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Found 12 papers, 1 papers with code
Robust Ordinal Regression for Subsets Comparisons with Interactions
This paper is dedicated to a robust ordinal method for learning the preferences of a decision maker between subsets.
Thou Shalt not Pick all Items if Thou are First: of Strategyproof and Fair Picking Sequences
When allocating indivisible items to agents, it is known that the only strategyproof mechanisms that satisfy a set of rather mild conditions are constrained serial dictatorships: given a fixed order over agents, at each step the designated agent chooses a given number of items (depending on her position in the sequence).
Measuring a Priori Voting Power -- Taking Delegations Seriously
We introduce new power indices to measure the a priori voting power of voters in liquid democracy elections where an underlying network restricts delegations.
Cautious Learning of Multiattribute Preferences
This paper is dedicated to a cautious learning methodology for predicting preferences between alternatives characterized by binary attributes (formally, each alternative is seen as a subset of attributes).
Computation and Bribery of Voting Power in Delegative Simple Games
Following Zhang and Grossi~(AAAI 2021), we study in more depth a variant of weighted voting games in which agents' weights are induced by a transitive support structure.
When Can Liquid Democracy Unveil the Truth?
Interestingly, under some hypothesis on either the accuracies of voters or the connectivity of the network, we obtain a polynomial-time $1/2$-approximation algorithm.
Fairness in Influence Maximization through Randomization
Maybe non-surprisingly, we show that the ex-ante values of the computed probabilistic strategies are significantly larger than the (ex-post) fairness values of previous methods.
Fairness
Social and Information Networks
Data Structures and Algorithms
Computer Science and Game Theory
Beyond Pairwise Comparisons in Social Choice: A Setwise Kemeny Aggregation Problem
In this paper, we advocate the use of setwise contests for aggregating a set of input rankings into an output ranking.
The Convergence of Iterative Delegations in Liquid Democracy in a Social Network
We answer several questions on the equilibria of this process in any social network or in social networks that correspond to restricted types of graphs.
Iterative Delegations in Liquid Democracy with Restricted Preferences
In this paper, we study liquid democracy, a collective decision making paradigm which lies between direct and representative democracy.
Optimizing Quantiles in Preference-based Markov Decision Processes
In the Markov decision process model, policies are usually evaluated by expected cumulative rewards.
Quantile Reinforcement Learning
In reinforcement learning, the standard criterion to evaluate policies in a state is the expectation of (discounted) sum of rewards.
