Philip Derbeko

17 papers Journal 9Unranked 8

Year	Rank	Type	Title / Venue / Authors
2022	J	`jnl`	Efficient and Privacy Preserving Approximation of Distributed Statistical Queries. IEEE Trans. Big Data Philip Derbeko, Shlomi Dolev, Ehud Gudes, Jeffrey D. Ullman
2021	—	`conf`	PolyDNN Polynomial Representation of NN for Communication-Less SMPC Inference. CSCML Philip Derbeko, Shlomi Dolev
2021	J	`jnl`	PolyDNN: Polynomial Representation of NN for Communication-less SMPC Inference. CoRR Philip Derbeko, Shlomi Dolev
2021	J	`jnl`	Wavelet-based dynamic and privacy-preserving similitude data models for edge computing. Wirel. Networks Philip Derbeko, Shlomi Dolev, Ehud Gudes
2019	—	`conf`	Deep Neural Networks as Similitude Models for Sharing Big Data. IEEE BigData Philip Derbeko, Shlomi Dolev, Ehud Gudes
2019	—	`conf`	MLDStore - DNNs as Similitude Models for Sharing Big Data (Brief Announcement). CSCML Philip Derbeko, Shlomi Dolev, Ehud Gudes
2019	J	`jnl`	Upper bounds for multi-level multi-server paging. Inf. Process. Lett. Shlomi Dolev, Anat Eyal, Danny Hendler, Philip Derbeko, Marina Sadetsky
2018	—	`conf`	Privacy via Maintaining Small Similitude Data for Big Data Statistical Representation. CSCML Philip Derbeko, Shlomi Dolev, Ehud Gudes
2017	—	`conf`	Efficient and private approximations of distributed databases calculations. IEEE BigData Philip Derbeko, Shlomi Dolev, Ehud Gudes, Jeffrey D. Ullman
2016	—	`conf`	Concise essence-preserving big data representation. IEEE BigData Philip Derbeko, Shlomi Dolev, Ehud Gudes, Jeffrey D. Ullman
2016	J	`jnl`	Efficient and Private Approximations of Distributed Databases Calculations. CoRR Philip Derbeko, Shlomi Dolev, Ehud Gudes, Jeffrey D. Ullman
2016	J	`jnl`	Security and Privacy Aspects in MapReduce on Clouds: A Survey. CoRR Philip Derbeko, Shlomi Dolev, Ehud Gudes, Shantanu Sharma
2016	J	`jnl`	Security and privacy aspects in MapReduce on clouds: A survey. Comput. Sci. Rev. Philip Derbeko, Shlomi Dolev, Ehud Gudes, Shantanu Sharma
2011	J	`jnl`	Explicit Learning Curves for Transduction and Application to Clustering and Compression Algorithms CoRR Philip Derbeko, Ran El-Yaniv, Ron Meir
2004	J	`jnl`	Explicit Learning Curves for Transduction and Application to Clustering and Compression Algorithms. J. Artif. Intell. Res. Philip Derbeko, Ran El-Yaniv, Ron Meir
2003	—	`conf`	Error Bounds for Transductive Learning via Compression and Clustering. NIPS Philip Derbeko, Ran El-Yaniv, Ron Meir
2002	—	`conf`	Variance Optimized Bagging. ECML Philip Derbeko, Ran El-Yaniv, Ron Meir