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Gowtham Muniraju
Deep learningRandom searchParameterized complexityLinear searchBayesian optimization
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#2Bhavya KailkhuraH-Index: 12
Last. Peer-Timo BremerH-Index: 26
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Sampling one or more effective solutions from large search spaces is a recurring idea in computer vision, and sequential optimization has become the prevalent solution. Typical examples are hyper-parameter optimization in deep learning and sample mining in predictive modeling tasks. Existing solutions attempt to trade-off between global exploration and local exploitation, wherein the initial exploratory sample is critical to their success. While discrepancy-based samples have become the \textit{...
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