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most citedMethods for Interpreting and Understanding Deep Neural Networks

2.8k citations

Showing 2014Show all

40 papers · 1 filter

cs.DC2014★ 5 cited

Fast Partial Distance Estimation and Applications

Christoph Lenzen, Boaz Patt-Shamir

We study approximate distributed solutions to the weighted {\it all-pairs-shortest-paths} (APSP) problem in the CONGEST model. We obtain the following results. A deterministic…

cs.DS2014★ 1 cited

Algorithms in the Ultra-Wide Word Model

Arash Farzan, Alejandro López-Ortiz, Patrick K. Nicholson +1

The effective use of parallel computing resources to speed up algorithms in current multi-core parallel architectures remains a difficult challenge, with ease of programming playin…

cs.DS2014★ 3 cited

Queries on LZ-Bounded Encodings

Djamal Belazzougui, Travis Gagie, Paweł Gawrychowski +4

We describe a data structure that stores a string in space similar to that of its Lempel-Ziv encoding and efficiently supports access, rank and select queries. These queries ar…

cs.CV2014★ 88 cited

Towards Scene Understanding with Detailed 3D Object Representations

M. Zeeshan Zia, Michael Stark, Konrad Schindler

Current approaches to semantic image and scene understanding typically employ rather simple object representations such as 2D or 3D bounding boxes. While such coarse models are rob…

cs.CV2014★ 99 cited

Ten Years of Pedestrian Detection, What Have We Learned?

Rodrigo Benenson, Mohamed Omran, Jan Hosang +1

Paper-by-paper results make it easy to miss the forest for the trees.We analyse the remarkable progress of the last decade by discussing the main ideas explored in the 40+ detector…

cs.CG2014★ 1 cited

Uniformity of point samples in metric spaces using gap ratio

Arijit Bishnu, Sameer Desai, Arijit Ghosh +2

Teramoto et al. defined a new measure called the gap ratio that measures the uniformity of a finite point set sampled from , a bounded subset of . We generali…