M. Pawan Kumar












These are some of the talks I gave at various seminars, tutorials and reading groups.
In order to access the slides, please contact me via email.


Ranking with High-Order and Missing Information
Oxford Robotics Research Group Seminar, 2014
Berkeley-INRIA-Stanford Symposium, 2014
Universite Paris Est Seminar, 2014

Rounding-based Moves for Metric Labeling
Swedish Artificial Intelligence Society Workshop, 2014
International Insitute of Information Technology (IIIT) Seminar, 2014
Xerox Research Center Europe (XRCE) Seminar, 2014

Multiplicative Bounds for Metric Labeling
European Conference on Operations Research (EURO), 2013

Loss-based Learning with Weak Supervision
Stanford Vision Group Seminar, 2013

Loss-based Visual Learning with Weak Supervision
Berkeley-INRIA-Stanford Symposium, 2013

Multiplicative Bounds for Metric Labeling
Workshop on Discrete Graphical Models and Combinatorial Optimization, University of Heidelberg, 2012
Ecole Normale Superieure (ENS) de Cachan Seminar, 2013
Czech Technical University (CTU) Seminar, 2013

Loss-based Learning with Latent Variables
Workshop on Statistics, Learning and Variational Methods in Imaging, University of Cambridge, 2012
Oxford Robotics Research Group Seminar, 2012
Institute of Science and Technology - Austria, 2012

Modeling Latent Variable Uncertainty for Loss-based Learning
Berkeley-INRIA-Stanford Symposium, 2012
DAGS Internal Seminar, 2012

Max-Margin Latent Variable Models
Mysore Park Workshop on Computer Vision, 2011

Learning to Segment with Diverse Data
Ecole Centrale Paris (ECP) Seminar, 2011
Ecole Normale Superieure (ENS) Seminar, 2011
Kungliga Techniska Hogskolan (KTH) Seminar, 2011

Self-Paced Learning for Specific-Class Semantic Segmentation
Microsoft Research India Vision Shindig, 2010

Curriculum Learning for Latent Structural SVM
TTI-Chicago Seminar, 2010

Relaxations and Moves for MAP Estimation in MRFs
NIPS 2009 Workshop on Discrete Optimization

Hierarchical Graph Cuts for Semi-Metric Labeling
DAGS Internal Seminar, 2009

Improved Moves for Truncated Convex Models
Microsoft Research Cambridge Symposium, 2008

An Analysis of Convex Relaxations for MAP Estimation
IPAM Symposium, 2008

Invariant Large Margin Nearest Neighbour Classifier
Rank Symposium, 2007
Best contributed paper award

Layered Pictorial Structures for Object Category Segmentation
Microsoft Research Cambridge Seminar, 2005
University of Leeds Seminar, 2005


Neural Network Verification
VMCAI Winter School, 2019

Efficient Frank-Wolfe for Dense CRFs and Piecewise Linear CNNs
ETH Zurich Pre-Doc Summer School, 2017

Graph Cuts and Linear Programming for Energy Minimization
University of Zurich Institute for Informatics Summer School, 2016

Discrete Optimization in Computer Vision
ICIAP, 2013

Visual Learning with Weak Supervision
CVPR, 2013

Inference and Learning for Image Processing and Computer Vision

Introduction to Machine learning
Biomedical Image Analysis Summer School, 2012

Learning with Inference for Discrete Graphical Models
ICCV, 2011

Markov Models for Computer Vision
ICVGIP, 2010

MAP Inference in Discrete Models
ICCV, 2009

MAP Estimation Algorithms in Computer Vision
ECCV, 2008


Exploiting Duality
VGG Reading Group

Junction Tree Algorithm
Brookes Vision Reading Group

Introduction to Convex Programming
Brookes Vision Reading Group