22 citations · 40 across the 5 of their papers we have counts for
9 papers
Algorithmic Learning Foundations for Common Law
Jason D. Hartline, Daniel W. Linna, Liren Shan +1
This paper looks at a common law legal system as a learning algorithm, models specific features of legal proceedings, and asks whether this system learns efficiently. A particular…
Near-optimal Algorithms for Explainable k-Medians and k-Means
Konstantin Makarychev, Liren Shan
We consider the problem of explainable -medians and -means introduced by Dasgupta, Frost, Moshkovitz, and Rashtchian~(ICML 2020). In this problem, our goal is to find a thres…
Edge Deletion Algorithms for Minimizing Spread in SIR Epidemic Models
Yuhao Yi, Liren Shan, Philip E. Paré +1
This paper studies algorithmic strategies to effectively reduce the number of infections in susceptible-infected-recovered (SIR) epidemic models. We consider a Markov chain SIR mod…
Improved Guarantees for k-means++ and k-means++ Parallel
Konstantin Makarychev, Aravind Reddy, Liren Shan
In this paper, we study k-means++ and k-means++ parallel, the two most popular algorithms for the classic k-means clustering problem. We provide novel analyses and show improved ap…
Stochastic Linear Optimization with Adversarial Corruption
Yingkai Li, Edmund Y. Lou, Liren Shan
We extend the model of stochastic bandits with adversarial corruption (Lykouriset al., 2018) to the stochastic linear optimization problem (Dani et al., 2008). Our algorithm is agn…
Improving information centrality of a node in complex networks by adding edges
Liren Shan, Yuhao Yi, Zhongzhi Zhang
The problem of increasing the centrality of a network node arises in many practical applications. In this paper, we study the optimization problem of maximizing the information cen…