Search Results for author: Maksim Lapin

Found 6 papers, 3 papers with code

Analysis and Optimization of Loss Functions for Multiclass, Top-k, and Multilabel Classification

1 code implementation12 Dec 2016 Maksim Lapin, Matthias Hein, Bernt Schiele

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.

General Classification Image Classification

Loss Functions for Top-k Error: Analysis and Insights

1 code implementation CVPR 2016 Maksim Lapin, Matthias Hein, Bernt Schiele

In the experiments, we compare on various datasets all of the proposed and established methods for top-k error optimization.

Top-k Multiclass SVM

1 code implementation NeurIPS 2015 Maksim Lapin, Matthias Hein, Bernt Schiele

Class ambiguity is typical in image classification problems with a large number of classes.

General Classification Image Classification

Efficient Output Kernel Learning for Multiple Tasks

no code implementations NeurIPS 2015 Pratik Jawanpuria, Maksim Lapin, Matthias Hein, Bernt Schiele

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.

Multi-Task Learning

Learning Using Privileged Information: SVM+ and Weighted SVM

no code implementations13 Jun 2013 Maksim Lapin, Matthias Hein, Bernt Schiele

Prior knowledge can be used to improve predictive performance of learning algorithms or reduce the amount of data required for training.

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