270 citations · 835 across the 84 of their papers we have counts for
6 papers · 1 filter
Selective classification using a robust meta-learning approach
Nishant Jain, Karthikeyan Shanmugam, Pradeep Shenoy
Predictive uncertainty-a model's self awareness regarding its accuracy on an input-is key for both building robust models via training interventions and for test-time applications…
Causal Bandits for Linear Structural Equation Models
Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri +1
This paper studies the problem of designing an optimal sequence of interventions in a causal graphical model to minimize cumulative regret with respect to the best intervention in…
Attribute Graphs Underlying Molecular Generative Models: Path to Learning with Limited Data
Samuel C. Hoffman, Payel Das, Karthikeyan Shanmugam +2
Training generative models that capture rich semantics of the data and interpreting the latent representations encoded by such models are very important problems in un-/self-superv…
PAC Generalization via Invariant Representations
Advait Parulekar, Karthikeyan Shanmugam, Sanjay Shakkottai
One method for obtaining generalizable solutions to machine learning tasks when presented with diverse training environments is to find \textit{invariant representations} of the da…
Auto-Transfer: Learning to Route Transferrable Representations
Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss +3
Knowledge transfer between heterogeneous source and target networks and tasks has received a lot of attention in recent times as large amounts of quality labeled data can be diffic…
Fourier Representations for Black-Box Optimization over Categorical Variables
Hamid Dadkhahi, Jesus Rios, Karthikeyan Shanmugam +1
Optimization of real-world black-box functions defined over purely categorical variables is an active area of research. In particular, optimization and design of biological sequenc…