Search alternatives:
problems optimization » process optimization (Expand Search), policy optimization (Expand Search), robust optimization (Expand Search)
guided optimization » based optimization (Expand Search), model optimization (Expand Search)
common problems » common problem (Expand Search), complex problems (Expand Search)
binary i » binary _ (Expand Search)
i guided » ai guided (Expand Search), mri guided (Expand Search), ct guided (Expand Search)
problems optimization » process optimization (Expand Search), policy optimization (Expand Search), robust optimization (Expand Search)
guided optimization » based optimization (Expand Search), model optimization (Expand Search)
common problems » common problem (Expand Search), complex problems (Expand Search)
binary i » binary _ (Expand Search)
i guided » ai guided (Expand Search), mri guided (Expand Search), ct guided (Expand Search)
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MCLP_quantum_annealer_V0.5
Published 2025“…Currently, classical high-performance and parallel spatial computing architectures are commonly employed to solve geospatial optimization problems. …”
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Generalized Tensor Decomposition With Features on Multiple Modes
Published 2021“…An efficient alternating optimization algorithm with provable spectral initialization is further developed. …”
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Contextual Dynamic Pricing with Strategic Buyers
Published 2024“…We then establish an <math><mrow><mi>O</mi><mo>(</mo><msqrt><mi>T</mi></msqrt><mo>)</mo></mrow></math> regret upper bound of our proposed policy and an <math><mrow><mi>Ω</mi><mo>(</mo><msqrt><mi>T</mi></msqrt><mo>)</mo></mrow></math> regret lower bound for any pricing policy within our problem setting. This underscores the rate optimality of our policy. …”
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Bayesian sequential design for sensitivity experiments with hybrid responses
Published 2023“…<p>In experimental design, a common problem seen in practice is when the result includes one binary response and multiple continuous responses. …”
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Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf
Published 2020“…The proposed multilabel approaches convert the original 8-class problem into a set of three binary problems to facilitate the use of the CSP algorithm. …”
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