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Dive into the research topics where Benedikt Bünz is active.

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Featured researches published by Benedikt Bünz.


international cryptology conference | 2018

Verifiable Delay Functions.

Dan Boneh; Joseph Bonneau; Benedikt Bünz; Ben Fisch

We study the problem of building a verifiable delay function (VDF). A \(\text {VDF}\)requires a specified number of sequential steps to evaluate, yet produces a unique output that can be efficiently and publicly verified. \(\text {VDF}\)s have many applications in decentralized systems, including public randomness beacons, leader election in consensus protocols, and proofs of replication. We formalize the requirements for \(\text {VDF}\)s and present new candidate constructions that are the first to achieve an exponential gap between evaluation and verification time.


international joint conference on artificial intelligence | 2017

Computing Bayes-Nash Equilibria in Combinatorial Auctions with Continuous Value and Action Spaces

Vitor Bosshard; Benedikt Bünz; Benjamin Lubin; Sven Seuken

Combinatorial auctions (CAs) are widely used in practice, which is why understanding their incentive properties is an important problem. However, finding Bayes-Nash equilibria (BNEs) of CAs analytically is tedious, and prior algorithmic work has only considered limited solution concepts (e.g. restricted action spaces). In this paper, we present a fast, general algorithm for computing symmetric pure ε-BNEs in CAs with continuous values and actions. In contrast to prior work, we separate the search phase (for finding the BNE) from the verification step (for estimating the ε), and always consider the full (continuous) action space in the best response computation. We evaluate our method in the well-studied LLG domain, against a benchmark of 16 CAs for which analytical BNEs are known. In all cases, our algorithm converges quickly, matching the known results with high precision. Furthermore, for CAs with quasi-linear utility functions and independently distributed valuations, we derive a theoretical bound on ε. Finally, we introduce the new Multi-Minded LLLLGG domain with eight goods and six bidders, and apply our algorithm to finding an equilibrium in this domain. Our algorithm is the first to find an accurate BNE in a CA of this size.


computer and communications security | 2015

Provisions: Privacy-preserving Proofs of Solvency for Bitcoin Exchanges

Gaby G. Dagher; Benedikt Bünz; Joseph Bonneau; Jeremy Clark; Dan Boneh


national conference on artificial intelligence | 2015

A faster core constraint generation algorithm for combinatorial auctions

Benedikt Bünz; Sven Seuken; Benjamin Lubin


arXiv: Artificial Intelligence | 2018

Learning a SAT Solver from Single-Bit Supervision.

Daniel Selsam; Matthew Lamm; Benedikt Bünz; Percy Liang; Leonardo Mendonça de Moura; David L. Dill


auctions market mechanisms and their applications | 2015

New Core-Selecting Payment Rules with Better Fairness and Incentive Properties

Benjamin Lubin; Benedikt Bünz; Sven Seuken


ieee symposium on security and privacy | 2018

Bulletproofs: Short Proofs for Confidential Transactions and More

Benedikt Bünz; Jonathan Bootle; Dan Boneh; Andrew Poelstra; Pieter Wuille; Greg Maxwell


Archive | 2017

Graph Neural Networks and Boolean Satisfiability.

Benedikt Bünz; Matthew Lamm


IACR Cryptology ePrint Archive | 2017

Bulletproofs: Short Proofs for Confidential Transactions and More.

Benedikt Bünz; Jonathan Bootle; Dan Boneh; Andrew Poelstra; Pieter Wuille; Greg Maxwell


economics and computation | 2018

Designing Core-selecting Payment Rules: A Computational Search Approach

Benedikt Bünz; Benjamin Lubin; Sven Seuken

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Jonathan Bootle

University College London

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