Cited By
View all- Menon ARooyen BNatarajan N(2018)Learning from binary labels with instance-dependent noiseMachine Language10.1007/s10994-018-5715-3107:8-10(1561-1595)Online publication date: 1-Sep-2018
We prove two main results on how arbitrary linear threshold functions $f(x) = \sign(w\cdot x - \theta)$ over the $n$-dimensional Boolean hypercube can be approximated by simple threshold functions. Our first result shows that every $n$-variable ...
The analysis of linear threshold Boolean functions has recently attracted the attention of those interested in circuit complexity as well as of those interested in neural networks. Here a generalization of linear threshold functions is defined, namely, ...
We consider probabilistically constrained linear programs with general distributions for the uncertain parameters. These problems involve non-convex feasible sets. We develop a branch-and-bound algorithm that searches for a global optimal solution to ...
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