activity
20092026
most citedInterpretable Multi-Objective Reinforcement Learning through Policy Orchestration

23 citations · 173 across the 34 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.LG2019★ 5 cited

Group Fairness in Bandit Arm Selection

Candice Schumann, Zhi Lang, Nicholas Mattei +1

We propose a novel formulation of group fairness with biased feedback in the contextual multi-armed bandit (CMAB) setting. In the CMAB setting, a sequential decision maker must, at…

cs.GT2019

Heuristic Strategies in Uncertain Approval Voting Environments

Jaelle Scheuerman, Jason L. Harman, Nicholas Mattei +1

In many collective decision making situations, agents vote to choose an alternative that best represents the preferences of the group. Agents may manipulate the vote to achieve a b…

cs.CL2019

Infusing Knowledge into the Textual Entailment Task Using Graph Convolutional Networks

Pavan Kapanipathi, Veronika Thost, Siva Sankalp Patel +10

Textual entailment is a fundamental task in natural language processing. Most approaches for solving the problem use only the textual content present in training data. A few approa…

cs.GT2019★ 12 cited

The Constrained Round Robin Algorithm for Fair and Efficient Allocation

Haris Aziz, Xin Huang, Nicholas Mattei +1

We consider a multi-agent resource allocation setting that models the assignment of papers to reviewers. A recurring issue in allocation problems is the compatibility of welfare/ef…

cs.GT2019★ 2 cited

Heuristics in Multi-Winner Approval Voting

Jaelle Scheuerman, Jason L. Harman, Nicholas Mattei +1

In many real world situations, collective decisions are made using voting. Moreover, scenarios such as committee or board elections require voting rules that return multiple winner…