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公开(公告)号：US10169292B2
公开(公告)日：2019-01-01
申请号：US15582698
申请日：2017-04-30
发明人： Merav Aharoni , Yael Ben-Haim , Eyal Bin , Odellia Boni
IPC分类号： G06F17/11
摘要： A method and product for solving a Constraint Satisfaction Problem (CSP) having a constraint associated with a string variable, comprising: defining a string variable using a string domain data structure representing a domain of string values for string variables, the structure represents the domain as a Deterministic Finite Automaton (DFA) with no back loops longer than 1 and edges representing characters; defining a constraint for the CSP, wherein the constraint involves the variable and is to be complied with by a solution to the CSP; invoking a CSP solver using the string variable while complying with the constraint, and to invoke operations performed over the domain, wherein the solver: propagates values into the domain of string values, wherein the value propagation reduces the domain size; or selects values from the domain thus reducing the domain to a singleton domain, whereby value propagation to domains of other variables is invoked by the solver.
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公开(公告)号：US20230025731A1
公开(公告)日：2023-01-26
申请号：US17378794
申请日：2021-07-19
发明人： Michael Vinov , Oleg Blinder , Diptikalyan Saha , Sandeep Hans , Aniya Aggarwal , Omer Yehuda Boehm , Eyal Bin
摘要： A computer-implemented method comprising, automatically: analyzing a machine learning dataset which comprises multiple datapoints, to deduce constraints on features of the datapoints; generating a first set of CSP (Constraint Satisfaction Problem) rules expressing the constraints; based on a machine learning model which was trained on the dataset, generating a second set of CSP rules that define one or more perturbation candidates among the features of one of the datapoints; formulating a CSP based on the first and second sets of CSP rules; solving the formulated CSP using a solver; and using the solution of the CSP as a counterfactual explanation of a prediction made by the machine learning model with respect to the one datapoint.
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公开(公告)号：US10657180B2
公开(公告)日：2020-05-19
申请号：US14931954
申请日：2015-11-04
发明人： Eyal Bin
IPC分类号： G06N5/00 , G06F16/901
摘要： Technical solutions are described for reusing a solution for a test. An example method includes building, by a processor, a solution cache including a tree structure representative of a plurality of solutions, which stores a key configurable immediate value of a previous solution as a node, the previous solution as a leaf node of the tree, and an edge from the node indicative of a value of the key configurable immediate value at the node. The method includes traversing nodes of the tree structure in the solution cache to identify key configurable immediate values of a previous solution identical to configurable immediate values from the test by identifying edges associated values identical to those from the test. In response to reaching a leaf node of the tree structure, using the solution(s) at the leaf node as a solution of the test.
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公开(公告)号：US20190235865A1
公开(公告)日：2019-08-01
申请号：US15881804
申请日：2018-01-29
IPC分类号： G06F9/30
CPC分类号： G06F9/30036 , G06F9/3001 , G06F16/2237 , G06F16/2246
摘要： A method, apparatus and product for solving CSP comprising vectors of unknown size. The method comprises generating a structural skeleton tree of a problem description, wherein the structural skeleton tree comprises a node representing a vector of unknown size and a node representing a size of the vector; determining a vector size Constraint Satisfaction Problem (CSP) based on the structural skeleton tree, wherein said determining comprises projecting over-approximated constraints on the size of the vector based on operators used on the vector or elements thereof; solving the vector size CSP to determine the size of the vector; modifying the structural skeleton tree to set the size of the vector and to include nodes for each element in the vector, whereby obtaining a CSP; and solving the CSP.
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