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11/01/2022
Invited Paper: Fault-tolerant and Expressive Cross-Chain Swaps
Cross-chain swaps enable exchange of different assets that reside on dif...
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06/14/2022
Cross-Chain State Machine Replication
This paper considers the classical state machine replication (SMR) probl...
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04/20/2022
Distributed Runtime Verification of Metric Temporal Properties for Cross-Chain Protocols
Transactions involving multiple blockchains are implemented by cross-cha...
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10/18/2021
Presentation and Publication: Loss and Slippage in Networks of Automated Market Makers
Automated market makers (AMMs) are smart contracts that automatically tr...
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09/24/2021
Invited Paper: Failure is (literally) an Option: Atomic Commitment vs Optionality in Decentralized Finance
Many aspects of blockchain-based decentralized finance can be understood...
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07/29/2021
VBR: Version Based Reclamation
Safe lock-free memory reclamation is a difficult problem. Existing solut...
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05/31/2021
Composing Networks of Automated Market Makers
Automated market makers (AMMs) are automata that trade electronic assets...
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05/14/2021
Linearizability: a Typo
Linearizability is the de facto consistency condition for concurrent obj...
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05/13/2021
Hedging Against Sore Loser Attacks in Cross-Chain Transactions
A *sore loser attack* in cross-blockchain commerce rises when one party ...
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01/15/2021
Cryptoasset Competition and Market Concentration in the Presence of Network Effects
When network products and services become more valuable as their userbas...
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05/28/2019
Clairvoyant State Machine Replication
We propose a new protocol for the generalized consensus problem in async...
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05/23/2019
Cross-chain Deals and Adversarial Commerce
Modern distributed data management systems face a new challenge: how can...
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01/05/2019
An Empirical Study of Speculative Concurrency in Ethereum Smart Contracts
We use historical data to estimate the potential benefit of speculative ...
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11/21/2018
SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks
The performance and efficiency of distributed training of Deep Neural Ne...
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01/29/2018
