Anish Prasad Sevekari — accepted AI-conference papers

2023

Pitfalls of Gaussians as a noise distribution in NCE

Holden Lee, Chirag Pabbaraju, Anish Prasad Sevekari, Andrej Risteski

ICLR 2023poster

Noise Contrastive Estimation (NCE) is a popular approach for learning probability density functions parameterized up to a constant of proportionality. The main idea is to design a classification problem for distinguishing training data from samples from an (easy-to-sample) noise distribution $q$, in…

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2021

Universal Approximation Using Well-Conditioned Normalizing Flows

Holden Lee, Chirag Pabbaraju, Anish Prasad Sevekari, Andrej Risteski

NeurIPS 2021poster

Normalizing flows are a widely used class of latent-variable generative models with a tractable likelihood. Affine-coupling models [Dinh et al., 2014, 2016] are a particularly common type of normalizing flows, for which the Jacobian of the latent-to-observable-variable transformation is triangular,…

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2018

Robust Subspace Approximation in a Stream

Roie Levin, Anish Prasad Sevekari, David Woodruff

NeurIPS 2018spotlight

We study robust subspace estimation in the streaming and distributed settings. Given a set of n data points {a

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