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Found 7 papers, 3 papers with code
Contrastive Language-Action Pre-training for Temporal Localization
Long-form video understanding requires designing approaches that are able to temporally localize activities or language.
Contrastive Learning
Few Shot Temporal Action Localization
+3
Analysis and Optimization of Loss Functions for Multiclass, Top-k, and Multilabel Classification
In particular, we find that it is possible to obtain effective multilabel classifiers on Pascal VOC using a single label per image for training, while the gap between multiclass and multilabel methods on MS COCO is more significant.
Loss Functions for Top-k Error: Analysis and Insights
In the experiments, we compare on various datasets all of the proposed and established methods for top-k error optimization.
Top-k Multiclass SVM
Class ambiguity is typical in image classification problems with a large number of classes.
Efficient Output Kernel Learning for Multiple Tasks
The paradigm of multi-task learning is that one can achieve better generalization by learning tasks jointly and thus exploiting the similarity between the tasks rather than learning them independently of each other.
Scalable Multitask Representation Learning for Scene Classification
The underlying idea of multitask learning is that learning tasks jointly is better than learning each task individually.
Learning Using Privileged Information: SVM+ and Weighted SVM
Prior knowledge can be used to improve predictive performance of learning algorithms or reduce the amount of data required for training.
