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Found 10 papers, 1 papers with code
Classification with Partially Private Features
In this paper, we consider differentially private classification when some features are sensitive, while the rest of the features and the label are not.
Online Learning and Bandits with Queried Hints
For stochastic MAB, we also consider a stronger model where a probe reveals the reward values of the probed arms, and show that in this case, $k=3$ probes suffice to achieve parameter-independent constant regret, $O(n^2)$.
Robust Allocations with Diversity Constraints
We show in a formal sense that the Nash Welfare rule that maximizes product of agent values is uniquely positioned to be robust when diversity constraints are introduced, while almost all other natural allocation rules fail this criterion.
Fair for All: Best-effort Fairness Guarantees for Classification
Instead, we propose a fairness notion whose guarantee, on each group $g$ in a class $\mathcal{G}$, is relative to the performance of the best classifier on $g$.
Adaptive Probing Policies for Shortest Path Routing
Inspired by traffic routing applications, we consider the problem of finding the shortest path from a source $s$ to a destination $t$ in a graph, when the lengths of the edges are unknown.
Proportionally Fair Clustering
We extend the fair machine learning literature by considering the problem of proportional centroid clustering in a metric context.
Random Dictators with a Random Referee: Constant Sample Complexity Mechanisms for Social Choice
Constant sample complexity means that the mechanism (potentially randomized) only uses a constant number of ordinal queries regardless of the number of voters and alternatives.
Sequential Deliberation for Social Choice
In large scale collective decision making, social choice is a normative study of how one ought to design a protocol for reaching consensus.
Computer Science and Game Theory Multiagent Systems
Approximation Algorithms for Bayesian Multi-Armed Bandit Problems
We show that by restricting the state spaces of arms we can find single arm policies and that these single arm policies can be combined into global (near) index policies where the approximate version of the exchange property is true in expectation.
