72 citations · 189 across the 132 of their papers we have counts for
31 papers · 1 filter
Closed-form empirical Bernstein confidence sequences for scalars and matrices
Ben Chugg, Aaditya Ramdas
We derive a new closed-form variance-adaptive confidence sequence (CS) for estimating the average conditional mean of a sequence of bounded random variables. Empirically, it yields…
Rao-Blackwellized e-variables
Dante de Roos, Ben Chugg, Peter Grünwald +1
We show that for any concave utility, the expected utility of an e-variable can only increase after conditioning on a sufficient statistic. The simplest form of the result has an e…
Optimal Transportation and Alignment Between Gaussian Measures
Sanjit Dandapanthula, Aleksandr Podkopaev, Shiva Prasad Kasiviswanathan +2
Optimal transport (OT) and Gromov-Wasserstein (GW) alignment provide interpretable geometric frameworks for comparing, transforming, and aggregating heterogeneous datasets -- tasks…
Eventually LIL Regret: Almost Sure Regret for a sub-Gaussian Mixture on Unbounded Data
Shubhada Agrawal, Aaditya Ramdas
We prove that a classic sub-Gaussian mixture proposed by Robbins in a stochastic setting actually satisfies a path-wise (deterministic) regret bound. For every path in a natural ``…
Gradient descent for deep equilibrium single-index models
Sanjit Dandapanthula, Aaditya Ramdas
Deep equilibrium models (DEQs) have recently emerged as a powerful paradigm for training infinitely deep weight-tied neural networks that achieve state of the art performance acros…
Vector-valued self-normalized concentration inequalities beyond sub-Gaussianity
Diego Martinez-Taboada, Tomas Gonzalez, Aaditya Ramdas
The study of self-normalized processes plays a crucial role in a wide range of applications, from sequential decision-making to econometrics. While the behavior of self-normalized…