3 papers
eess.SP2021
Improving Channel Charting using a Split Triplet Loss and an Inertial Regularizer
Brian Rappaport, Emre Gönültaş, Jakob Hoydis +3
Channel charting is an emerging technology that enables self-supervised pseudo-localization of user equipments by performing dimensionality reduction on large channel-state informa…
stat.ML2018
Multi-View Graph Embedding Using Randomized Shortest Paths
Anuththari Gamage, Brian Rappaport, Shuchin Aeron +1
Real-world data sets often provide multiple types of information about the same set of entities. This data is well represented by multi-view graphs, which consist of several distin…
stat.ML2017
Faster Clustering via Non-Backtracking Random Walks
Brian Rappaport, Anuththari Gamage, Shuchin Aeron
This paper presents VEC-NBT, a variation on the unsupervised graph clustering technique VEC, which improves upon the performance of the original algorithm significantly for sparse…