34 citations · 269 across the 42 of their papers we have counts for
5 papers · 1 filter
Turning Big data into tiny data: Constant-size coresets for k-means, PCA and projective clustering
Dan Feldman, Melanie Schmidt, Christian Sohler
We develop and analyze a method to reduce the size of a very large set of data points in a high dimensional Euclidean space R d to a small set of weighted points such that the resu…
Aligning Points to Lines: Provable Approximations
Ibrahim Jubran, Dan Feldman
We suggest a new optimization technique for minimizing the sum of non-convex real functions that satisfy a property that we call piecewise log-Lipschitz.…
Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds
Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski +2
We present an efficient coresets-based neural network compression algorithm that sparsifies the parameters of a trained fully-connected neural network in a manner that provably app…
Generic Coreset for Scalable Learning of Monotonic Kernels: Logistic Regression, Sigmoid and more
Elad Tolochinsky, Ibrahim Jubran, Dan Feldman
Coreset (or core-set) is a small weighted \emph{subset} of an input set with respect to a given \emph{monotonic} function that \emph{provably} a…
Secure -ish Nearest Neighbors Classifier
Hayim Shaul, Dan Feldman, Daniela Rus
In machine learning, classifiers are used to predict a class of a given query based on an existing (classified) database. Given a database S of n d-dimensional points and a d-dimen…