activity
20152026
most citedSafe Exploration in Continuous Action Spaces

275 citations · 347 across the 35 of their papers we have counts for

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Showing 2020Show all

5 papers · 1 filter

cs.LG202015 cited

Autoencoding Variational Autoencoder

A. Taylan Cemgil, Sumedh Ghaisas, Krishnamurthy Dvijotham +2

Does a Variational AutoEncoder (VAE) consistently encode typical samples generated from its decoder? This paper shows that the perhaps surprising answer to this question is `No'; a…

cs.LG20202 cited

Towards transformation-resilient provenance detection of digital media

Jamie Hayes, Krishnamurthy, Dvijotham +4

Advancements in deep generative models have made it possible to synthesize images, videos and audio signals that are difficult to distinguish from natural signals, creating opportu…

cs.LG202014 cited

Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming

Sumanth Dathathri, Krishnamurthy Dvijotham, Alexey Kurakin +8

Convex relaxations have emerged as a promising approach for verifying desirable properties of neural networks like robustness to adversarial perturbations. Widely used Linear Progr…

math.OC20204 cited

An efficient nonconvex reformulation of stagewise convex optimization problems

Rudy Bunel, Oliver Hinder, Srinadh Bhojanapalli +2

Convex optimization problems with staged structure appear in several contexts, including optimal control, verification of deep neural networks, and isotonic regression. Off-the-she…

cs.LG2020

Lagrangian Decomposition for Neural Network Verification

Rudy Bunel, Alessandro De Palma, Alban Desmaison +4

A fundamental component of neural network verification is the computation of bounds on the values their outputs can take. Previous methods have either used off-the-shelf solvers, d…