Not enough data to create a plot.
Try a different view from the menu above.
Nikhil Ghosh
Landmark Ordinal Embedding
Nikhil Ghosh, Yuxin Chen, Yisong Yue
Neural Information Processing Systems http://nips.cc/
Landmark Ordinal Embedding
Nikhil Ghosh, Yuxin Chen, Yisong Yue
In this paper, we aim to learn a low-dimensional Euclidean representation from a set of constraints of the form "item j is closer to item i than item k". Existing approaches for this "ordinal embedding" problem require expensive optimization procedures, which cannot scale to handle increasingly larger datasets. To address this issue, we propose a landmark-based strategy, which we call Landmark Ordinal Embedding (LOE).