activity
20132026
most citedLimits on correlations in networks for quantum and no-signaling resources

73 citations · 276 across the 38 of their papers we have counts for

collaborators
Showing 2018Show all

10 papers · 1 filter

cs.CR2018★ 15 cited

Towards Secure and Efficient Payment Channels

Georgia Avarikioti, Felix Laufenberg, Jakub Sliwinski +2

Micropayment channels are the most prominent solution to the limitation on transaction throughput in current blockchain systems. However, in practice channels are risky because par…

cs.CG2018

High Dimensional Clustering with -nets

Georgia Avarikioti, Alain Ryser, Yuyi Wang +1

Clustering, a fundamental task in data science and machine learning, groups a set of objects in such a way that objects in the same cluster are closer to each other than to those i…

cs.DS2018★ 3 cited

Algorithmic Blockchain Channel Design

Georgia Avarikioti, Yuyi Wang, Roger Wattenhofer

Payment networks, also known as channels, are a most promising solution to the throughput problem of cryptocurrencies. In this paper we study the design of capital-efficient paymen…

cs.DS2018

Payment Network Design with Fees

Georgia Avarikioti, Gerrit Janssen, Yuyi Wang +1

Payment channels are the most prominent solution to the blockchain scalability problem. We introduce the problem of network design with fees for payment channels from the perspecti…

cs.SD2018★ 63 cited

MIDI-VAE: Modeling Dynamics and Instrumentation of Music with Applications to Style Transfer

Gino Brunner, Andres Konrad, Yuyi Wang +1

We introduce MIDI-VAE, a neural network model based on Variational Autoencoders that is capable of handling polyphonic music with multiple instrument tracks, as well as modeling th…

cs.SD2018★ 3 cited

Symbolic Music Genre Transfer with CycleGAN

Gino Brunner, Yuyi Wang, Roger Wattenhofer +1

Deep generative models such as Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs) have recently been applied to style and domain transfer for images, and in…

cs.LG2018

VC-Dimension Based Generalization Bounds for Relational Learning

Ondrej Kuzelka, Yuyi Wang, Steven Schockaert

In many applications of relational learning, the available data can be seen as a sample from a larger relational structure (e.g. we may be given a small fragment from some social n…

cs.DC2018

Byzantine Preferential Voting

Darya Melnyk, Yuyi Wang, Roger Wattenhofer

In the Byzantine agreement problem, n nodes with possibly different input values aim to reach agreement on a common value in the presence of t < n/3 Byzantine nodes which represent…

cs.AI2018★ 2 cited

PAC-Reasoning in Relational Domains

Ondrej Kuzelka, Yuyi Wang, Jesse Davis +1

We consider the problem of predicting plausible missing facts in relational data, given a set of imperfect logical rules. In particular, our aim is to provide bounds on the (expect…

cs.CL2018★ 7 cited

Natural Language Multitasking: Analyzing and Improving Syntactic Saliency of Hidden Representations

Gino Brunner, Yuyi Wang, Roger Wattenhofer +1

We train multi-task autoencoders on linguistic tasks and analyze the learned hidden sentence representations. The representations change significantly when translation and part-of-…