Learning to Segment Document Images. - K. S. Sesh Kumar; Anoop M. Namboodiri; C. V. Jawahar (PReMI, 2005)

A Semi-automatic Adaptive OCR for Digital Libraries. - Sachin Rawat; K. S. Sesh Kumar; Million Meshesha; Indraneel Deb Sikdar; A. Balasubramanian; C. V. Jawahar (Document Analysis Systems, 2006)

Learning Segmentation of Documents with Complex Scripts. - K. S. Sesh Kumar; Anoop M. Namboodiri; C. V. Jawahar (ICVGIP, 2006)

On Segmentation of Documents in Complex Scripts. - K. S. Sesh Kumar; S. Kumar; C. V. Jawahar (ICDAR, 2007)

Convex Relaxations for Learning Bounded-Treewidth Decomposable Graphs. - K. S. Sesh Kumar; Francis R. Bach (ICML (1), 2013)

Maximizing submodular functions using probabilistic graphical models. - K. S. Sesh Kumar; Francis R. Bach (CoRR, 2013)

Convex Optimization for Parallel Energy Minimization. - K. S. Sesh Kumar; Álvaro Barbero Jiménez; Stefanie Jegelka; Suvrit Sra; Francis R. Bach (CoRR, 2015)

On the Links between Probabilistic Graphical Models and Submodular Optimisation. (Liens entre modèles graphiques probabilistes et optimisation sous-modulaire). - K. S. Sesh Kumar (2016)

Active-set Methods for Submodular Minimization Problems. - K. S. Sesh Kumar; Francis R. Bach (J. Mach. Learn. Res., 2017)

High-Dimensional Bayesian Optimization with Manifold Gaussian Processes. - Riccardo Moriconi; K. S. Sesh Kumar; Marc Peter Deisenroth (CoRR, 2019)

Differentially Private Empirical Risk Minimization with Sparsity-Inducing Norms. - K. S. Sesh Kumar; Marc Peter Deisenroth (CoRR, 2019)

High-dimensional Bayesian optimization using low-dimensional feature spaces. - Riccardo Moriconi; Marc Peter Deisenroth; K. S. Sesh Kumar (Mach. Learn., 2020)

High-dimensional Bayesian optimization with projections using quantile Gaussian processes. - Riccardo Moriconi; K. S. Sesh Kumar; Marc Peter Deisenroth (Optim. Lett., 2020)

Sliced Multi-Marginal Optimal Transport. - Samuel Cohen; K. S. Sesh Kumar; Marc Peter Deisenroth (CoRR, 2021)

Submodular Kernels for Efficient Rankings. - Michelangelo Conserva; Marc Peter Deisenroth; K. S. Sesh Kumar (CoRR, 2021)

Data Learning: Integrating Data Assimilation and Machine Learning. - Caterina Buizza; César Quilodrán Casas; Philip Nadler; Julian Mack; Stefano Marrone 002; Zainab Titus; Clémence Le Cornec; Evelyn Heylen; Tolga Hasan Dur; Luis G. Baca Ruíz; Claire E. Heaney; Julio Amador Díaz López; et al. (J. Comput. Sci., 2022)

The Graph Cut Kernel for Ranked Data. - Michelangelo Conserva; Marc Peter Deisenroth; K. S. Sesh Kumar (Trans. Mach. Learn. Res., 2022)