All Stories

  1. Causal Representation Learning from Network Data
  2. Learning Peer Influence Probabilities with Linear Contextual Bandits
  3. Framework for Variable-lag Motif Following Relation Inference In Time Series using Matrix Profile analysis
  4. Leveraging Heterogeneous Spillover in Maximizing Contextual Bandit Rewards
  5. Fairness of Interaction in Ranking under Position, Selection, and Trust Bias
  6. Understanding the Effects of Intergroup Interactions on Polarization
  7. Register-based census in Thailand: A case study in Chachoengsao province
  8. Improving Data-driven Heterogeneous Treatment Effect Estimation Under Structure Uncertainty
  9. RGRecSys
  10. Inferring causal effects with arbitrary time delays in time series.
  11. Causal Inference from Network Data
  12. Propensity-Independent Bias Recovery in Offline Learning-to-Rank Systems
  13. Identifying Linear Models in Multi-Resolution Population Data Using Minimum Description Length Principle to Predict Household Income
  14. A nonparametric framework for inferring orders of categorical data from category-real pairs
  15. Framework for Inferring Following Strategies from Time Series of Movement Data
  16. Correcting for Selection Bias in Learning-to-rank Systems
  17. ipADMIXTURE: R package for inferring sub-population clusters based on genetic admixture
  18. Moving Beyond Set-It-And-Forget-It Privacy Settings on Social Media
  19. Mining and modeling complex leadership–followership dynamics of movement data
  20. Variable-Lag Granger Causality for Time Series Analysis
  21. Traits of Leaders in Movement Initiation: Classification and Identification
  22. Coordination Event Detection and Initiator Identification in Time Series Data
  23. Mining and Modeling Complex Leadership Dynamics of Movement data
  24. Framework for Inferring Leadership Dynamics of Complex Movement from Time Series
  25. Identifying Traits of Leaders in Movement Initiation
  26. iNJclust: Iterative Neighbor-Joining Tree Clustering Framework for Inferring Population Structure
  27. Improved iterative pruning principal component analysis with graph-theoretic hierarchical clustering