Large-Scale

A GPU-Accelerated Moving-Horizon Algorithm for Training Deep Classification Trees on Large Datasets
Decision trees are essential yet NP-complete to train, prompting the widespread use of heuristic methods such as CART, which suffers …
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Large-scale process models using deep learning
Chemical and biological processes are inherently characterized by strong and unknown nonlinearities and measurement noise. In addition, …
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Optimization of compressor standby schemes for gas transmission pipeline systems based on gas delivery reliability
To guarantee the gas delivery reliability of a gas pipeline system, some standby compressor units or standby powers are typically …
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A Chance-Constrained Nonlinear Programming Approach for Equipment Design Under Uncertainty
In this work there are shown different strategies to cope uncertainty in large-scale chance-constrained nonlinear programs. We present …
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Scalable solution strategies for chance-constrained nonlinear programs
Probabilistic (chance) constraints are a powerful modeling paradigm that helps decision-makers control risk. Unfortunately, chance …
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An interior-point method for efficient solution of block-structured NLP problems using an implicit Schur-complement decomposition
In this work, we address optimization of large-scale, nonlinear, block-structured problems with a significant number of coupling …
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