| M. Pawan Kumar |
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These are some of the talks I gave at various seminars, tutorials
and reading groups. SEMINARS / INVITED TALKS
Ranking with High-Order and Missing Information
Rounding-based Moves for Metric Labeling
Multiplicative Bounds for Metric Labeling
Loss-based Learning with Weak Supervision
Loss-based Visual Learning with Weak Supervision
Multiplicative Bounds for Metric Labeling
Loss-based Learning with Latent Variables
Modeling Latent Variable Uncertainty for Loss-based Learning
Max-Margin Latent Variable Models
Learning to Segment with Diverse Data
Self-Paced Learning for Specific-Class Semantic Segmentation
Curriculum Learning for Latent Structural SVM
Relaxations and Moves for MAP Estimation in MRFs
Hierarchical Graph Cuts for Semi-Metric Labeling
Improved Moves for Truncated Convex Models
An Analysis of Convex Relaxations for MAP Estimation
Invariant Large Margin Nearest Neighbour Classifier
Layered Pictorial Structures for Object Category Segmentation TUTORIALS
Neural Network Verification
Efficient Frank-Wolfe for Dense CRFs and Piecewise Linear CNNs
Graph Cuts and Linear Programming for Energy Minimization
Discrete Optimization in Computer Vision
Visual Learning with Weak Supervision
Inference and Learning for Image Processing and Computer Vision
Introduction to Machine learning
Learning with Inference for Discrete Graphical Models
Markov Models for Computer Vision
MAP Inference in Discrete Models
MAP Estimation Algorithms in Computer Vision READING GROUPS
Exploiting Duality
Junction Tree Algorithm
Introduction to Convex Programming |