Variance Optimized Bagging. - Philip Derbeko; Ran El-Yaniv; Ron Meir (ECML, 2002)

Error Bounds for Transductive Learning via Compression and Clustering. - Philip Derbeko; Ran El-Yaniv; Ron Meir (NIPS, 2003)

Explicit Learning Curves for Transduction and Application to Clustering and Compression Algorithms. - Philip Derbeko; Ran El-Yaniv; Ron Meir (J. Artif. Intell. Res., 2004)

Concise essence-preserving big data representation. - Philip Derbeko; Shlomi Dolev; Ehud Gudes; Jeffrey D. Ullman (IEEE BigData, 2016)

Security and privacy aspects in MapReduce on clouds: A survey. - Philip Derbeko; Shlomi Dolev; Ehud Gudes; Shantanu Sharma 001 (Comput. Sci. Rev., 2016)

Efficient and private approximations of distributed databases calculations. - Philip Derbeko; Shlomi Dolev; Ehud Gudes; Jeffrey D. Ullman (IEEE BigData, 2017)

Privacy via Maintaining Small Similitude Data for Big Data Statistical Representation. - Philip Derbeko; Shlomi Dolev; Ehud Gudes (CSCML, 2018)

Deep Neural Networks as Similitude Models for Sharing Big Data. - Philip Derbeko; Shlomi Dolev; Ehud Gudes (IEEE BigData, 2019)

MLDStore - DNNs as Similitude Models for Sharing Big Data (Brief Announcement). - Philip Derbeko; Shlomi Dolev; Ehud Gudes (CSCML, 2019)

Upper bounds for multi-level multi-server paging. - Shlomi Dolev; Anat Eyal; Danny Hendler; Philip Derbeko; Marina Sadetsky (Inf. Process. Lett., 2019)

PolyDNN Polynomial Representation of NN for Communication-Less SMPC Inference. - Philip Derbeko; Shlomi Dolev (CSCML, 2021)

Wavelet-based dynamic and privacy-preserving similitude data models for edge computing. - Philip Derbeko; Shlomi Dolev; Ehud Gudes (Wirel. Networks, 2021)

Efficient and Privacy Preserving Approximation of Distributed Statistical Queries. - Philip Derbeko; Shlomi Dolev; Ehud Gudes; Jeffrey D. Ullman (IEEE Trans. Big Data, 2022)