange their willing, but incompatible living donors among each other. National kidney exchange programmes are in operation in ten European countries, and some of them have already ... More
IP Solutions for International Kidney Exchange ProgrammesApr 15 2019In kidney exchange programmes patients with end-stage renal failure may exchange their willing, but incompatible living donors among each other. National kidney exchange programmes are in operation in ten European countries, and some of them have already ... More
Stabilization of non-admissible curves for a class of nonholonomic systemsApr 15 2019The problem of tracking an arbitrary curve in the state space is considered for underactuated driftless control-affine systems. This problem is formulated as the stabilization of a time-varying family of sets associated with a neighborhood of the reference ... More
Quasi-best approximation in optimization with PDE constraintsApr 15 2019We consider finite element solutions to quadratic optimization problems, where the state depends on the control via a well-posed linear partial differential equation. Exploiting the structure of a suitably reduced optimality system, we prove that the ... More
Euler's optimal profile problemApr 15 2019We study an old variational problem formulated by Euler as Proposition 53 of his `Scientia Navalis' by means of the direct method of the calculus of variations. Precisely, through relaxation arguments, we prove the existence of minimizers. We fully investigate ... More
Reduced Order Modeling for Nonlinear PDE-constrained Optimization using Neural NetworksApr 15 2019Nonlinear model predictive control (NMPC) often requires real-time solution to optimization problems. However, in cases where the mathematical model is of high dimension in the solution space, e.g. for solution of partial differential equations (PDEs), ... More
Regional gradient controllability of ultra-slow diffusions involving the Hadamard-Caputo time fractional derivativeApr 15 2019This paper investigates the regional gradient controllability for ultra-slow diffusion processes governed by the time fractional diffusion systems with a Hadamard-Caputo time fractional derivative. Some necessary and sufficient conditions on regional ... More
New sweep algorithm for solving a continuous linear-quadratic optimization problem with unseptable boundary conditionsApr 15 2019A new algorithm for solving the solution of the linear-quadratic optimization problem (LQP) with unseparated boundary conditions in the continuous case is given. Using the properties of symmetry of the corresponding Hamiltonian matrix, the Euler-Lagrange ... More
Most IPs with bounded determinants can be solved in polynomial timeApr 15 2019In 1983 Lenstra showed that an integer program (IP) is fixed parameter tractable in the number of integer variables or the number of constraints. Since then, an open question has been to identify other parameters for which IP is fixed parameter tractable. ... More
A Trust Region Method for Finding Second-Order Stationarity in Linearly Constrained Non-Convex OptimizationApr 14 2019Motivated by TRACE algorithm [Curtis et al. 2017], we propose a trust region algorithm for finding second order stationary points of a linearly constrained non-convex optimization problem. We show the convergence of the proposed algorithm to (\epsilon_g, ... More
Data-driven Decision Making with Probabilistic Guarantees (Part 2): Applications of Chance-constrained Optimization in Power SystemsApr 14 2019Uncertainties from deepening penetration of renewable energy resources have posed critical challenges to the secure and reliable operations of future electric grids. Among various approaches for decision making in uncertain environments, this paper focuses ... More
Lower Bounds for the Bandwidth ProblemApr 14 2019The Bandwidth Problem asks for a simultaneous permutation of the rows and columns of the adjacency matrix of a graph such that all nonzero entries are as close as possible to the main diagonal. This work focuses on investigating novel approaches to obtain ... More
Exploiting Vulnerabilities of Load Forecasting Through Adversarial AttacksApr 13 2019Load forecasting plays a critical role in the operation and planning of power systems. By using input features such as historical loads and weather forecasts, system operators and utilities build forecast models to guide decision making in commitment ... More
Design of optimized backstepping controller for the synchronization of chaotic Colpitts oscillator using shark smell algorithmApr 13 2019In this paper, an adaptive backstepping controller has been tuned to synchronize two chaotic Colpitts oscillators in a master slave configuration. The parameters of the controller are determined using shark smell optimization (SSO) algorithm. Numerical ... More
Time-Fractional Optimal Control of Initial Value Problems on Time ScalesApr 13 2019We investigate Optimal Control Problems (OCP) for fractional systems involving fractional-time derivatives on time scales. The fractional-time derivatives and integrals are considered, on time scales, in the Riemann--Liouville sense. By using the Banach ... More
Optimal control of second-order integral equationsApr 13 2019We analyze optimal control problems for multiple Fredholm and Volterra integral equations. These are non Pontryaginian optimal control problems, i.e. an extremum principle of Pontryagin type does not hold. We obtain first order necessary conditions for ... More
On barrier and modified barrier multigrid methods for 3d topology optimizationApr 13 2019One of the challenges encountered in optimization of mechanical structures, in particular in what is known as topology optimization, is the size of the problems, which can easily involve millions of variables. A basic example is the minimum compliance ... More
Joint Scheduling and Power Control for V2V Broadcast Communication with Adjacent Channel InterferenceApr 13 2019This paper investigates how to mitigate the impact of adjacent channel interference (ACI) in vehicular broadcast communication, using scheduling and power control. Our objective is to maximize the number of connected vehicles. First, we formulate the ... More
Dynamic scheduling in a partially fluid, partially lossy queueing systemApr 13 2019We consider a single server queueing system with two classes of jobs: eager jobs with small sizes that require service to begin almost immediately upon arrival, and tolerant jobs with larger sizes that can wait for service. While blocking probability ... More
A Non-Monotone Conjugate Subgradient Type Method for Minimization of Convex FunctionsApr 12 2019We suggest a conjugate subgradient type method without any line-search for minimization of convex non differentiable functions. Unlike the custom methods of this class, it does not require monotone decrease of the goal function and reduces the implementation ... More
A Non-Monotone Conjugate Subgradient Type Method for Minimization of Convex FunctionsApr 12 2019Apr 16 2019We suggest a conjugate subgradient type method without any line-search for minimization of convex non differentiable functions. Unlike the custom methods of this class, it does not require monotone decrease of the goal function and reduces the implementation ... More
A Non-Monotone Conjugate Subgradient Type Method for Minimization of Convex FunctionsApr 12 2019Apr 19 2019We suggest a conjugate subgradient type method without any line-search for minimization of convex non differentiable functions. Unlike the custom methods of this class, it does not require monotone decrease of the goal function and reduces the implementation ... More
A new conjugate gradient-like method with sufficient descent condition and its global convergence based on the Armijo line searchApr 12 2019In this paper, we propose a new conjugate gradient-like algorithm. The step directions generated by the new algorithm satisfy a sufficient descent condition independent of the line search. The global convergence of the new algorithm, with the Armijo backtracking ... More
Information Based Method for Approximate Solving Stochastic Control ProblemsApr 12 2019An information based method for solving stochastic control problems with partial observation has been proposed. First, the information-theoretic lower bounds of the cost function has been analysed. It has been shown, under rather weak assumptions, that ... More
Categorization Problem on Controllability of Boolean Control NetworksApr 12 2019A Boolean control network (BCN) is a discrete-time dynamical system whose variables take values from a binary set $\{0,1\}$. At each time step, each variable of the BCN updates its value simultaneously according to a Boolean function which takes the state ... More
Stability of the Solution Set of Quasi-variational Inequalities and Optimal ControlApr 12 2019For a class of quasivariational inequalities (QVIs) of obstacle-type the stability of its solution set and associated optimal control problems are considered. These optimal control problems are non-standard in the sense that they involve an objective ... More
A note on the combination of equilibrium problemsApr 12 2019In this short paper, we show that the solution set of a combination of equilibrium problems is not necessary contained in the intersection of a finite family of solution sets of equilibrium problems. As a corollary, we deduce that statements in recent ... More
Optimization of drug controlled release from multi-laminated devices based on the modified Tikhonov regularization methodApr 12 2019From the viewpoint of inverse problem, the optimization of drug release based on the multi-laminated drug controlled release devices has been regarded as the solution problem of the diffusion equation initial value inverse problem. In view of the ill-posedness ... More
Defence EfficiencyApr 11 2019In order to automate actions, such as defences against network attacks, one needs to quantify their efficiency. This can subsequently be used in post-evaluation, learning, etc. In order to quantify the defence efficiency as a function of the impact of ... More
External optimal control of fractional parabolic PDEsApr 11 2019In this paper we introduce a new notion of optimal control, or source identification in inverse, problems with fractional parabolic PDEs as constraints. This new notion allows a source/control placement outside the domain where the PDE is fulfilled. We ... More
Derivation and Generation of Path-Based Valid Inequalities for Transmission Expansion PlanningApr 11 2019This paper seeks to solve the long-term transmission expansion planning problem more effectively by reducing the solution search space and the computational effort. The proposed methodology finds and adds cutting planes based on structural insights about ... More
Connections Between Adaptive Control and Optimization in Machine LearningApr 11 2019This paper demonstrates many immediate connections between adaptive control and optimization methods commonly employed in machine learning. Starting from common output error formulations, similarities in update law modifications are examined. Concepts ... More
Tikhonov regularization of dynamical systems associated with nonexpansive operators defined in closed and convex setsApr 11 2019In this paper, we propose a Tikhonov-like regularization for dynamical systems associated with non-expansive operators defined in closed and convex sets of a Hilbert space. We prove the well-posedness and the strong convergence of the proposed dynamical ... More
Matrix Modeling of Energy Hub with Variable Energy EfficienciesApr 11 2019The modeling of multi-energy systems (MES) is the basic task of analyzing energy systems integration. The variable energy efficiencies of the energy conversion and storage components in MES introduce nonlinearity to the model and thus complicate the analysis ... More
On the Inapproximability of the Discrete Witsenhausen ProblemApr 11 2019We consider a discrete version of the Witsenhausen problem where all random variables are bounded and take on integer values. Our main goal is to understand the complexity of computing good strategies given the distributions for the initial state and ... More
Deep learning as optimal control problems: models and numerical methodsApr 11 2019We consider recent work of Haber and Ruthotto 2017 and Chang et al. 2018, where deep learning neural networks have been interpreted as discretisations of an optimal control problem subject to an ordinary differential equation constraint. We review the ... More
A Stochastic LBFGS Algorithm for Radio Interferometric CalibrationApr 11 2019We present a stochastic, limited-memory Broyden Fletcher Goldfarb Shanno (LBFGS) algorithm that is suitable for handling very large amounts of data. A direct application of this algorithm is radio interferometric calibration of raw data at fine time and ... More
A Stochastic LBFGS Algorithm for Radio Interferometric CalibrationApr 11 2019Apr 13 2019We present a stochastic, limited-memory Broyden Fletcher Goldfarb Shanno (LBFGS) algorithm that is suitable for handling very large amounts of data. A direct application of this algorithm is radio interferometric calibration of raw data at fine time and ... More
Low-rank matrix recovery with Ky Fan 2-k-normApr 11 2019We propose Ky Fan 2-k-norm-based models for the nonconvex low-rank matrix recovery problem. A general difference of convex algorithm (DCA) is developed to solve these models. Numerical results show that the proposed models achieve high recoverability ... More
Game representations for state constrained continuous time linear regulator problemsApr 11 2019A supremum-of-quadratics representation for convex barrier-type constraints is developed and applied within the context of a class of continuous time state constrained linear regulator problems. Using this representation, it is shown that a linear regulator ... More
Optimal Nonergodic Sublinear Convergence Rate of Proximal Point Algorithm for Maximal Monotone Inclusion ProblemsApr 11 2019We establish the optimal nonergodic sublinear convergence rate of the proximal point algorithm for maximal monotone inclusion problems. First, the optimal bound is formulated by the performance estimation framework, resulting in an infinite dimensional ... More
Stochastic Comparative Statics in Markov Decision ProcessesApr 10 2019In multi-period stochastic optimization problems, the future optimal decision is a random variable whose distribution depends on the parameters of the optimization problem. We analyze how the expected value of this random variable changes as a function ... More