Srinivasan Arunachalam

81 papers A* 11A 7Misc 1Journal 57Unranked 5
YearRankTypeTitle / Venue / Authors
2026 A conf
Classical and Quantum Polynomial Freiman-Ruzsa Algorithms.
ITCS
Srinivasan Arunachalam, Davi Castro-Silva, Arkopal Dutt, Tom Gur
2025 J jnl
Algorithmic Polynomial Freiman-Ruzsa Theorems.
Electron. Colloquium Comput. Complex.
Srinivasan Arunachalam, Davi Castro-Silva, Arkopal Dutt, Tom Gur
2025 J jnl
Efficiently learning depth-3 circuits via quantum agnostic boosting.
CoRR
Srinivasan Arunachalam, Arkopal Dutt, Alexandru Gheorghiu, Michael de Oliveira
2025 A conf
Generalized Inner Product Estimation with Limited Quantum Communication.
STACS
Srinivasan Arunachalam, Louis Schatzki
2025 J jnl
Learning stabilizer structure of quantum states.
CoRR
Srinivasan Arunachalam, Arkopal Dutt
2025 A* conf
Polynomial-Time Tolerant Testing Stabilizer States.
STOC
Srinivasan Arunachalam, Arkopal Dutt
2025 A* conf
Testing and Learning Structured Quantum Hamiltonians.
STOC
Srinivasan Arunachalam, Arkopal Dutt, Francisco Escudero Gutiérrez
2024 J jnl
A note on polynomial-time tolerant testing stabilizer states.
CoRR
Srinivasan Arunachalam, Sergey Bravyi, Arkopal Dutt
2024 J jnl
Distributed inner product estimation with limited quantum communication.
CoRR
Srinivasan Arunachalam, Louis Schatzki
2024 A* conf
Learning Low-Degree Quantum Objects.
ICALP
Srinivasan Arunachalam, Arkopal Dutt, Francisco Escudero Gutiérrez, Carlos Palazuelos
2024 J jnl
Learning low-degree quantum objects.
CoRR
Srinivasan Arunachalam, Arkopal Dutt, Francisco Escudero Gutiérrez, Carlos Palazuelos
2024 J jnl
Matrix hypercontractivity, streaming algorithms and LDCs: the large alphabet case.
ACM Trans. Comput. Theory
Srinivasan Arunachalam, João F. Doriguello
2024 J jnl
Testing and learning structured quantum Hamiltonians.
CoRR
Srinivasan Arunachalam, Arkopal Dutt, Francisco Escudero Gutiérrez
2024 J jnl
Tolerant testing stabilizer states.
CoRR
Srinivasan Arunachalam, Arkopal Dutt
2023 J jnl
A note on the partition bound for one-way classical communication complexity.
CoRR
Srinivasan Arunachalam, João F. Doriguello, Rahul Jain
2023 J jnl
A survey on the complexity of learning quantum states.
CoRR
Anurag Anshu, Srinivasan Arunachalam
2023 J jnl
Generalized Stratified Sampling for Efficient Reliability Assessment of Structures Against Natural Hazards.
CoRR
Srinivasan Arunachalam, Seymour M. J. Spence
2023 A* conf
On the Role of Entanglement and Statistics in Learning.
NeurIPS
Srinivasan Arunachalam, Vojtech Havlícek, Louis Schatzki
2023 J jnl
On the Role of Entanglement and Statistics in Learning.
CoRR
Srinivasan Arunachalam, Vojtech Havlícek, Louis Schatzki
2023 J jnl
One Clean Qubit Suffices for Quantum Communication Advantage.
CoRR
Srinivasan Arunachalam, Uma Girish, Noam Lifshitz
2023 J jnl
One Clean Qubit Suffices for Quantum Communication Advantage.
Electron. Colloquium Comput. Complex.
Srinivasan Arunachalam, Uma Girish, Noam Lifshitz
2023 — conf
Optimal Algorithms for Learning Quantum Phase States.
TQC
Srinivasan Arunachalam, Sergey Bravyi, Arkopal Dutt, Theodore J. Yoder
2023 A conf
Trade-Offs Between Entanglement and Communication.
CCC
Srinivasan Arunachalam, Uma Girish
2023 J jnl
Trade-offs between Entanglement and Communication.
CoRR
Srinivasan Arunachalam, Uma Girish
2023 J jnl
Uncertainty Quantification of a Wind Tunnel-Informed Stochastic Wind Load Model for Wind Engineering Applications.
CoRR
Thays Guerra Araujo Duarte, Srinivasan Arunachalam, Arthriya Subgranon, Seymour M. J. Spence
2022 J jnl
Optimal algorithms for learning quantum phase states.
CoRR
Srinivasan Arunachalam, Sergey Bravyi, Arkopal Dutt, Theodore J. Yoder
2022 A* conf
Positive spectrahedra: invariance principles and pseudorandom generators.
STOC
Srinivasan Arunachalam, Penghui Yao
2022 J jnl
Reliability-Based Collapse Assessment of Wind-Excited Steel Structures within Performance-Based Wind Engineering.
CoRR
Srinivasan Arunachalam, Seymour M. J. Spence
2022 J jnl
Simpler (classical) and faster (quantum) algorithms for Gibbs partition functions.
Quantum
Srinivasan Arunachalam, Vojtech Havlícek, Giacomo Nannicini, Kristan Temme, Pawel Wocjan
2022 J jnl
The Parameterized Complexity of Quantum Verification.
CoRR
Srinivasan Arunachalam, Sergey Bravyi, Chinmay Nirkhe, Bryan O'Gorman
2022 — conf
The Parametrized Complexity of Quantum Verification.
TQC
Srinivasan Arunachalam, Sergey Bravyi, Chinmay Nirkhe, Bryan O'Gorman
2021 A conf
Communication Memento: Memoryless Communication Complexity.
ITCS
Srinivasan Arunachalam, Supartha Podder
2021 J jnl
Improved Bounds on Fourier Entropy and Min-entropy.
ACM Trans. Comput. Theory
Srinivasan Arunachalam, Sourav Chakraborty, Michal Koucký, Nitin Saurabh, Ronald de Wolf
2021 J jnl
Matrix hypercontractivity, streaming algorithms and LDCs: the large alphabet case.
CoRR
Srinivasan Arunachalam, João F. Doriguello
2021 J jnl
Matrix hypercontractivity, streaming algorithms and LDCs: the large alphabet case.
Electron. Colloquium Comput. Complex.
Srinivasan Arunachalam, João F. Doriguello
2021 J jnl
On the Gaussian surface area of spectrahedra.
Electron. Colloquium Comput. Complex.
Srinivasan Arunachalam, Oded Regev, Penghui Yao
2021 J jnl
Positive spectrahedrons: Geometric properties, Invariance principles and Pseudorandom generators.
CoRR
Srinivasan Arunachalam, Penghui Yao
2021 J jnl
Positive spectrahedrons: Geometric properties, Invariance principles and Pseudorandom generators.
Electron. Colloquium Comput. Complex.
Srinivasan Arunachalam, Penghui Yao
2021 A* conf
Private learning implies quantum stability.
NeurIPS
Yihui Quek, Srinivasan Arunachalam, John A. Smolin
2021 J jnl
Private learning implies quantum stability.
CoRR
Srinivasan Arunachalam, Yihui Quek, John A. Smolin
2021 J jnl
Quantum Hardness of Learning Shallow Classical Circuits.
SIAM J. Comput.
Srinivasan Arunachalam, Alex Bredariol Grilo, Aarthi Sundaram
2021 A* conf
Quantum learning algorithms imply circuit lower bounds.
FOCS
Srinivasan Arunachalam, Alex B. Grilo, Tom Gur, Igor C. Oliveira, Aarthi Sundaram
2021 Misc conf
Simpler (Classical) and Faster (Quantum) Algorithms for Gibbs Partition Functions.
QCE
Srinivasan Arunachalam, Vojtech Havlícek, Giacomo Nannicini, Kristan Temme, Pawel Wocjan
2021 J jnl
Two new results about quantum exact learning.
Quantum
Srinivasan Arunachalam, Sourav Chakraborty, Troy Lee, Manaswi Paraashar, Ronald de Wolf
2020 J jnl
A rigorous and robust quantum speed-up in supervised machine learning.
CoRR
Yunchao Liu, Srinivasan Arunachalam, Kristan Temme
2020 J jnl
Communication memento: Memoryless communication complexity.
CoRR
Srinivasan Arunachalam, Supartha Podder
2020 A conf
Improved Bounds on Fourier Entropy and Min-Entropy.
STACS
Srinivasan Arunachalam, Sourav Chakraborty, Michal Koucký, Nitin Saurabh, Ronald de Wolf
2020 A* conf
Quantum Boosting.
ICML
Srinivasan Arunachalam, Reevu Maity
2020 J jnl
Quantum Boosting.
CoRR
Srinivasan Arunachalam, Reevu Maity
2020 — conf
Quantum Coupon Collector.
TQC
Srinivasan Arunachalam, Aleksandrs Belovs, Andrew M. Childs, Robin Kothari, Ansis Rosmanis, Ronald de Wolf
2020 J jnl
Quantum Coupon Collector.
CoRR
Srinivasan Arunachalam, Aleksandrs Belovs, Andrew M. Childs, Robin Kothari, Ansis Rosmanis, Ronald de Wolf
2020 J jnl
Quantum learning algorithms imply circuit lower bounds.
CoRR
Srinivasan Arunachalam, Alex B. Grilo, Tom Gur, Igor C. Oliveira, Aarthi Sundaram
2020 J jnl
Quantum learning algorithms imply circuit lower bounds.
Electron. Colloquium Comput. Complex.
Srinivasan Arunachalam, Alex Bredariol Grilo, Tom Gur, Igor C. Oliveira, Aarthi Sundaram
2020 J jnl
Quantum statistical query learning.
CoRR
Srinivasan Arunachalam, Alex B. Grilo, Henry Yuen
2020 A* conf
Sample-efficient learning of quantum many-body systems.
FOCS
Anurag Anshu, Srinivasan Arunachalam, Tomotaka Kuwahara, Mehdi Soleimanifar
2020 J jnl
Sample-efficient learning of quantum many-body systems.
CoRR
Anurag Anshu, Srinivasan Arunachalam, Tomotaka Kuwahara, Mehdi Soleimanifar
2020 J jnl
The Asymptotic Induced Matching Number of Hypergraphs: Balanced Binary Strings.
Electron. J. Comb.
Srinivasan Arunachalam, Péter Vrana, Jeroen Zuiddam
2019 A* conf
Optimizing quantum optimization algorithms via faster quantum gradient computation.
SODA
András Gilyén, Srinivasan Arunachalam, Nathan Wiebe
2019 J jnl
Quantum Query Algorithms Are Completely Bounded Forms.
SIAM J. Comput.
Srinivasan Arunachalam, Jop Briët, Carlos Palazuelos
2019 J jnl
Quantum hardness of learning shallow classical circuits.
CoRR
Srinivasan Arunachalam, Alex Bredariol Grilo, Aarthi Sundaram
2019 J jnl
Quantum hardness of learning shallow classical circuits.
Electron. Colloquium Comput. Complex.
Srinivasan Arunachalam, Alex Bredariol Grilo, Aarthi Sundaram
2019 J jnl
The asymptotic induced matching number of hypergraphs: balanced binary strings.
CoRR
Srinivasan Arunachalam, Péter Vrana, Jeroen Zuiddam
2019 A* conf
Two New Results About Quantum Exact Learning.
ICALP
Srinivasan Arunachalam, Sourav Chakraborty, Troy Lee, Manaswi Paraashar, Ronald de Wolf
2018 J jnl
Improved bounds on Fourier entropy and Min-entropy.
CoRR
Srinivasan Arunachalam, Sourav Chakraborty, Michal Koucký, Nitin Saurabh, Ronald de Wolf
2018 J jnl
Improved bounds on Fourier entropy and Min-entropy.
Electron. Colloquium Comput. Complex.
Srinivasan Arunachalam, Sourav Chakraborty, Michal Koucký, Nitin Saurabh, Ronald de Wolf
2018 J jnl
Optimal Quantum Sample Complexity of Learning Algorithms.
J. Mach. Learn. Res.
Srinivasan Arunachalam, Ronald de Wolf
2018 A conf
Quantum Query Algorithms are Completely Bounded Forms.
ITCS
Srinivasan Arunachalam, Jop Briët, Carlos Palazuelos
2018 J jnl
Two new results about quantum exact learning.
CoRR
Srinivasan Arunachalam, Sourav Chakraborty, Troy Lee, Ronald de Wolf
2017 J jnl
A Survey of Quantum Learning Theory.
CoRR
Srinivasan Arunachalam, Ronald de Wolf
2017 J jnl
Guest Column: A Survey of Quantum Learning Theory.
SIGACT News
Srinivasan Arunachalam, Ronald de Wolf
2017 A conf
Optimal Quantum Sample Complexity of Learning Algorithms.
CCC
Srinivasan Arunachalam, Ronald de Wolf
2017 J jnl
Optimizing quantum optimization algorithms via faster quantum gradient computation.
CoRR
András Gilyén, Srinivasan Arunachalam, Nathan Wiebe
2017 J jnl
Optimizing the number of gates in quantum search.
Quantum Inf. Comput.
Srinivasan Arunachalam, Ronald de Wolf
2017 — conf
Quantum Hedging in Two-Round Prover-Verifier Interactions.
TQC
Srinivasan Arunachalam, Abel Molina, Vincent Russo
2017 J jnl
Quantum Query Algorithms are Completely Bounded Forms.
CoRR
Srinivasan Arunachalam, Jop Briët, Carlos Palazuelos
2016 J jnl
Hard satisfiable 3-SAT instances via autocorrelation.
J. Satisf. Boolean Model. Comput.
Srinivasan Arunachalam, Ilias S. Kotsireas
2016 J jnl
Optimal Quantum Sample Complexity of Learning Algorithms.
CoRR
Srinivasan Arunachalam, Ronald de Wolf
2015 J jnl
Is absolute separability determined by the partial transpose?
Quantum Inf. Comput.
Srinivasan Arunachalam, Nathaniel Johnston, Vincent Russo
2015 — conf
On the Robustness of Bucket Brigade Quantum RAM.
TQC
Srinivasan Arunachalam, Vlad Gheorghiu, Tomas Jochym-O'Connor, Michele Mosca, Priyaa Varshinee Srinivasan
2015 J jnl
Optimizing the Number of Gates in Quantum Search.
CoRR
Srinivasan Arunachalam, Ronald de Wolf
2013 J jnl
Quantum hedging in two-round prover-verifier interactions.
CoRR
Srinivasan Arunachalam, Abel Molina, Vincent Russo