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Found 4 papers, 2 papers with code
Label Budget Allocation in Multi-Task Learning
How should the label budget (i. e. the amount of money spent on labeling) be allocated among different tasks to achieve optimal multi-task performance?
CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning
Semi-supervised learning on class-imbalanced data, although a realistic problem, has been under studied.
LOH and behold: Web-scale visual search, recommendation and clustering using Locally Optimized Hashing
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-scale search, recommendation, clustering, and deduplication.
Cross-dimensional Weighting for Aggregated Deep Convolutional Features
We propose a simple and straightforward way of creating powerful image representations via cross-dimensional weighting and aggregation of deep convolutional neural network layer outputs.
Ranked #13 on
Image Retrieval
on RParis (Medium)
