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Low-dimensional linear programming with violations

The 43rd Annual IEEE Symposium on Foundations of Computer Science, 2002. Proceedings., 2002
Timothy M. Chan
semanticscholar   +1 more source

Mixed-integer quadratic programming formulations for computing the Lipschitz constant of ReLU networks

The Lipschitz constant of a neural network is a useful metric to get information about the robustness of a trained network. Its exact calculation is however NP-hard even for one hidden layer ReLU networks. In this presentation, by taking into account activation regions at each layer as new constraints, we propose new quadratically constrained mixed ...
Sbihi, Mohammed   +2 more
openaire   +1 more source

Use of a New Moodle Module for Improving the Teaching of a Basic Course on Computer Architecture

IEEE Transactions on Education, 2011
M. A. Trenas   +4 more
semanticscholar   +1 more source

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