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Navigation of a Quadratic Potential with Ellipsoidal ObstaclesAug 22 2019Given a convex quadratic potential of which its minimum is the agent's goal and a space populated with ellipsoidal obstacles, one can construct a Rimon-Koditschek artificial potential to navigate. These potentials are such that they combine the natural ... More
On the convergence of single-call stochastic extra-gradient methodsAug 22 2019Variational inequalities have recently attracted considerable interest in machine learning as a flexible paradigm for models that go beyond ordinary loss function minimization (such as generative adversarial networks and related deep learning systems). ... More
Tractable Reformulations of Distributionally Robust Two-stage Stochastic Programs with $\infty-$Wasserstein DistanceAug 22 2019In the optimization under uncertainty, decision-makers first select a wait-and-see policy before any realization of uncertainty and then place a here-and-now decision after the uncertainty has been observed. Two-stage stochastic programming is a popular ... More
A General Analysis Framework of Lower Complexity Bounds for Finite-Sum OptimizationAug 22 2019This paper studies the lower bound complexity for the optimization problem whose objective function is the average of $n$ individual smooth convex functions. We consider the algorithm which gets access to gradient and proximal oracle for each individual ... More
On the Modelling of Uncertain Impulse Control for Continuous Markov ProcessesAug 22 2019The use of coordinate processes for the modelling of impulse control for {\em general}\ Markov processes typically involves the construction of a probability measure on a countable product of copies of the path space. In addition, admissibility of an ... More
On representation formulas for solutions of linear differential equations with Caputo fractional derivativesAug 22 2019In the paper, a linear differential equation with variable coefficients and a Caputo fractional derivative is considered. For this equation, a Cauchy problem is studied, when an initial condition is given at an intermediate point that does not necessarily ... More
Input-to-state stability for parabolic boundary control: Linear and semi-linear systemsAug 22 2019Input-to-state stability (ISS) for systems described by partial differential equations has seen intensified research activity recently, and in particular the class of boundary control systems, for which truly infinite-dimensional effects enter the situation. ... More
`Regression Anytime' with Brute-Force SVD TruncationAug 22 2019We propose a new least-squares Monte Carlo algorithm for the approximation of conditional expectations in the presence of stochastic derivative weights. The algorithm can serve as a building block for solving dynamic programming equations, which arise, ... More
Quantum Algorithms for Portfolio OptimizationAug 22 2019We develop the first quantum algorithm for the constrained portfolio optimization problem. The algorithm has running time $\widetilde{O} \left( n\sqrt{r} \frac{\zeta \kappa}{\delta^2} \log \left(1/\epsilon\right) \right)$, where $r$ is the number of positivity ... More
Power Factor Angle Droop Control-A General Decentralized Control of Cascaded invertersAug 22 2019This letter proposes a general decentralized control of cascaded inverters-power factor angle droop control. Compared to the existing control strategies, it has the following attractive benefits: 1) it is suitable for both grid-connected and islanded ... More
Finite Precision Stochastic Optimisation -- Accounting for the BiasAug 22 2019We consider first order stochastic optimization where the oracle must quantize each subgradient estimate to $r$ bits. We treat two oracle models: the first where the Euclidean norm of the oracle output is almost surely bounded and the second where it ... More
Primary frequency regulation in power grids with on-off loads: chattering, limit cycles and convergence to optimalityAug 21 2019Load side participation can provide valuable support to the power network in case of urgencies. On many occasions, loads are naturally represented by on and off states. However, the use of on-off loads for frequency control can lead to chattering and ... More
A tree-based radial basis function method for noisy parallel surrogate optimizationAug 21 2019Parallel surrogate optimization algorithms have proven to be efficient methods for solving expensive noisy optimization problems. In this work we develop a new parallel surrogate optimization algorithm (ProSRS), using a novel tree-based "zoom strategy" ... More
Deterministic Epidemic Models For Ebola Infection With Time-dependent ControlsAug 21 2019Aug 22 2019In this paper, we have studied epidemiological models for Ebola infection using nonlinear ordinary differential equations and optimal control theory. We considered optimal control analysis of SIR and SEIR models for the deadly Ebola infection using vaccination, ... More
Deterministic epidemic models for ebola infection with time-dependent controlsAug 21 2019In this paper, we have studied epidemiological models for Ebola infection using nonlinear ordinary differential equations and optimal control theory. We considered optimal control analysis of SIR and SEIR models for the deadly Ebola virus infection using ... More
Stability of the linear complementarity problem properties under interval uncertaintyAug 21 2019We consider the linear complementarity problem with uncertain data modeled by intervals, representing the range of possible values. Many properties of the linear complementarity problem (such as solvability, uniqueness, convexity, finite number of solutions ... More
A Lyapunov analysis for accelerated gradient methods: From deterministic to stochastic caseAug 21 2019The article [SBC14] made a connection between Nesterov's accelerated gradient descent method and an ordinary differential equation (ODE). We show that this connection can be extended to the case of stochastic gradients, and develop Lyapunov function based ... More
Optimal Portfolio of Distinct Frequency-Response Services in Low-Inertia SystemsAug 21 2019A reduced level of system inertia due to renewable integration increases the need for cost-effective provision of ancillary services, such as Frequency Response (FR). In this paper we propose a closed-form solution to the differential equation describing ... More
Tensor Methods for Generating Compact Uncertainty Quantification and Deep Learning ModelsAug 21 2019Tensor methods have become a promising tool to solve high-dimensional problems in the big data era. By exploiting possible low-rank tensor factorization, many high-dimensional model-based or data-driven problems can be solved to facilitate decision making ... More
Detection-averse optimal and receding-horizon control for Markov decision processesAug 21 2019In this paper, we consider a Markov decision process (MDP), where the ego agent has a nominal objective to pursue while needs to hide its state from detection by an adversary. After formulating the problem, we first propose a value iteration (VI) approach ... More
Stabilization Control for ItO Stochastic System with Indefinite State and Control Weight CostsAug 21 2019In standard linear quadratic (LQ) control, the first step in investigating infinite-horizon optimal control is to derive the stabilization condition with the optimal LQ controller. This paper focuses on the stabilization of an Ito stochastic system with ... More
Iterative Linearized Control: Stable Algorithms and Complexity GuaranteesAug 20 2019We examine popular gradient-based algorithms for nonlinear control in the light of the modern complexity analysis of first-order optimization algorithms. The examination reveals that the complexity bounds can be clearly stated in terms of calls to a computational ... More
Chance-Constrained Yield Optimization of Photonic IC with Non-Gaussian Correlated Process VariationsAug 20 2019Uncertainty quantification has become an efficient tool for yield prediction, but its power in yield-aware optimization has not been well explored from either theoretical or application perspectives. Yield optimization is a much more challenging task. ... More
Nonlinear Forward-Backward Splitting with Projection CorrectionAug 20 2019In this paper, we propose and analyze a versatile algorithm called nonlinear forward-backward splitting (NOFOB). We show that the algorithm has many special cases in the literature and propose new methods that are special cases of the general framework. ... More
Mixed-Timescale Beamforming and Power Splitting for Massive MIMO Aided SWIPT IoT NetworkAug 20 2019Traditional simultaneous wireless information and power transfer (SWIPT) with power splitting assumes perfect channel state information (CSI), which is difficult to obtain especially in the massive multiple-input-multiple-output (MIMO) regime. In this ... More
Outer Approximation Methods for Solving Variational Inequalities Defined over the Solution Set of a Split Convex Feasibility ProblemAug 20 2019We study variational inequalities which are governed by a strongly monotone and Lipschitz continuous operator $F$ over a closed and convex set $S$. We assume that $S=C\cap A^{-1}(Q)$ is the nonempty solution set of a (multiple-set) split convex feasibility ... More
Interactive Trajectory Adaptation through Force-guided Bayesian OptimizationAug 20 2019Flexible manufacturing processes demand robots to easily adapt to changes in the environment and interact with humans. In such dynamic scenarios, robotic tasks may be programmed through learning-from-demonstration approaches, where a nominal plan of the ... More
An efficient non-condensed approach for linear and nonlinear model predictive control with bounded variablesAug 20 2019This paper presents a new approach to solving linear and nonlinear model predictive control (MPC) problems that requires minimal memory footprint and throughput and is particularly suitable when the model and/or controller parameters change at runtime. ... More
Strong Convergence of Forward-Backward-Forward Methods for Pseudo-monotone Variational Inequalities with Applications to Dynamic User Equilibrium in Traffic NetworksAug 20 2019In infinite-dimensional Hilbert spaces we device a class of strongly convergent primal-dual schemes for solving variational inequalities defined by a Lipschitz continuous and pseudomonote map. Our novel numerical scheme is based on Tseng's forward-backward-forward ... More
On the asymptotic convergence and acceleration of gradient methodsAug 19 2019We consider the asymptotic behavior of a family of gradient methods, which include the steepest descent and minimal gradient methods as special instances. It is proved that each method in the family will asymptotically zigzag between two directions. Asymptotic ... More
Warped Proximal Iterations for Monotone InclusionsAug 19 2019Resolvents play a central role in the design and the analysis of splitting algorithms for solving monotone inclusions. We investigate a generalization of this notion, called warped resolvent, which is constructed with the help of an auxiliary operator. ... More
Financial storage rights for hydroelectricityAug 19 2019There has recently been growing interest in the development of financial storage rights for energy storage systems as instruments akin to their transmission counterparts as a means to not only distribute congestion rents, but also to mitigate price risks, ... More
Second-Order Guarantees of Stochastic Gradient Descent in Non-Convex OptimizationAug 19 2019Recent years have seen increased interest in performance guarantees of gradient descent algorithms for non-convex optimization. A number of works have uncovered that gradient noise plays a critical role in the ability of gradient descent recursions to ... More
Stochastic Derivative-Free Optimization on Riemannian manifoldsAug 19 2019We study optimization problems over Riemannian manifolds using Stochastic Derivative-Free Optimization (SDFO) algorithms. Riemannian adaptations of SDFO in the literature use search information generated within the normal neighbourhoods around search ... More
Stabilization for a perturbed chain of integrators in prescribed timeAug 19 2019In this paper, we consider issues relative to prescribed time stabilisation of a chain of integrators of arbitrary length, either pure (i.e., where there is no disturbance) or perturbed. In a first part, we revisit the proportional navigation feedback ... More
Rates of convergence for iterative solutions of equations involving set-valued accretive operatorsAug 19 2019This paper studies proofs of strong convergence of various iterative algorithms for computing the unique zeros of set-valued accretive operators that also satisfy some weak form of uniform accretivity at zero. More precisely, we extract explicit rates ... More
On bin packing with clustering and bin packing with delaysAug 19 2019We continue the study of two recently introduced bin packing type problems, called bin packing with clustering, and online bin packing with delays. A bin packing input consists of items of sizes not larger than 1, and the goal is to partition or pack ... More
Distributed Stochastic Gradient Method for Non-Convex Problems with Applications in Supervised LearningAug 19 2019We develop a distributed stochastic gradient descent algorithm for solving non-convex optimization problems under the assumption that the local objective functions are twice continuously differentiable with Lipschitz continuous gradients and Hessians. ... More
Cluster-based Distributed Augmented Lagrangian Algorithm for a Class of Constrained Convex Optimization ProblemsAug 19 2019We propose a distributed solution for a constrained convex optimization problem over a network of clustered agents each consisted of a set of subagents. The communication range of the clustered agents is such that they can form a connected undirected ... More
The Landscape of Minimum Label Cut (Hedge Connectivity) ProblemAug 19 2019Minimum Label Cut (or Hedge Connectivity) problem is defined as follows: given an undirected graph $G=(V, E)$ with $n$ vertices and $m$ edges, in which, each edge is labeled (with one or multiple labels) from a label set $L=\{\ell_1,\ell_2, ..., \ell_{|L|}\}$, ... More
The Landscape of Minimum Label Cut (Hedge Connectivity) ProblemAug 19 2019Aug 20 2019Minimum Label Cut (or Hedge Connectivity) problem is defined as follows: given an undirected graph $G=(V, E)$ with $n$ vertices and $m$ edges, in which, each edge is labeled (with one or multiple labels) from a label set $L=\{\ell_1,\ell_2, ..., \ell_{|L|}\}$, ... More
Computing Estimators of Dantzig Selector type via Column and Constraint GenerationAug 18 2019We consider a class of linear-programming based estimators in reconstructing a sparse signal from linear measurements. Specific formulations of the reconstruction problem considered here include Dantzig selector, basis pursuit (for the case in which the ... More
Optimal scheduling of critically loaded multiclass GI/M/n+M queues in an alternating renewal environmentAug 17 2019In this paper, we study optimal control problems for multiclass GI/M/n+M queues in an alternating renewal (up-down) random environment in the Halfin-Whitt regime. Assuming that the downtimes are asymptotically negligible and only the service processes ... More
Implicit Deep LearningAug 17 2019We define a new class of ``implicit'' deep learning prediction rules that generalize the recursive rules of feedforward neural networks. These models are based on the solution of a fixed-point equation involving a single a vector of hidden features. The ... More
The stable set problem in graphs with bounded genus and bounded odd cycle packing numberAug 17 2019Consider the family of graphs without $ k $ node-disjoint odd cycles, where $ k $ is a constant. Determining the complexity of the stable set problem for such graphs $ G $ is a long-standing problem. We give a polynomial-time algorithm for the case that ... More
Generalized potential gamesAug 17 2019In this paper, we introduce a notion of generalized potential games that is inspired by a newly developed theory on generalized gradient flows. More precisely, a game is called generalized potential if the simultaneous gradient of the loss functions is ... More
Distributed Averaging Problems on Signed Networks with Directed TopologiesAug 17 2019This paper aims at addressing distributed averaging problems for signed networks in the presence of general directed topologies that are represented by signed digraphs. A new class of improved Laplacian potential functions is proposed by presenting two ... More
Parametric Majorization for Data-Driven Energy Minimization MethodsAug 17 2019Energy minimization methods are a classical tool in a multitude of computer vision applications. While they are interpretable and well-studied, their regularity assumptions are difficult to design by hand. Deep learning techniques on the other hand are ... More
On non-uniqueness in mean field gamesAug 16 2019We analyze an $N+1$-player game and the corresponding mean field game with state space $\{0,1\}$. The transition rate of $j$-th player is the sum of his control $\alpha^j$ plus a minimum jumping rate $\eta$. Instead of working under monotonicity conditions, ... More
Levenberg-Marquardt methods with inexact projections for constrained nonlinear systemsAug 16 2019In this paper, we first propose a new Levenberg-Marquardt method for solving constrained (and not necessarily square) nonlinear systems. Basically, the method combines the unconstrained Levenberg-Marquardt method with a type of feasible inexact projection. ... More
Convex geometry of the Coding problem for error constrained Dictionary LearningAug 16 2019In this article we expose the convex geometry of the class of coding problems that includes the likes of Basis Pursuit Denoising. We propose a novel reformulation of the coding problem as a convex-concave min-max problem. This particular reformulation ... More
Stability Results for the Continuity EquationAug 16 2019We provide a thorough study of stability of the 1-D continuity equation, which models many physical conservation laws. In our system-theoretic perspective, the velocity is considered to be an input. An additional input appears in the boundary condition ... More
A reflected forward-backward splitting method for monotone inclusions involving Lipschitzian operatorsAug 16 2019The proximal extrapolated gradient method \cite{Malitsky18a} is an extension of the projected reflected gradient method \cite{Malitsky15}. Both methods were proposed for solving the classic variational inequalities. In this paper, we investigate the projected ... More
On the optimality of double barrier strategies for Lévy processesAug 16 2019This paper studies the de Finetti's optimal dividend problem with capital injection. We confirm the optimality of a double barrier strategy when the underlying risk model follows a L\'evy process which may have positive and negative jumps. The main result ... More
Experimental performance of graph neural networks on random instances of max-cutAug 15 2019This note explores the applicability of unsupervised machine learning techniques towards hard optimization problems on random inputs. In particular we consider Graph Neural Networks (GNNs) -- a class of neural networks designed to learn functions on graphs ... More
Strong Structural Controllability of Signed NetworksAug 15 2019In this paper, we discuss the controllability of a family of linear time-invariant (LTI) networks that are defined on a signed graph. In this direction, we introduce the notion of positive and negative signed zero forcing sets for the controllability ... More
Convergence Behaviour of Some Gradient-Based Methods on Bilinear GamesAug 15 2019Min-max optimization has attracted much attention in the machine learning community due to the popularization of deep generative models and adversarial training. The optimization is quite different from traditional minimization analysis. For example, ... More
Stochastic Polynomial OptimizationAug 15 2019This paper studies stochastic optimization problems with polynomials. We propose an optimization model with sample averages and perturbations. The Lasserre type Moment-SOS relaxations are used to solve the sample average optimization. Properties of the ... More
Safe global optimization of expensive noisy black-box functions in the $δ$-Lipschitz frameworkAug 15 2019In this paper, the problem of safe global maximization (it should not be confused with robust optimization) of expensive noisy black-box functions satisfying the Lipschitz condition is considered. The notion "safe" means that the objective function $f(x)$ ... More
Mean-variance hedging of unit linked life insurance contracts in a jump-diffusion modelAug 15 2019We consider a time-consistent mean-variance portfolio selection problem of an insurer and allow for the incorporation of basis (mortality) risk. The optimal solution is identified with a Nash subgame perfect equilibrium. We characterize an optimal strategy ... More
On the behaviour of the Douglas-Rachford algorithm for minimizing a convex function subject to a linear constraintAug 15 2019The Douglas-Rachford algorithm (DRA) is a powerful optimization method for minimizing the sum of two convex (not necessarily smooth) functions. The vast majority of previous research dealt with the case when the sum has at least one minimizer. In the ... More
On Separating Points for Ensemble ControllabilityAug 14 2019Recent years have witnessed a wave of research activities in systems science toward the study of population systems. The driving force behind this shift was geared by numerous emerging and ever-changing technologies in life and physical sciences and engineering, ... More
A Survey of Recent Scalability Improvements for Semidefinite Programming with Applications in Machine Learning, Control, and RoboticsAug 14 2019Historically, scalability has been a major challenge to the successful application of semidefinite programming in fields such as machine learning, control, and robotics. In this paper, we survey recent approaches for addressing this challenge including ... More
The sum-of-squares hierarchy on the sphere, and applications in quantum information theoryAug 14 2019We consider the problem of maximizing a homogeneous polynomial on the unit sphere and its hierarchy of Sum-of-Squares (SOS) relaxations. Exploiting the polynomial kernel technique, we obtain a quadratic improvement of the known convergence rate by Reznick ... More
Algorithms the min-max regret 0-1 Integer Linear Programming Problem with Interval DataAug 14 2019We address the Interval Data Min-Max Regret 0-1 Integer Linear Programming problem (MMR-ILP), a variant of the 0-1 Integer Linear Programming problem where the objective function coefficients are uncertain. We solve MMR-ILP using a Benders-like Decomposition ... More
Mean Field Game for Linear Quadratic Stochastic Recursive SystemsAug 14 2019This paper focuses on linear-quadratic (LQ for short) mean-field games described by forward-backward stochastic differential equations (FBSDEs for short), in which the individual control region is postulated to be convex. The decentralized strategies ... More
Building Temperature Control: A Distributed Escort Dynamical ApproachAug 14 2019The constrained multi-agent optimization problem of distributed resource allocation is addressed using the evolutionary game theoretic framework. The issue of building temperature control is analyzed in which the controller is to devise a scheme to distribute ... More
Gradient-based shape optimization for the reduction of particle erosion in bended pipesAug 13 2019In this paper we consider a shape optimization problem for the minimization of the erosion, that is caused by the impact of inert particles onto the walls of a bended pipe. Using the continuous adjoint approach, we formally compute the shape derivative ... More
A multi-level ADMM algorithm for elliptic PDE-constrained optimization problemsAug 13 2019In this paper, the elliptic PDE-constrained optimization problem with box constraints on the control is studied. To numerically solve the problem, we apply the 'optimize-discretize-optimize' strategy. Specifically, the alternating direction method of ... More
A Closed-Form Analytical Solution for Optimal Coordination of Connected and Automated VehiclesAug 13 2019In earlier work, a decentralized optimal control framework was established for coordinating online connected and automated vehicles (CAVs) in merging roadways, urban intersections, speed reduction zones, and roundabouts. The dynamics of each vehicle were ... More
Bregman Itoh--Abe methods for sparse optimisationAug 13 2019In this paper we propose optimisation methods for variational regularisation problems based on discretising the inverse scale space flow with discrete gradient methods. Inverse scale space flow generalises gradient flow by incorporating a generalised ... More
A proximal DC approach for quadratic assignment problemAug 13 2019In this paper, we show that the quadratic assignment problem (QAP) can be reformulated to an equivalent rank constrained doubly nonnegative (DNN) problem. Under the framework of the difference of convex functions (DC) approach, a semi-proximal DC algorithm ... More
A Generic Solver for Unconstrained Control Problems with Integral Functional ObjectivesAug 13 2019We present a generic solver for unconstrained control problems (UCPs) whose objectives take the form of an integral functional of the controllers. The solver generalizes and improves upon the algorithm proposed by Tseng and Tang for the Witsenhausen's ... More
On the Convergence of AdaBound and its Connection to SGDAug 13 2019Adaptive gradient methods such as Adam have gained extreme popularity due to their success in training complex neural networks and less sensitivity to hyperparameter tuning compared to SGD. However, it has been recently shown that Adam can fail to converge ... More
Distributionally Robust Optimization: A ReviewAug 13 2019The concepts of risk-aversion, chance-constrained optimization, and robust optimization have developed significantly over the last decade. Statistical learning community has also witnessed a rapid theoretical and applied growth by relying on these concepts. ... More
Error Bounds and Singularity Degree in Semidefinite ProgrammingAug 12 2019In semidefinite programming a proposed optimal solution may be quite poor in spite of having sufficiently small residual in the optimality conditions. This issue may be framed in terms of the discrepancy between forward error (the unmeasurable `true error') ... More
Solving the problem of simultaneous diagonalisation via congruenceAug 12 2019We provide a solution to the so-called $SD$ $problem$, that is, the problem of simultaneous $diagonalisation$ $via$ $congruence$ of a given set of $m$ symmetric $n\times n$ matrices $\{A_{1},\ldots,A_{m}\}$, by showing that it can be reduced to a lower-dimensional ... More
Positivity Certificates via Integral RepresentationsAug 12 2019Complete monotonicity is a strong positivity property for real-valued functions on convex cones. It is certified by the kernel of the inverse Laplace transform. We study this for negative powers of hyperbolic polynomials. Here the certificate is the Riesz ... More
Intrinsic Lipschitz Regularity of Mean-Field Optimal ControlsAug 12 2019In this paper, we provide a sufficient condition for the Lipschitz-in-space regularity for solutions of optimal control problems formulated on continuity equations. Our approach involves a novel combination of mean-field approximation results for infinite-dimensional ... More
Assignability of dichotomy spectrum for discrete time-varying linear control systemsAug 12 2019In this paper, we show that for discrete time-varying linear control systems uniform complete controllability implies arbitrary assignability of dichotomy spectrum of closed-loop systems. This result significantly strengthens the result in A. Babiarz ... More
Near-optimal Robust Bilevel OptimizationAug 12 2019Aug 13 2019Bilevel optimization studies problems where the optimal response to a second mathematical optimization problem is integrated in the constraints. Such structure arises in a variety of decision-making problems in areas such as market equilibria, policy ... More
Near-optimal Robust Bilevel OptimizationAug 12 2019Aug 19 2019Bilevel optimization studies problems where the optimal response to a second mathematical optimization problem is integrated in the constraints. Such structure arises in a variety of decision-making problems in areas such as market equilibria, policy ... More
Near-optimal Robust Bilevel OptimizationAug 12 2019Bilevel optimization studies problems where the optimal response to a second mathematical optimization problem is integrated in the constraints. Such structure arises in a variety of decision-making problems in areas such as market equilibria, policy ... More
Near-optimal Robust Bilevel OptimizationAug 12 2019Aug 15 2019Bilevel optimization studies problems where the optimal response to a second mathematical optimization problem is integrated in the constraints. Such structure arises in a variety of decision-making problems in areas such as market equilibria, policy ... More
Solving high-dimensional nonlinear filtering problems using a tensor train decomposition methodAug 12 2019In this paper, we propose an efficient numerical method to solve high-dimensional nonlinear filtering (NLF) problems. Specifically, we use the tensor train decomposition method to solve the forward Kolmogorov equation (FKE) arising from the NLF problem. ... More
Mixed $H_2/H_{\infty}$ Control for Markov Jump Linear Systems with State and Mode-observation DelaysAug 12 2019In this paper, we study state-feedback control of Markov jump linear systems with state and mode-observation delays. We assume that the delay of the mode observation induced by the controllers follows an exponential distribution. We also introduce a time-varying ... More
Sufficient conditions for forward invariance and contractivity in hybrid inclusions using barrier functions -- with proofsAug 12 2019This paper studies set invariance and contractivity in hybrid systems modeled by hybrid inclusions using barrier functions. After introducing the notion of a multiple barrier functions, we investigate the tightest possible sufficient conditions to guarantee ... More
Sufficient conditions for forward invariance and contractivity in hybrid inclusions using barrier functionsAug 12 2019Aug 13 2019This paper studies set invariance and contractivity in hybrid systems modeled by hybrid inclusions using barrier functions. After introducing the notion of a multiple barrier functions, we investigate the tightest possible sufficient conditions to guarantee ... More
A Review of Cooperative Multi-Agent Deep Reinforcement LearningAug 11 2019Deep Reinforcement Learning has made significant progress in multi-agent systems in recent years. In this review article, we have mostly focused on recent papers on Multi-Agent Reinforcement Learning (MARL) than the older papers, unless it was necessary. ... More
Incentivizing Collaboration in Heterogeneous Teams via Common-Pool Resource GamesAug 11 2019We consider a team of heterogeneous agents that is collectively responsible for servicing and subsequently reviewing a stream of homogeneous tasks. Each agent (autonomous system or human operator) has an associated mean service time and mean review time ... More
Quantum algorithm for estimating volumes of convex bodiesAug 11 2019Estimating the volume of a convex body is a central problem in convex geometry and can be viewed as a continuous version of counting. We present a quantum algorithm that estimates the volume of an $n$-dimensional convex body within multiplicative error ... More
Bregman Forward-Backward Operator SplittingAug 11 2019We propose a general algorithm for finding a zero of the sum of two maximally monotone operators in reflexive Banach spaces. One of the operators is single-valued, and the algorithm alternates an explicit step on this operator and an implicit step of ... More
Optimal Control for Chemotaxis Systems and Adjoint-Based Optimization with Multiple-Relaxation-Time Lattice Boltzmann ModelsAug 11 2019This paper is devoted to continuous and discrete adjoint-based optimization approaches for optimal control problems governed by an important class of Nonlinear Coupled Anisotropic Convection-Diffusion Chemotaxis-type System (NCACDCS). This study is motivated ... More
A symbolic approach to the self-triggered design for networked control systemsAug 10 2019In this paper, we investigate novel self-triggered controllers for nonlinear control systems with reachability and safety specifications. To synthesize the self-triggered controller, we leverage the notion of symbolic models, or abstractions, which represent ... More
Yet the Game between Precommitted Policy and Time-Consistent PolicyAug 10 2019In this paper, a time-inconsistent stochastic linear-quadratic problem is investigated under the philosophy of self-control to balance the global optimality and time consistency. To this aim, the controller is modelled as having two classes of selves: ... More
Unique ergodicity of deterministic zero-sum differential gamesAug 09 2019We study the ergodicity of deterministic two-person zero-sum differential games. This property is defined by the uniform convergence to a constant of either the infinite-horizon discounted value as the discount factor tends to zero, or equivalently, the ... More
Transactive Energy System: Market-Based Coordination of Distributed Energy ResourcesAug 09 2019Distributed energy resources (DER) provide significant value for renewable energy integration in modern power grids. However, unlocking this value requires complex design and coordination. This paper focuses on the emerging {\em transactive energy systems}, ... More
The Chen-Teboulle algorithm is the proximal point algorithmAug 09 2019We revisit the Chen-Teboulle algorithm using recent insights and show that this allows a better bound on the step-size parameter.
A Data-Driven and Model-Based Approach to Fault Detection and Isolation in Networked SystemsAug 09 2019Fault detection and isolation is a field of engineering dealing with designing on-line protocols for systems that allow one to identify the existence of faults, pinpoint their exact location, and overcome them. We consider the case of multi-agent systems, ... More
Optimizing Consistent Merging and Pruning of Subgraphs in Network TomographyAug 09 2019A communication network can be modeled as a directed connected graph with edge weights that characterize performance metrics such as loss and delay. Network tomography aims to infer these edge weights from their pathwise versions measured on a set of ... More