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Showing 1 to 8 of 8 for “"Min-max Optimization"”.
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Convergence Rates of Gradient Descent-ascent Dynamics under Computation Constraints in Solving Min-max Optimization
… Descent-ascent (GDA) method for solving the Min-max optimization (MMO) problems under computation constraints. In particular, we focus our study on two main classes of MMO: a continuous-time variant of the centralized Min-max problem where the GDA update only has access to the gradients of …
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Multi-Mode Robust Appointment Scheduling for Uncertain Service Time and Random No-Show Using Min-Max Optimization
… a robust appointment scheduling model that uses min-max optimization to generate appointment time for a multi-mode system while considering customer no-shows and uncertain service times. The objective is to minimize the total expected cost of the job waiting time and service provider's idling and …
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On the Complexity of Nonconvex-Strongly-Concave Smooth Minimax Optimization Using First-Order Methods
The problem of minimax optimization arises in a wide range of applications. When the objective function is convex-concave, almost the full picture is known. However, the general nonconvex-concave setting is less understood. In this work, we study the complexity of nonconvex-strongly-concave minimax …
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Biomechanical analysis of asymmetric and dynamic lifting task
… hand loads. An infinite order polynomial (min/max) optimization criterion predicted percentage of maximum muscle forces, which achieved 98% correlation with normalized EMG. In a separate study, motion data during lifting of 13.6 kg (30 lb) weight at 0 , 30 and 60 asymmetry was collected by …
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Optimized Thruster Allocation Utilizing Dual Quaternions for the Asteroid Sample Return Mission (OSIRIS-REx)
… frames. The developed method is based on a min-max optimization that results in a constant thruster distribution matrix. From the optimization, a minimum thrust solution is calculated for the coupled position and attitude commands. Therefore, its integration into the dual quaternion dynamics …
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Event-triggered near optimal adaptive control of interconnected systems
… are considered as non-cooperative players and a min-max optimization problem is formulated for linear and affine nonlinear systems by using zero-sum game approach for simultaneous optimization of both the control policy and the event based sampling instants. The net result is the development of …
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Mathematical Optimization Algorithms for Model Compression and Adversarial Learning in Deep Neural Networks
… pruning framework for DNNs based on mathematical optimization. We first formulate the weight pruning for DNNs as a non-convex optimization problem, and then systematically solve it using alternating direction method of multipliers (ADMM). Our work achieves a higher weight pruning ratio on DNNs …
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Evaluation of process systems operating envelopes
… or Stackelberg game, commonly known as the "minimax" problem, or more precisely as a max-min or min-max optimization problem. However, since the application here is to steady-state design, the problem formulation results in a more general nonconvex equality-constrained min-max program, for …