K. S. Sesh Kumar

The Graph Cut Kernel for Ranked Data (2022)
High-Dimensional Bayesian Optimization with Manifold Gaussian Processes (2020)
High-Dimensional Bayesian Optimization Using Low-Dimensional Feature Spaces (2019)
Differentially Private Empirical Risk Minimization with Sparsity-Inducing Norms (2019)
High-Dimensional Bayesian Optimization with Projections using Quantile Gaussian Processes (2019)
Fast Decomposable Submodular Function Minimization using Constrained Total Variation (2019)

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