'Latent svm' presentation slideshows

Loss-based Learning with Weak Supervision

Loss-based Learning with Weak Supervision. M. Pawan Kumar. Computer Vision Data. Log (Size). ~ 2000. Segmentation. Information. Computer Vision Data. ~ 1 M. Log (Size). Bounding Box. ~ 2000. Segmentation. Information. Computer Vision Data. > 14 M. ~ 1 M. Log (Size). Image-Level.

1.54k views • 142 slides

Modeling Latent Variable Uncertainty for Loss-based Learning

369 views • 36 slides

Multiple Kernel Learning

November 5, 2013. Multiple Kernel Learning. Hossein Hajimirsadeghi School of Computing Science Simon Fraser University. Introduction - SVM. Max . Margin. s.t. s.t. Regularizer. Loss Function. SVM: Optimization Problem. s.t. SVM: Dual. Primal. s.t. s.t. Dual. SVM-Dual. s.t.

366 views • 32 slides

Intro to DPM

337 views • 20 slides

Intro to DPM

263 views • 20 slides

Discriminative Sub-categorization

Discriminative Sub-categorization. Minh Hoai Nguyen, Andrew Zisserman University of Oxford. S ub-categorization. Head-images. Sub-category 1. Sub-category 2. Sub-category 3. Sub-category 4. Sub-category 5. Why sub-categorization?. - Better head detector.

285 views • 14 slides

Weakly Supervised Action Recognition

136 views • 1 slides