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K S Sesh Kumar
K S Sesh Kumar
Research Fellow @ Imperial College, London
Verified email at imperial.ac.uk - Homepage
Title
Cited by
Cited by
Year
High-dimensional Bayesian optimization using low-dimensional feature spaces
R Moriconi, MP Deisenroth, KS Sesh Kumar
Machine Learning 109, 1925-1943, 2020
692020
Learning segmentation of documents with complex scripts
KS Sesh Kumar, AM Namboodiri, CV Jawahar
Computer Vision, Graphics and Image Processing: 5th Indian Conference …, 2006
552006
On segmentation of documents in complex scripts
KS Kumar, S Kumar, C Jawahar
Ninth International Conference on Document Analysis and Recognition (ICDAR …, 2007
292007
On segmentation of documents in complex scripts
KS Sesh Kumar, S Kumar, CV Jawahar
Document Analysis and Recognition, 2007. ICDAR 2007. Ninth International …, 2007
29*2007
High-dimensional Bayesian optimization with projections using quantile Gaussian processes
R Moriconi, KSS Kumar, MP Deisenroth
Optimization Letters 14, 51-64, 2020
242020
Convex relaxations for learning bounded-treewidth decomposable graphs
KSS Kumar, F Bach
International Conference on Machine Learning, 525-533, 2013
202013
Convex Relaxations for Learning Bounded Treewidth Decomposable Graphs
KS Sesh Kumar, F Bach
arXiv preprint arXiv:1212.2573, 2012
20*2012
A semi-automatic adaptive OCR for digital libraries
S Rawat, K Kumar, M Meshesha, I Sikdar, A Balasubramanian, ...
Document Analysis Systems VII, 13-24, 2006
152006
Data learning: integrating data assimilation and machine learning
C Buizza, CQ Casas, P Nadler, J Mack, S Marrone, Z Titus, C Le Cornec, ...
Journal of Computational Science 58, 101525, 2022
132022
Real-time particle filtering with heuristics for 3D motion capture by monocular vision
DAG Jáuregui, P Horain, MK Rajagopal, SSK Karri
2010 IEEE International Workshop on Multimedia Signal Processing, 139-144, 2010
122010
Convex optimization for parallel energy minimization
KS Kumar, A Barbero, S Jegelka, S Sra, F Bach
arXiv preprint arXiv:1503.01563, 2015
102015
High-Dimensional Bayesian Optimization with Manifold Gaussian Processes
R Moriconi, KSS Kumar, MP Deisenroth
https://arxiv.org/pdf/1902.10675, 2019
82019
Learning to segment document images
K Kumar, A Namboodiri, C Jawahar
Pattern Recognition and Machine Intelligence, 471-476, 2005
82005
Active-set methods for submodular minimization problems
KS Kumar, F Bach
The Journal of Machine Learning Research 18 (1), 4809-4839, 2017
62017
Differentially Private Empirical Risk Minimization with Sparsity-Inducing Norms
KSS Kumar, MP Deisenroth
https://arxiv.org/pdf/1905.04873, 2019
52019
Sliced multi-marginal optimal transport
S Cohen, A Terenin, Y Pitcan, B Amos, MP Deisenroth, KS Kumar
arXiv preprint arXiv:2102.07115, 2021
42021
Active-set methods for submodular optimization
K Kumar, F Bach
arXiv preprint arXiv:1506.02852, 2015
32015
Maximizing submodular functions using probabilistic graphical models
KS Kumar, F Bach
arXiv preprint arXiv:1309.2593, 2013
32013
In vitro and in vivo anti-snake venom activity of Coccinia indica L. leaf
RA Vijayabharathi, S Kumar, KS Kumar
Hamdard Med 48, 132-135, 2005
32005
Fast decomposable submodular function minimization using constrained total variation
SSK Karri, F Bach, T Pock
Advances in Neural Information Processing Systems 32, 2019
12019
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Articles 1–20