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Found 3 papers, 2 papers with code
A Randomised Subspace Gauss-Newton Method for Nonlinear Least-Squares
We propose a Randomised Subspace Gauss-Newton (R-SGN) algorithm for solving nonlinear least-squares optimization problems, that uses a sketched Jacobian of the residual in the variable domain and solves a reduced linear least-squares on each iteration.
A Subsequence Interleaving Model for Sequential Pattern Mining
Recent sequential pattern mining methods have used the minimum description length (MDL) principle to define an encoding scheme which describes an algorithm for mining the most compressing patterns in a database.
A Bayesian Network Model for Interesting Itemsets
Mining itemsets that are the most interesting under a statistical model of the underlying data is a commonly used and well-studied technique for exploratory data analysis, with the most recent interestingness models exhibiting state of the art performance.
