Learning about social learning in MOOCs: From statistical analysis to generative model

CG Brinton, M Chiang, S Jain, H Lam… - IEEE transactions on …, 2014 - ieeexplore.ieee.org
We study user behavior in the courses offered by a major massive online open course
(MOOC) provider during the summer of 2013. Since social learning is a key element of …

Liquid democracy: An algorithmic perspective

A Kahng, S Mackenzie, A Procaccia - Journal of Artificial Intelligence …, 2021 - jair.org
We study liquid democracy, a collective decision making paradigm that allows voters to
transitively delegate their votes, through an algorithmic lens. In our model, there are two …

Optimal algorithms for stochastic contextual preference bandits

A Saha - Advances in Neural Information Processing …, 2021 - proceedings.neurips.cc
We consider the problem of preference bandits in the contextual setting. At each round, the
learner is presented with a context set of $ K $ items, chosen randomly from a potentially …

Personalized and situation-aware multimodal route recommendations: the FAVOUR algorithm

P Campigotto, C Rudloff, M Leodolter… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Route choice in multimodal networks shows a considerable variation between different
individuals and the current situational context. Personalization and situation awareness of …

Minimax-optimal inference from partial rankings

B Hajek, S Oh, J Xu - Advances in Neural Information …, 2014 - proceedings.neurips.cc
This paper studies the problem of rank aggregation under the Plackett-Luce model. The goal
is to infer a global ranking and related scores of the items, based on partial rankings …

A local-dominance theory of voting equilibria

R Meir, O Lev, JS Rosenschein - … of the fifteenth ACM conference on …, 2014 - dl.acm.org
We suggest a new model for strategic voting based on local dominance, where voters
consider a set of possible outcomes without assigning probabilities to them. We prove that …

Group decision making under uncertain preferences: powered by AI, empowered by AI

L Xia - Annals of the New York Academy of Sciences, 2022 - Wiley Online Library
Group decision making is an important, long‐standing, and ubiquitous problem in all
societies, where collective decisions must be made by a group of agents despite individual …

Computing parametric ranking models via rank-breaking

HA Soufiani, D Parkes, L Xia - International Conference on …, 2014 - proceedings.mlr.press
Rank breaking is a methodology introduced by Azari Soufiani et al.(2013a) for applying a
Generalized Method of Moments (GMM) algorithm to the estimation of parametric ranking …

Statistical foundations of virtual democracy

A Kahng, MK Lee, R Noothigattu… - International …, 2019 - proceedings.mlr.press
Virtual democracy is an approach to automating decisions, by learning models of the
preferences of individual people, and, at runtime, aggregating the predicted preferences of …

Structure discovery in Bayesian networks by sampling partial orders

T Niinim, P Parviainen, M Koivisto - Journal of Machine Learning …, 2016 - jmlr.org
Data in the form of pairwise comparisons arises in many domains, including preference
elicitation, sporting competitions, and peer grading among others. We consider parametric …