299 papers
This paper introduces the time-consistent Dynamically Augmented CVaR (DCVaR) risk measure for Markov Decision Processes and presents a provably correct algorithm to optimize it by analyzing a specially defined Dynamically Augmented Robust MDP.
This paper establishes sharp rates of propagation of chaos for McKean-Vlasov equations with non-linear measure-dependent coefficients, applying these results to derive uniform-in-time convergence guarantees for mean field Langevin dynamics, control, and games by combining the BBGKY hierarchy with weak propagation techniques.
This paper establishes the first time-uniform error estimate for a fully discrete Luenberger observer applied to the one-dimensional barotropic Euler equations using mixed finite elements and implicit Euler time integration, demonstrating convergence that depends on initial errors, discretization parameters, and measurement noise via a modified relative energy technique.
This paper proposes VR-SDA-A, a novel variance-reduced algorithm that overcomes the stochasticity barrier in non-convex non-concave variational inequalities by integrating recursive momentum with a same-batch curvature verification mechanism, thereby achieving optimal O(ε⁻³) oracle complexity while enabling automated step-size adaptation.
This paper presents a Lanczos tau method for approximating and optimizing the -norm of delay differential algebraic systems, proving its convergence and stability under specific conditions while deriving efficient gradient formulas for robust controller synthesis and demonstrating accelerated convergence through spline-based extensions.
This paper introduces a disjunctive branch-and-bound framework combined with novel convex relaxations to solve low-rank matrix completion problems to certifiable optimality, significantly reducing optimality and test errors compared to existing heuristic methods for matrices up to 2500 dimensions.
This paper presents a framework for analyzing and synthesizing discrete-time optimization algorithms that guarantee certified exponential convergence and robustness against time-varying delays and unstable channel dynamics by utilizing Zames-Falb multipliers and linear matrix inequalities.
This paper proposes a noise-tolerant regularized quasi-Newton method with a relaxed Armijo-type line search that achieves a global convergence rate of for smooth nonconvex optimization under inexact function values, demonstrating superior robustness and competitive efficiency in experiments involving both artificial noise and low-precision arithmetic.
This paper proposes a fast, deterministic tensor completion method that leverages standard linear algebra to recover tensors from fiberwise observations along a single mode, offering efficient recovery guarantees without relying on random sampling assumptions.
This paper presents a customized, dependency-free C-based second-order cone programming solver for embedded real-time guidance and control applications that utilizes a predictor-corrector primal-dual interior-point method with homogeneous embedding to efficiently handle quadratic objectives without sparsity loss, supported by an automated code generation tool that outperforms existing solvers on typical problem scales.
This paper proposes a deterministic diffusion-based framework for controlling the probability density of nonlinear control-affine systems by leveraging a forward noise-excitation process and a reverse denoising feedback law to steer state distributions toward desired targets, with theoretical guarantees for drift-free and linear time-invariant dynamics.
This paper proposes a novel targeted exploration strategy for uncertain linear time-invariant systems with energy-bounded, non-stochastic disturbances, utilizing a semidefinite program to guarantee parameter estimation accuracy based on spectral content conditions that account for initial parametric uncertainty.
This paper establishes a general topological condition under which the semilocal Lipschitz upper semicontinuity modulus of a set-valued mapping is exactly determined by the supremum of its local calmness moduli, thereby enabling precise calculation of semilocal error bounds in various non-convex parametric optimization frameworks.
This paper establishes that hyperbolic systems admitting scaled Jordan frames possess minimal polynomials and, in the specific case of Jordan frames, exhibit orthonormality and Schur-type majorization properties that embed the space into a Euclidean Jordan algebra structure.
This paper proposes distributed dynamical algorithms that enable agents with only local data and no raw data sharing to collectively compute global system certificates, specifically solving the Lyapunov equation for stability verification and the algebraic Riccati equation for optimal LQR control, with guarantees of exact convergence and robustness.
This paper introduces PP-LUCB, a cost-efficient algorithm that optimally combines biased LLM-generated proxy scores with selective human audits to identify the best service system configuration while providing statistically valid confidence guarantees and significantly reducing audit costs.
This paper establishes theoretical conditions under which Monotone Operator Equilibrium Networks maintain convergence and bounded error under weight quantization by analyzing spectral perturbations, and validates these findings through experiments showing that quantization-aware training can recover provable convergence at four-bit precision.
This paper proposes a globally convergent monotone Hessian-Riemannian flow for solving time-dependent mean field games and introduces a solver-agnostic inverse problem framework that decouples parameter estimation from specific forward solvers by using implicit differentiation of the discrete MFG equations.
This paper characterizes the Q-property for various classes of banded matrices, including triangular and newly defined bidiagonal southwest matrices, by analyzing their sign patterns and determinants, while also extending these results to Euclidean Jordan algebras to establish conditions for rank-one linear transformations.
This paper establishes a new existence theory for equilibria in continuous-time time-inconsistent stochastic control problems by proving that solutions to entropy-regularized exploratory equilibrium HJB equations converge to a weak solution of the generalized equilibrium HJB equation as the regularization vanishes, thereby resolving the open problem of existence without requiring strong regularity assumptions.