75 citations · 84 across the 7 of their papers we have counts for
7 papers
Subspace Determination through Local Intrinsic Dimensional Decomposition: Theory and Experimentation
Ruben Becker, Imane Hafnaoui, Michael E. Houle +2
Axis-aligned subspace clustering generally entails searching through enormous numbers of subspaces (feature combinations) and evaluation of cluster quality within each subspace. In…
Latent Multi-Criteria Ratings for Recommendations
Pan Li, Alexander Tuzhilin
Multi-criteria recommender systems have been increasingly valuable for helping consumers identify the most relevant items based on different dimensions of user experiences. However…
Latent Unexpected and Useful Recommendation
Pan Li, Alexander Tuzhilin
Providing unexpected recommendations is an important task for recommender systems. To do this, we need to start from the expectations of users and deviate from these expectations w…
Inhomogeneous Hypergraph Clustering with Applications
Pan Li, Olgica Milenkovic
Hypergraph partitioning is an important problem in machine learning, computer vision and network analytics. A widely used method for hypergraph partitioning relies on minimizing a…
Efficient Rank Aggregation via Lehmer Codes
Pan Li, Arya Mazumdar, Olgica Milenkovic
We propose a novel rank aggregation method based on converting permutations into their corresponding Lehmer codes or other subdiagonal images. Lehmer codes, also known as inversion…
Multiclass MinMax Rank Aggregation
Pan Li, Olgica Milenkovic
We introduce a new family of minmax rank aggregation problems under two distance measures, the Kendall τ and the Spearman footrule. As the problems are NP-hard, we proceed to descr…