Data-Driven Inverse Optimization with Incomplete Information

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Path-following control is a critical technology for autonomous vehicles. However, time-varying parameters, parametric uncertainties, external disturbances, and complicated environments significantly challenge autonomous driving. We propose an iterative rob ...

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In certain cases of astronomical data analysis, the meaningful physical quantity to extract is the ratio R between two data sets. Examples include the lensing ratio, the interloper rate in spectroscopic redshift samples, and the decay rate of gravitational ...

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Selection bias may arise when data have been chosen in a way that subsequent analysis does not account for. Such bias can arise in climate event attribution studies that are performed rapidly after a devastating "trigger event'', whose occurrence correspon ...

Designing turbocompressors is a complex and challenging task, as it involves balancing conflicting objectives such as efficiency, stability, and robustness against manufacturing deviations. This paper proposes an integrated design methodology for turbocomp ...

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Data-Driven Inverse Optimization with Incomplete Information

Chattez avec Graph Search

Less Conservatism, Stronger Robustness: Iterative Robust Gain-Scheduled Path Following Control of Autonomous Bus With Unstructured and Changing Dynamics

Spectral Estimators for High-Dimensional Matrix Inference

Health Prediction for Lithium-Ion Batteries Under Unseen Working Conditions

Unveiling the complexity of learning and decision-making

An Iterative Adaptive Dynamic Programming Approach for Macroscopic Fundamental Diagram-Based Perimeter Control and Route Guidance

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Multi-agent Learning with Privacy Guarantees

Quantization for Decentralized Learning Under Subspace Constraints

Range-separated hybrid functionals for accurate prediction of band gaps of extended systems

Near-Minimax Optimal Estimation With Shallow ReLU Neural Networks

Universal and adaptive methods for robust stochastic optimization

An Unbiased Method of Measuring the Ratio of Two Data Sets

WINC: A Wireless IoT Network for Multi-Noise Source Cancellation

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems"

Optimal digital filter selection for remote photoplethysmography (rPPG) signal conditioning

Observation of non-reciprocal harmonic conversion in real sounds

A Spatial Branch and Bound Algorithm for Continuous Pricing with Advanced Discrete Choice Demand Modeling

Timing and spatial selection bias in rapid extreme event attribution

An Integrated Approach to Designing Robust Turbocompressors on Gas Bearings Through Surrogate Modeling and Constrained Multi-Objective Optimization

Safe multi-agent deep reinforcement learning for joint bidding and maintenance scheduling of generation units