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Every paper Pith has read. Search by title, abstract, or pith.
2292 papers in math.OC · page 1
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Incentives close the loop between mechanism and distributed optimization
Harnessing Individual Motivation for Collective Efficiency: A Mechanism-Driven Distributed Optimization Method
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Augmented action yields optimal control without costates
Minimum Effort Control Using Variational Methods of Analytical Mechanics A New Approach For Optimal Control
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One mass threshold replaces reachable-set grids for low-thrust targets
Reachability for Low-Thrust Trajectories via Maximum Initial Mass
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LBFGS and DIOM outperform CG on nonconvex trust-region steps
Quasi-Newton and Krylov Methods for the Solution of Nonconvex Trust-Region Subproblems
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Complex chance constraints turn into convex cone programs
Distributionally Robust Complex Chance-Constrained Optimization
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Measure solutions concentrate on unique PDE solutions
Concentration of measure-valued solutions for semilinear parabolic equations
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T-tests cut simulations in stochastic scheduling search
Simulation Strategies for an Efficient Local Search to solve Stochastic Scheduling Problems
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Algorithm clears two-layer prosumer markets with voltage limits in 0.8 s
A Non-Iterative Algorithm for Clearing Two-Layer Energy-Sharing Markets with Voltage Constraints
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Schrödinger equations with magnetic drift are small-time controllable
Approximate controllability in small times of bilinear Schr{\"o}dinger equations with magnetic drift
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The paper proposes an output feedback MPC framework using adaptive tubes that update as…
Output Feedback MPC with Adaptive Tubes
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Linear-quadratic costs ensure well-posed Monge problem for non-negative costs
Linear quadratic optimal transport and interpolation inequalities
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Marginal costs yield exact time series aggregation for GEP
Unlocking the Informational Value of Marginal Costs for Exact Time Series Aggregation in Generation Expansion Planning
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Suboptimal MPC recovered as splitting of monotone dynamics
Coupling optimization algorithms and monotone control systems: Suboptimal model predictive control as an operator splitting scheme
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Randomized screening yields directional stationarity in max-DC programs
RA-DCA: A Randomized Active-Set DCA for Directional Stationarity in Max-Structured DC Programs
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Neural net inside state estimator improves accuracy with few measurements
End-to-End Pseudo-Measurement Learning for State Estimation under Limited Observability
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Stochastic proximal algorithm converges linearly on constrained minimax
A Stochastic Implicit Proximal Point Algorithm for Solving Linearly Constrained Stochastic Minimax Problems
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Non-normal operators flag neural network training instabilities
Non-normal spectral signatures of instability in neural network training dynamics
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Selective dual dispatch improves ambulance response with less fleet use
Selective Ambulance Dispatch Under Contextual Travel-Time Uncertainty
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Neumann Hamilton-Jacobi solutions obey optimal fractional semiconcavity
Optimal semiconcavity with fractional modulus for Hamilton-Jacobi equations with Neumann boundary conditions
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Proximal DC algorithm solves signed Fréchet regression on manifolds
Proximal DCA for Fr\'echet Regression on Riemannian Manifolds with Bounded Curvature
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One config matches tuned AdamW across 1-8x horizons on LLMs
Anytime Training with Schedule-Free Spectral Optimization
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High-order Lie brackets give exponential extremum seeking on flat costs
Extremum seeking with exponential convergence via high-order Lie bracket approximations
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Rollout loss bounded by value error times hitting time
Performance Bounds for Rollout Policies in Stochastic Shortest Path Problems
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Prox-ITEM matches ITEM's optimal distance rate for composite problems
An optimal first-order method for smooth and strongly convex composite optimization and its stationary limit
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RL agent outperforms fixed rules for job shops with random arrivals
Deep Reinforcement Learning for Flexible Job Shop Scheduling with Random Job Arrivals
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Equivalence of manifold conditions simplifies intersection optimization
Optimization over the intersection of manifolds
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Newton method solves TV minimization with superlinear convergence
A $\operatorname{prox}$-Based Semi-Smooth Newton Method for TV-Minimization
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Normalizer of subsuperalgebra characterizes controls on supergroups
Characterization of Normalizer of Lie Superalgebra and its Application to Control Theory
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WPO converges linearly to optimum under entropy regularization
A note on convergence of Wasserstein policy optimization
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Data alone yields regulator that cancels unknown output disturbances
Output regulation via input-output data
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One conditional gradient step per iteration matches best-known rates
A conditional-gradient-based single-loop augmented Lagrangian method for inequality constrained optimization
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Control flows converge globally on non-convex constrained problems
Global Convergence of Control-Based Lagrangian Flows for Non-Convex Optimization
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Poisson scheme yields entropy for martingale transport
Generalized specific entropy on Wiener space with application to Martingale Optimal Transport
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Nash bargaining in RL lifts EV energy trading welfare 61 percent
Incentive-Aligned Vehicle-to-Vehicle Energy Trading via Nash-Integrated Multi-Agent Reinforcement Learning
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Matching convergence for PDE opt and control via time decomposition
From PDEs constrained optimization to controllability problems via time domain decomposition
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Bound on expected tracking error derived for online optimization
Online Optimization with Unknown Time-Varying Parameters from Noisy Gradient Measurements
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GPU batches cut optimal sparse GLM search time by 10-100 times
From Sequential Nodes to GPU Batches: Parallel Branch and Bound for Optimal $k$-Sparse GLMs
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One random direction step forces directional stationarity
Achieving Directional-Stationarity from a Single Random Direction Step
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Equal spacing uniquely maximizes Solow-Polasky diversity on intervals
Exact Uniform L1 Spacing for Solow-Polasky Diversity on Lines and Ordered Pareto Fronts
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Low-rank tensors reduce Riccati equations for large control
Proximal Gradient-based Low Rank Tensor Decomposition for State Dependent Riccati Equation
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Jacobian decomposition enables constant-step MSA with rate 1-s
Spectral analysis of the logit mapping and implications for stochastic user equilibrium algorithms
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Jacobian split proves linear convergence for SUE
Spectral analysis of the logit mapping and implications for stochastic user equilibrium algorithms
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Optimal transport penalties give explicit generators for risk measures
An optimal transport foundation for a class of dynamically consistent risk measures
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Mixed atomic-continuous measures recovered from moments
On Moment-Based Recovery of Measures with Atomic and Continuous Parts
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Revenue adequacy holds for nonlinear energy network flows
General Revenue Adequacy Conditions for Energy Transport Networks
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DADS partial feedback regulates unknown PDE-ODE systems
Beyond Nonlinear Small-Gain Design: DADS with Partial-State Feedback
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Quantum RL matches classical on chemical flowsheet design
Enhanced Reinforcement Learning-based Process Synthesis via Quantum Computing
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YANN-RL cuts training time for chemical process control
Reinforcement Learning-based Control via Y-wise Affine Neural Networks: Comparative Case Studies for Chemical Processes
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Decentralized cubic Newton matches exact iteration complexity
Decentralized Inexact Cubic Newton Method with Consensus Procedure
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Decentralized cubic Newton matches exact speed with polylog comm overhead
Decentralized Inexact Cubic Newton Method with Consensus Procedure