34 citations · 49 across the 4 of their papers we have counts for
4 papers
Label Budget Allocation in Multi-Task Learning
Ximeng Sun, Kihyuk Sohn, Kate Saenko +2
The cost of labeling data often limits the performance of machine learning systems. In multi-task learning, related tasks provide information to each other and improve overall perf…
CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning
Chen Wei, Kihyuk Sohn, Clayton Mellina +2
Semi-supervised learning on class-imbalanced data, although a realistic problem, has been under studied. While existing semi-supervised learning (SSL) methods are known to perform…
LOH and behold: Web-scale visual search, recommendation and clustering using Locally Optimized Hashing
Yannis Kalantidis, Lyndon Kennedy, Huy Nguyen +2
We propose a novel hashing-based matching scheme, called Locally Optimized Hashing (LOH), based on a state-of-the-art quantization algorithm that can be used for efficient, large-s…
Cross-dimensional Weighting for Aggregated Deep Convolutional Features
Yannis Kalantidis, Clayton Mellina, Simon Osindero
We propose a simple and straightforward way of creating powerful image representations via cross-dimensional weighting and aggregation of deep convolutional neural network layer ou…