Spremljaj
M. Pawan Kumar
M. Pawan Kumar
Google DeepMind
Preverjeni e-poštni naslov na deepmind.com
Naslov
Navedeno
Navedeno
Leto
Self-paced learning for latent variable models
M Kumar, B Packer, D Koller
Advances in neural information processing systems 23, 2010
17102010
Objcut: Efficient segmentation using top-down and bottom-up cues
MP Kumar, PHS Torr, A Zisserman
Pattern Analysis and Machine Intelligence, IEEE Transactions on 32 (3), 530-545, 2010
661*2010
A unified view of piecewise linear neural network verification
RR Bunel, I Turkaslan, P Torr, P Kohli, PK Mudigonda
Advances in Neural Information Processing Systems 31, 2018
485*2018
P³ & Beyond: Move Making Algorithms for Solving Higher Order Functions
P Kohli, MP Kumar, PHS Torr
Pattern Analysis and Machine Intelligence, IEEE Transactions on 31 (9), 1645 …, 2009
472*2009
Mathematical discoveries from program search with large language models
B Romera-Paredes, M Barekatain, A Novikov, M Balog, MP Kumar, ...
Nature 625 (7995), 468-475, 2024
2632024
Learning layered motion segmentations of video
M Pawan Kumar, PHS Torr, A Zisserman
International Journal of Computer Vision 76, 301-319, 2008
2542008
Branch and bound for piecewise linear neural network verification
R Bunel, J Lu, I Turkaslan, PHS Torr, P Kohli, MP Kumar
Journal of Machine Learning Research 21 (42), 1-39, 2020
2342020
Efficiently selecting regions for scene understanding
MP Kumar, D Koller
2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010
1862010
Hybrid models for learning to branch
P Gupta, M Gasse, E Khalil, P Mudigonda, A Lodi, Y Bengio
Advances in neural information processing systems 33, 18087-18097, 2020
1452020
Smooth loss functions for deep top-k classification
L Berrada, A Zisserman, MP Kumar
arXiv preprint arXiv:1802.07595, 2018
1362018
Parameter estimation and energy minimization for region-based semantic segmentation
MP Kumar, H Turki, D Preston, D Koller
IEEE transactions on pattern analysis and machine intelligence 37 (7), 1373-1386, 2014
134*2014
An analysis of convex relaxations for MAP estimation of discrete MRFs
MP Kumar, V Kolmogorov, PHS Torr
The Journal of Machine Learning Research 10, 71-106, 2009
122*2009
Efficient discriminative learning of parts-based models
MP Kumar, A Zisserman, PHS Torr
2009 IEEE 12th International Conference on Computer Vision, 552-559, 2009
1202009
Dissimilarity coefficient based weakly supervised object detection
A Arun, CV Jawahar, MP Kumar
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
1072019
Extending pictorial structures for object recognition
MP Kumar, PHS Torr, A Zisserman
British Machine Vision Association, 2004
1062004
A statistical approach to assessing neural network robustness
S Webb, T Rainforth, YW Teh, MP Kumar
arXiv preprint arXiv:1811.07209, 2018
1002018
Improved moves for truncated convex models
MP Kumar, O Veksler, PHS Torr
The Journal of Machine Learning Research 12, 31-67, 2011
79*2011
Weakly supervised instance segmentation by learning annotation consistent instances
A Arun, CV Jawahar, MP Kumar
European Conference on Computer Vision, 254-270, 2020
752020
In defense of the unitary scalarization for deep multi-task learning
V Kurin, A De Palma, I Kostrikov, S Whiteson, PK Mudigonda
Advances in Neural Information Processing Systems 35, 12169-12183, 2022
742022
Neural network branching for neural network verification
J Lu, MP Kumar
arXiv preprint arXiv:1912.01329, 2019
742019
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