activity
20092023
most citedThe Convex Geometry of Linear Inverse Problems

885 citations · 3.5k across the 45 of their papers we have counts for

collaborators

50 papers

stat.ME2023

Model Selection over Partially Ordered Sets

Armeen Taeb, Peter Bühlmann, Venkat Chandrasekaran

In problems such as variable selection and graph estimation, models are characterized by Boolean logical structure such as presence or absence of a variable or an edge. Consequentl…

cs.CL2023★ 8 cited

Question Decomposition Improves the Faithfulness of Model-Generated Reasoning

Ansh Radhakrishnan, Karina Nguyen, Anna Chen +21

As large language models (LLMs) perform more difficult tasks, it becomes harder to verify the correctness and safety of their behavior. One approach to help with this issue is to p…

math.OC2023

Dimension-Free Descriptions of Convex Sets

Eitan Levin, Venkat Chandrasekaran

Convex sets arising in a variety of applications are well-defined for every relevant dimension. Examples include the simplex and the spectraplex that correspond to probability dist…

math.OC2022★ 1 cited

Optimal Regularization for a Data Source

Oscar Leong, Eliza O'Reilly, Yong Sheng Soh +1

In optimization-based approaches to inverse problems and to statistical estimation, it is common to augment criteria that enforce data fidelity with a regularizer that promotes des…

hep-th2022★ 151 cited

Large N algebras and generalized entropy

Venkatesa Chandrasekaran, Geoff Penington, Edward Witten

We construct a Type II von Neumann algebra that describes the large physics of single-trace operators in AdS/CFT in the microcanonical ensemble, where there is no need…

hep-th2022★ 4 cited

A Tale of Two Saddles

Venkatesa Chandrasekaran, Netta Engelhardt, Sebastian Fischetti +1

We find a new on-shell replica wormhole in a computation of the generating functional of JT gravity coupled to matter. We show that this saddle has lower action than the disconnect…

math.OC2022

Kronecker Product Approximation of Operators in Spectral Norm via Alternating SDP

Mareike Dressler, André Uschmajew, Venkat Chandrasekaran

The decomposition or approximation of a linear operator on a matrix space as a sum of Kronecker products plays an important role in matrix equations and low-rank modeling. The appr…

hep-th2022★ 301 cited

An Algebra of Observables for de Sitter Space

Venkatesa Chandrasekaran, Roberto Longo, Geoff Penington +1

We describe an algebra of observables for a static patch in de Sitter space, with operators gravitationally dressed to the worldline of an observer. The algebra is a von Neumann al…

hep-th2022★ 10 cited

Quantum Error Correction in SYK and Bulk Emergence

Venkatesa Chandrasekaran, Adam Levine

We analyze the error correcting properties of the Sachdev-Ye-Kitaev model, with errors that correspond to erasures of subsets of fermions. We study the limit where the number of fe…

gr-qc2021★ 61 cited

A general framework for gravitational charges and holographic renormalization

Venkatesa Chandrasekaran, Eanna E. Flanagan, Ibrahim Shehzad +1

We develop a general framework for constructing charges associated with diffeomorphisms in gravitational theories using covariant phase space techniques. This framework encompasses…

math.OC2021

Spectrahedral Regression

Eliza O'Reilly, Venkat Chandrasekaran

Convex regression is the problem of fitting a convex function to a data set consisting of input-output pairs. We present a new approach to this problem called spectrahedral regress…

hep-th2021★ 69 cited

Brown-York charges at null boundaries

Venkatesa Chandrasekaran, Eanna E. Flanagan, Ibrahim Shehzad +1

The Brown-York stress tensor provides a means for defining quasilocal gravitational charges in subregions bounded by a timelike hypersurface. We consider the generalization of this…

hep-th2021★ 12 cited

Scattering strings off quantum extremal surfaces

Venkatesa Chandrasekaran, Thomas Faulkner, Adam Levine

We consider a Hayden \& Preskill like setup for both maximally chaotic and sub-maximally chaotic quantum field theories. We act on the vacuum with an operator in a Rindler like wed…

stat.ML2020★ 1 cited

Learning Exponential Family Graphical Models with Latent Variables using Regularized Conditional Likelihood

Armeen Taeb, Parikshit Shah, Venkat Chandrasekaran

Fitting a graphical model to a collection of random variables given sample observations is a challenging task if the observed variables are influenced by latent variables, which ca…

math.OC2020

Terracini Convexity

James Saunderson, Venkat Chandrasekaran

We present a generalization of the notion of neighborliness to non-polyhedral convex cones. Although a definition of neighborliness is available in the non-polyhedral case in the l…

hep-th2020★ 82 cited

Anomalies in gravitational charge algebras of null boundaries and black hole entropy

Venkatesa Chandrasekaran, Antony J. Speranza

We revisit the covariant phase space formalism applied to gravitational theories with null boundaries, utilizing the most general boundary conditions consistent with a fixed null n…

hep-th2020★ 31 cited

Gravity Dual of Connes Cocycle Flow

Raphael Bousso, Venkatesa Chandrasekaran, Pratik Rath +1

We define the "kink transform" as a one-sided boost of bulk initial data about the Ryu-Takayanagi surface of a boundary cut. For a flat cut, we conjecture that the resulting Wheele…

hep-th2020★ 104 cited

Islands for Reflected Entropy

Venkatesa Chandrasekaran, Masamichi Miyaji, Pratik Rath

Recent work has demonstrated the need to include contributions from entanglement islands when computing the entanglement entropy in QFT states coupled to regions of semiclassical g…

math.OC2019

A Note on Convex Relaxations for the Inverse Eigenvalue Problem

Utkan Candogan, Yong Sheng Soh, Venkat Chandrasekaran

The affine inverse eigenvalue problem consists of identifying a real symmetric matrix with a prescribed set of eigenvalues in an affine space. Due to its ubiquity in applications,…

gr-qc2019★ 28 cited

Symmetries, charges and conservation laws at causal diamonds in general relativity

Venkatesa Chandrasekaran, Kartik Prabhu

We study the covariant phase space of vacuum general relativity at the null boundary of causal diamonds. The past and future components of such a null boundary each have an infinit…

math.OC2019★ 34 cited

Signomial and Polynomial Optimization via Relative Entropy and Partial Dualization

Riley Murray, Venkat Chandrasekaran, Adam Wierman

We describe a generalization of the Sums-of-AM/GM Exponential (SAGE) relaxation methodology for obtaining bounds on constrained signomial and polynomial optimization problems. Our…

hep-th2019★ 2 cited

Entropy Variations and Light Ray Operators from Replica Defects

Srivatsan Balakrishnan, Venkatesa Chandrasekaran, Thomas Faulkner +2

We study the defect operator product expansion (OPE) of displacement operators in free and interacting conformal field theories using replica methods. We show that as approache…

hep-th2019★ 37 cited

Ignorance is Cheap: From Black Hole Entropy To Energy-Minimizing States In QFT

Raphael Bousso, Venkatesa Chandrasekaran, Arvin Shahbazi-Moghaddam

Behind certain marginally trapped surfaces one can construct a geometry containing an extremal surface of equal, but not larger area. This construction underlies the Engelhardt-Wal…

cs.DS2019

Convex Graph Invariant Relaxations For Graph Edit Distance

Utkan Onur Candogan, Venkat Chandrasekaran

The edit distance between two graphs is a widely used measure of similarity that evaluates the smallest number of vertex and edge deletions/insertions required to transform one gra…