33 citations · 44 across the 7 of their papers we have counts for
7 papers · 1 filter
The Power of Random Symmetry-Breaking in Nakamoto Consensus
Lili Su, Quanquan C. Liu, Neha Narula
Nakamoto consensus underlies the security of many of the world's largest cryptocurrencies, such as Bitcoin and Ethereum. Common lore is that Nakamoto consensus only achieves consis…
Distributed Learning with Adversarial Agents Under Relaxed Network Condition
Pooja Vyavahare, Lili Su, Nitin H. Vaidya
This work studies the problem of non-Bayesian learning over multi-agent network when there are some adversarial (faulty) agents in the network. At each time step, each non-faulty a…
Collaboratively Learning the Best Option on Graphs, Using Bounded Local Memory
Lili Su, Martin Zubeldia, Nancy Lynch
We consider multi-armed bandit problems in social groups wherein each individual has bounded memory and shares the common goal of learning the best arm/option. We say an individual…
Securing Distributed Gradient Descent in High Dimensional Statistical Learning
Lili Su, Jiaming Xu
We consider unreliable distributed learning systems wherein the training data is kept confidential by external workers, and the learner has to interact closely with those workers t…
Defending Non-Bayesian Learning against Adversarial Attacks
Lili Su, Nitin H. Vaidya
This paper addresses the problem of non-Bayesian learning over multi-agent networks, where agents repeatedly collect partially informative observations about an unknown state of th…
Asynchronous Distributed Hypothesis Testing in the Presence of Crash Failures
Lili Su, Nitin H. Vaidya
This paper addresses the problem of distributed hypothesis testing in multi-agent networks, where agents repeatedly collect local observations about an unknown state of the world,…