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most citedMethods for Interpreting and Understanding Deep Neural Networks

2.8k citations

Showing 2010Show all

29 papers · 1 filter

cs.NE2010

Faster Black-Box Algorithms Through Higher Arity Operators

Benjamin Doerr, Daniel Johannsen, Timo Kötzing +3

We extend the work of Lehre and Witt (GECCO 2010) on the unbiased black-box model by considering higher arity variation operators. In particular, we show that already for binary op…

cs.DS2010

Quasirandom Rumor Spreading

Benjamin Doerr, Tobias Friedrich, Thomas Sauerwald

We propose and analyze a quasirandom analogue of the classical push model for disseminating information in networks ("randomized rumor spreading"). In the classical model, in each…

cs.CG2010

Treemaps with Bounded Aspect Ratio

Mark de Berg, Bettina Speckmann, Vincent van der Weele

Treemaps are a popular technique to visualize hierarchical data. The input is a weighted tree $\tree$ where the weight of each node is the sum of the weights of its children. A tre…

cs.DS2010★ 2 cited

Asymptotically Optimal Randomized Rumor Spreading

Benjamin Doerr, Mahmoud Fouz

We propose a new protocol solving the fundamental problem of disseminating a piece of information to all members of a group of n players. It builds upon the classical randomized ru…

cs.NE2010

Non-Existence of Linear Universal Drift Functions

Benjamin Doerr, Daniel Johannsen, Carola Winzen

Drift analysis has become a powerful tool to prove bounds on the runtime of randomized search heuristics. It allows, for example, fairly simple proofs for the classical problem how…

cs.DS2010★ 22 cited

On the Complexity of Real Root Isolation

Michael Sagraloff

We introduce a new approach to isolate the real roots of a square-free polynomial with real coefficients. It is assumed that each coefficient of can be…