TNN-SV: Threshold KNN-Shapley, described in our Section 4. TNN-SV-private: Private version of Threshold KNN-Shapley, described in our Section 5.The meaning of all other input arguments in the above command line should be clear from its naming, but please feel free to reach out if anything...
But 1 À u is itself an RB-type quantity, meaning that it appears as an error rate (in experiments that measure purity), and is measured using RB. As a result, showing that u À umin ¼ O(r2) is equivalent to: 1. Performing standard RB to measure r, the decay rate of ...
In some cases the sources and drains are symmetric, meaning that the sources and drains seen in the illustrated cross sections could be reversed without altering physical design parameters. In addition to the setup illustrated in the diagram, other transistor structures are also possible. In FIG. ...
We show in Section 4 that estimators from a TR Model using a Wiener process with linear predictors are collapsible and, hence, the TR model can be easily adapted for causal survival analysis. In particular, we would like to investigate the causal meaning of TR, as well as how to make a...
We stop calling the function sim1() when each list in eliminar[] is empty, meaning that in the last SM were no detected low-speed segments at any period, if it is not empty sim1() will be called to run a SS. If the number of selected vehicles at the end of a SS is the same...
Deep learning methods effectively develop feature spaces where distances have semantic meaning that reflect the distribution of labels used in training. Generic nearest neighbors in high dimensions are often problematic [61], but deep networks use a fully connected layer to reduce dimensionality with the...
We show in Section 4 that estimators from a TR Model using a Wiener process with linear predictors are collapsible and, hence, the TR model can be easily adapted for causal survival analysis. In particular, we would like to investigate the causal meaning of TR, as well as how to make a...
For any pair of keys ( pk , s ) ∈ K p × K s we will have s ⟵ ∑ i = 1 u χ (meaning it is the sum of u samples of χ) and pk = ( a E , b E ) = ( a E , a E · s + e ) where a E ← $ R q and e ⟵ ∑ i = 1 u χ . E = { E pk :...
We stop calling the function sim1() when each list in eliminar[] is empty, meaning that in the last SM were no detected low-speed segments at any period, if it is not empty sim1() will be called to run a SS. If the number of selected vehicles at the end of a SS is the same...
For any pair of keys ( pk , s ) ∈ K p × K s we will have s ⟵ ∑ i = 1 u χ (meaning it is the sum of u samples of χ) and pk = ( a E , b E ) = ( a E , a E · s + e ) where a E ← $ R q and e ⟵ ∑ i = 1 u χ . E = { E pk :...