1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Geometry-Constrained Kolmogorov-Arnold Networks: Learning Edge Geometry via Banach Duality
K S Sesh Kumar
Kolmogorov-Arnold Networks (KANs) replace fixed activations in deep architectures with learnable univariate edge functions, making the choice of edge parametrisation central. Exist…
cs.LG2021
The Graph Cut Kernel for Ranked Data
Michelangelo Conserva, Marc Peter Deisenroth, K S Sesh Kumar
Many algorithms for ranked data become computationally intractable as the number of objects grows due to the complex geometric structure induced by rankings. An additional challeng…
stat.ML2021★ 1 cited
Sliced Multi-Marginal Optimal Transport
Samuel Cohen, Alexander Terenin, Yannik Pitcan +3
Multi-marginal optimal transport enables one to compare multiple probability measures, which increasingly finds application in multi-task learning problems. One practical limitatio…