10 citations · 12 across the 3 of their papers we have counts for
7 papers
Deterministic Sensitivity Oracles for Diameter, Eccentricities and All Pairs Distances
Davide Bilò, Keerti Choudhary, Sarel Cohen +2
We construct data structures for extremal and pairwise distances in directed graphs in the presence of transient edge failures. Henzinger et al. [ITCS 2017] initiated the study of…
Non-Volatile Memory Accelerated Geometric Multi-Scale Resolution Analysis
Andrew Wood, Moshik Hershcovitch, Daniel Waddington +5
Dimensionality reduction algorithms are standard tools in a researcher's toolbox. Dimensionality reduction algorithms are frequently used to augment downstream tasks such as machin…
What's Wrong with Deep Learning in Tree Search for Combinatorial Optimization
Maximilian Böther, Otto Kißig, Martin Taraz +3
Combinatorial optimization lies at the core of many real-world problems. Especially since the rise of graph neural networks (GNNs), the deep learning community has been developing…
Space-Efficient Fault-Tolerant Diameter Oracles
Davide Bilò, Sarel Cohen, Tobias Friedrich +1
We design -edge fault-tolerant diameter oracles (-FDOs). We preprocess a given graph on vertices and edges, and a positive integer , to construct a data struct…
Near-Optimal Deterministic Single-Source Distance Sensitivity Oracles
Davide Bilò, Sarel Cohen, Tobias Friedrich +1
Given a graph with a source vertex , the Single Source Replacement Paths (SSRP) problem is to compute, for every vertex and edge , the length of a shortest pat…
ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation
Sharon Fogel, Hadar Averbuch-Elor, Sarel Cohen +2
Optical character recognition (OCR) systems performance have improved significantly in the deep learning era. This is especially true for handwritten text recognition (HTR), where…