27 citations · 39 across the 5 of their papers we have counts for
8 papers
Positivity Validation Detection and Explainability via Zero Fraction Multi-Hypothesis Testing and Asymmetrically Pruned Decision Trees
Guy Wolf, Gil Shabat, Hanan Shteingart
Positivity is one of the three conditions for causal inference from observational data. The standard way to validate positivity is to analyze the distribution of propensity. Howeve…
DL-DDA -- Deep Learning based Dynamic Difficulty Adjustment with UX and Gameplay constraints
Dvir Ben Or, Michael Kolomenkin, Gil Shabat
Dynamic difficulty adjustment () is a process of automatically changing a game difficulty for the optimization of user experience. It is a vital part of almost any modern game…
Generalized Quantile Loss for Deep Neural Networks
Dvir Ben Or, Michael Kolomenkin, Gil Shabat
This note presents a simple way to add a count (or quantile) constraint to a regression neural net, such that given samples in the training set it guarantees that the predictio…
Super-resolution SAXS based on PSF engineering and sub-pixel detector translations
Benjamin Gutman, Michael Mrejen, Gil Shabat +3
Small-angle X-ray scattering (SAXS) technique enables convenient nanoscopic characterization for various systems and conditions. Nonetheless, lab-based SAXS systems intrinsically s…
Majority Voting and the Condorcet's Jury Theorem
Hanan Shteingart, Eran Marom, Igor Itkin +4
There is a striking relationship between a three hundred years old Political Science theorem named "Condorcet's jury theorem" (1785), which states that majorities are more likely t…
Fast and Accurate Gaussian Kernel Ridge Regression Using Matrix Decompositions for Preconditioning
Gil Shabat, Era Choshen, Dvir Ben Or +1
This paper presents a method for building a preconditioner for a kernel ridge regression problem, where the preconditioner is not only effective in its ability to reduce the condit…