activity
20182022
most citedNearly Linear Row Sampling Algorithm for Quantile Regression

2 citations · 4 across the 4 of their papers we have counts for

collaborators

6 papers

cs.GT2022

Efficient Algorithms for Planning with Participation Constraints

Hanrui Zhang, Yu Cheng, Vincent Conitzer

We consider the problem of planning with participation constraints introduced in [Zhang et al., 2022]. In this problem, a principal chooses actions in a Markov decision process, re…

cs.GT20212 cited

Automated Mechanism Design for Classification with Partial Verification

Hanrui Zhang, Yu Cheng, Vincent Conitzer

We study the problem of automated mechanism design with partial verification, where each type can (mis)report only a restricted set of types (rather than any other type), induced b…

cs.LG2021

Classification with Strategically Withheld Data

Anilesh K. Krishnaswamy, Haoming Li, David Rein +2

Machine learning techniques can be useful in applications such as credit approval and college admission. However, to be classified more favorably in such contexts, an agent may dec…

cs.DS20202 cited

Nearly Linear Row Sampling Algorithm for Quantile Regression

Yi Li, Ruosong Wang, Lin Yang +1

We give a row sampling algorithm for the quantile loss function with sample complexity nearly linear in the dimensionality of the data, improving upon the previous best algorithm w…

cs.AI2020

Mitigating Manipulation in Peer Review via Randomized Reviewer Assignments

Steven Jecmen, Hanrui Zhang, Ryan Liu +3

We consider three important challenges in conference peer review: (i) reviewers maliciously attempting to get assigned to certain papers to provide positive reviews, possibly as pa…

cs.DS2018

Capturing Complementarity in Set Functions by Going Beyond Submodularity/Subadditivity

Wei Chen, Shang-Hua Teng, Hanrui Zhang

We introduce two new "degree of complementarity" measures, which we refer to, respectively, as supermodular width and superadditive width. Both are formulated based on natural witn…