
Learning to Initialize Gradient Descent Using Gradient Descent
Nonconvex optimization problems are challenging to solve; the success a...
read it

Empirical or Invariant Risk Minimization? A Sample Complexity Perspective
Recently, invariant risk minimization (IRM) was proposed as a promising ...
read it

Linear Regression Games: Convergence Guarantees to Approximate OutofDistribution Solutions
Recently, invariant risk minimization (IRM) (Arjovsky et al.) was propos...
read it

Invariant Risk Minimization Games
The standard risk minimization paradigm of machine learning is brittle w...
read it

Estimating KullbackLeibler Divergence Using Kernel Machines
Recently, a method called the Mutual Information Neural Estimator (MINE)...
read it

RiskStratify: Confident Stratification Of Patients Based On Risk
A clinician desires to use a riskstratification method that achieves co...
read it

Generalized Concordance for Competing Risks
Existing metrics in competing risks survival analysis such as concordanc...
read it

Piecewise Approximations of Black Box Models for Model Interpretation
Machine Learning models have proved extremely successful for a wide vari...
read it
Kartik Ahuja
is this you? claim profile