Srinivasan Arunachalam | DeepAI

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Ronald de Wolf
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Troy Lee
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Michal Koucký
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∙ 06/05/2023

On the Role of Entanglement and Statistics in Learning

In this work we make progress in understanding the relationship between ...

0 Srinivasan Arunachalam, et al. ∙

∙ 06/02/2023

Trade-offs between Entanglement and Communication

We study the advantages of quantum communication models over classical c...

0 Srinivasan Arunachalam, et al. ∙

∙ 05/31/2023

A survey on the complexity of learning quantum states

We survey various recent results that rigorously study the complexity of...

0 Anurag Anshu, et al. ∙

∙ 05/10/2023

Generalized Stratified Sampling for Efficient Reliability Assessment of Structures Against Natural Hazards

Performance-based engineering for natural hazards facilitates the design...

0 Srinivasan Arunachalam, et al. ∙

∙ 05/10/2023

Uncertainty Quantification of a Wind Tunnel-Informed Stochastic Wind Load Model for Wind Engineering Applications

The simulation of stochastic wind loads is necessary for many applicatio...

0 Thays Guerra Araujo Duarte, et al. ∙

∙ 02/21/2023

A note on the partition bound for one-way classical communication complexity

We present a linear program for the one-way version of the partition bou...

0 Srinivasan Arunachalam, et al. ∙

∙ 08/16/2022

Optimal algorithms for learning quantum phase states

We analyze the complexity of learning n-qubit quantum phase states. A de...

0 Srinivasan Arunachalam, et al. ∙

∙ 07/06/2022

Reliability-Based Collapse Assessment of Wind-Excited Steel Structures within Performance-Based Wind Engineering

As inelastic design for wind is embraced by the engineering community, t...

0 Srinivasan Arunachalam, et al. ∙

∙ 02/16/2022

The Parameterized Complexity of Quantum Verification

We initiate the study of parameterized complexity of problems in terms ...

0 Srinivasan Arunachalam, et al. ∙

∙ 09/06/2021

Matrix hypercontractivity, streaming algorithms and LDCs: the large alphabet case

In this work, we prove a hypercontractive inequality for matrix-valued f...

0 Srinivasan Arunachalam, et al. ∙

∙ 02/14/2021

Private learning implies quantum stability

Learning an unknown n-qubit quantum state ρ is a fundamental challenge i...

0 Srinivasan Arunachalam, et al. ∙

∙ 01/20/2021

Positive spectrahedra: Invariance principles and Pseudorandom generators

In a recent work, O'Donnell, Servedio and Tan (STOC 2019) gave explicit ...

0 Srinivasan Arunachalam, et al. ∙

∙ 12/03/2020

Quantum learning algorithms imply circuit lower bounds

We establish the first general connection between the design of quantum ...

3 Srinivasan Arunachalam, et al. ∙

∙ 10/05/2020

A rigorous and robust quantum speed-up in supervised machine learning

Over the past few years several quantum machine learning algorithms were...

0 Yunchao Liu, et al. ∙

∙ 05/08/2020

Communication memento: Memoryless communication complexity

We study the communication complexity of computing functions F:{0,1}^n×{...

0 Srinivasan Arunachalam, et al. ∙

∙ 04/15/2020

Sample-efficient learning of quantum many-body systems

We study the problem of learning the Hamiltonian of a quantum many-body ...

0 Anurag Anshu, et al. ∙

∙ 02/19/2020

Quantum statistical query learning

We propose a learning model called the quantum statistical learning QSQ ...

0 Srinivasan Arunachalam, et al. ∙

∙ 02/12/2020

Quantum Boosting

Suppose we have a weak learning algorithm A for a Boolean-valued problem...

0 Srinivasan Arunachalam, et al. ∙

∙ 05/08/2019

The asymptotic induced matching number of hypergraphs: balanced binary strings

We compute the asymptotic induced matching number of the k-partite k-uni...

0 Srinivasan Arunachalam, et al. ∙

∙ 03/07/2019

Quantum hardness of learning shallow classical circuits

In this paper we study the quantum learnability of constant-depth classi...

0 Srinivasan Arunachalam, et al. ∙

∙ 09/30/2018

Two new results about quantum exact learning

We present two new results about exact learning by quantum computers. Fi...

0 Srinivasan Arunachalam, et al. ∙

∙ 09/26/2018

Improved bounds on Fourier entropy and Min-entropy

Given a Boolean function f:{-1,1}^n→{-1,1}, the Fourier distribution ass...

0 Srinivasan Arunachalam, et al. ∙

∙ 11/20/2017

Quantum Query Algorithms are Completely Bounded Forms

We prove a characterization of t-query quantum algorithms in terms of th...

0 Srinivasan Arunachalam, et al. ∙

∙ 11/01/2017

Optimizing quantum optimization algorithms via faster quantum gradient computation

We consider a generic framework of optimization algorithms based on grad...

0 András Gilyén, et al. ∙

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