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Showing 1 to 8 of 8 for “"finite-time performance"”.

  1. Assessing the Finite-Time Performance of Local Search Algorithms

    … process of choosing parameters to improve their performance difficult. This dissertation introduces the B-acceptable solution probability in terms of B-acceptable solutions as a finite-time performance measure for local search algorithms. The B-acceptable solution probability reflects how …

    vt Repository record for Assessing the Finite-Time Performance of Local Search Algorithms (opens in a new tab)

  2. Generalized hill climbing algorithms for discrete optimization problems

    … that exist between the GHC algorithm's finite-time performance on three problems, and the general random variable formulations used. The dissertation concludes with suggestions for further research.

    vt Repository record for Generalized hill climbing algorithms for discrete optimization problems (opens in a new tab)

  3. Sampling Controlled Stochastic Recursions: Applications to Simulation Optimization and Stochastic Root Finding

    … but most such theory focuses on asymptotic performance. Automatically choosing parameters to ensure good finite-time performance has remained vexingly elusive, as evidenced by continuing efforts six decades after the introduction of stochastic approximation! The other popular paradigm to …

    vt Repository record for Sampling Controlled Stochastic Recursions: Applications to Simulation Optimization and Stochastic Root Finding (opens in a new tab)

  4. Learning structure from unstructured data

    … problems: first, we are given access only to a finite noisy data set; and second, the hidden state dimension or model order is unknown. The first problem limits our ability to comment on the finite time performance of estimation algorithms; and the second problem prevents appropriate …

    mit Repository record for Learning structure from unstructured data (opens in a new tab)

  5. Adaptive sampling trust-region methods for derivative-based and derivative-free simulation optimization problems

    … a first-order critical point with good practical performance. In the second study the Monte Carlo simulation is assumed to provide no direct observations of the function gradient. We present ASTRO-DF, which is a class of derivative-free trust-region algorithms, where the stochastic local model is …

    purdue-thes Repository record for Adaptive sampling trust-region methods for derivative-based and derivative-free simulation optimization problems (opens in a new tab)

  6. The exploration-exploitation trade-off in sequential decision making problems

    … decision making problems, in terms of maximising finite-time reward. The most common and best studied abstraction of the exploration-exploitation trade-off is the classic multi-armed bandit problem. In this thesis we study several important extensions that are more suitable than the classic …

    lancaster Repository record for The exploration-exploitation trade-off in sequential decision making problems (opens in a new tab)

  7. Stochastically Constrained Simulation Optimization On Mixed-Integer Spaces

    … and the constraints are expressed in terms of performance measures of the system that are observable only via a simulation model parameterized by a finite number of decision variables. In solving for such a system, one faces the much harder challenge of verifying the feasibility of a potential …

    vt Repository record for Stochastically Constrained Simulation Optimization On Mixed-Integer Spaces (opens in a new tab)

  8. Online advertisements and multi-armed bandits

    … limitations and achievable results for the performance of multi-armed bandit algorithms. We then formulate variations of the basic stochastic multi-armed bandit problem, aimed at modeling how budget-limited advertisers should bid and how ad exchanges should choose whose ad to display, and …

    uiuc Repository record for Online advertisements and multi-armed bandits (opens in a new tab)