8 papers
Response Variability and Stability in Human Reasoning
Clemens Bombach, Rajmadan Lakshmanan, Marco Ragni
Understanding how humans reason -- and how reasoning responses vary across tasks and individuals -- remains a core challenge for modeling and explanation in cognitive science. We i…
Uniform convergence for Gaussian kernel ridge regression
Paul Dommel, Rajmadan Lakshmanan
This paper establishes the first polynomial convergence rates for Gaussian kernel ridge regression (KRR) with a fixed hyperparameter in both the uniform and the -norm. The u…
StochasticDominance.jl: A Julia Package for Higher Order Stochastic Dominance
Rajmadan Lakshmanan, Alois Pichler
Stochastic dominance is a fundamental concept in decision-making under uncertainty and quantitative finance, yet its practical application is hindered by computational intractabili…
Higher-Order Stochastic Dominance Constraints in Optimization
Rajmadan Lakshmanan, Alois Pichler, Miloš Kopa
This contribution examines optimization problems that involve stochastic dominance constraints. These problems have uncountably many constraints. We develop methods to solve the op…
Soft Quantization using Entropic Regularization
Rajmadan Lakshmanan, Alois Pichler
The quantization problem aims to find the best possible approximation of probability measures on using finite, discrete measures. The Wasserstein distance is a typ…
Unbalanced Optimal Transport and Maximum Mean Discrepancies: Interconnections and Rapid Evaluation
Rajmadan Lakshmanan, Alois Pichler
This contribution presents substantial computational advancements to compare measures even with varying masses. Specifically, we utilize the nonequispaced fast Fourier transform to…
Expectiles In Risk Averse Stochastic Programming and Dynamic Optimization
Rajmadan Lakshmanan, Alois Pichler
This paper features expectiles in dynamic and stochastic optimization. Expectiles are a family of risk functionals characterized as minimizers of optimization problems. For this re…
Nonequispaced Fast Fourier Transform Boost for the Sinkhorn Algorithm
Rajmadan Lakshmanan, Alois Pichler, Daniel Potts
This contribution features an accelerated computation of the Sinkhorn's algorithm, which approximates the Wasserstein transportation distance, by employing nonequispaced fast Fouri…