Srinivasan Arunachalam

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 69

Top Topics

Number Of Irrelevant Features

Parameterized Complexity

Learning Theory

Top Venues

Electron. Colloquium Comput. Complex.

Publications

Srinivasan Arunachalam, Arkopal Dutt, Francisco Escudero Gutiérrez, Carlos Palazuelos
Learning low-degree quantum objects. CoRR (2024)
Srinivasan Arunachalam, Arkopal Dutt, Francisco Escudero Gutiérrez, Carlos Palazuelos
Learning Low-Degree Quantum Objects. ICALP (2024)
Anurag Anshu, Srinivasan Arunachalam
A survey on the complexity of learning quantum states. CoRR (2023)
Srinivasan Arunachalam, Seymour M. J. Spence
Generalized Stratified Sampling for Efficient Reliability Assessment of Structures Against Natural Hazards. CoRR (2023)
Srinivasan Arunachalam, Sergey Bravyi, Arkopal Dutt, Theodore J. Yoder
Optimal Algorithms for Learning Quantum Phase States. TQC (2023)
Srinivasan Arunachalam, Vojtech Havlícek, Louis Schatzki
On the Role of Entanglement and Statistics in Learning. NeurIPS (2023)
Srinivasan Arunachalam, Vojtech Havlícek, Louis Schatzki
On the Role of Entanglement and Statistics in Learning. CoRR (2023)
Srinivasan Arunachalam, Uma Girish
Trade-offs between Entanglement and Communication. CoRR (2023)
Srinivasan Arunachalam, Uma Girish
Trade-Offs Between Entanglement and Communication. CCC (2023)
Thays Guerra Araujo Duarte, Srinivasan Arunachalam, Arthriya Subgranon, Seymour M. J. Spence
Uncertainty Quantification of a Wind Tunnel-Informed Stochastic Wind Load Model for Wind Engineering Applications. CoRR (2023)
Srinivasan Arunachalam, Uma Girish, Noam Lifshitz
One Clean Qubit Suffices for Quantum Communication Advantage. CoRR (2023)
Srinivasan Arunachalam, João F. Doriguello, Rahul Jain
A note on the partition bound for one-way classical communication complexity. CoRR (2023)
Srinivasan Arunachalam, Uma Girish, Noam Lifshitz
One Clean Qubit Suffices for Quantum Communication Advantage. Electron. Colloquium Comput. Complex. (2023)
Srinivasan Arunachalam, Penghui Yao
Positive spectrahedra: invariance principles and pseudorandom generators. STOC (2022)
Srinivasan Arunachalam, Sergey Bravyi, Chinmay Nirkhe, Bryan O'Gorman
The Parameterized Complexity of Quantum Verification. CoRR (2022)
Srinivasan Arunachalam, Seymour M. J. Spence
Reliability-Based Collapse Assessment of Wind-Excited Steel Structures within Performance-Based Wind Engineering. CoRR (2022)
Srinivasan Arunachalam, Alex B. Grilo, Tom Gur, Igor Carboni Oliveira, Aarthi Sundaram
Quantum learning algorithms imply circuit lower bounds. FOCS (2022)
Srinivasan Arunachalam, Sergey Bravyi, Arkopal Dutt, Theodore J. Yoder
Optimal algorithms for learning quantum phase states. CoRR (2022)
Srinivasan Arunachalam, Vojtech Havlícek, Giacomo Nannicini, Kristan Temme, Pawel Wocjan
Simpler (classical) and faster (quantum) algorithms for Gibbs partition functions. Quantum 6 (2022)
Srinivasan Arunachalam, Sergey Bravyi, Chinmay Nirkhe, Bryan O'Gorman
The Parametrized Complexity of Quantum Verification. TQC (2022)
Srinivasan Arunachalam, João F. Doriguello
Matrix hypercontractivity, streaming algorithms and LDCs: the large alphabet case. CoRR (2021)
Srinivasan Arunachalam, Sourav Chakraborty, Troy Lee, Manaswi Paraashar, Ronald de Wolf
Two new results about quantum exact learning. Quantum 5 (2021)
Srinivasan Arunachalam, Vojtech Havlícek, Giacomo Nannicini, Kristan Temme, Pawel Wocjan
Simpler (Classical) and Faster (Quantum) Algorithms for Gibbs Partition Functions. QCE (2021)
Srinivasan Arunachalam, Sourav Chakraborty, Michal Koucký, Nitin Saurabh, Ronald de Wolf
Improved Bounds on Fourier Entropy and Min-entropy. ACM Trans. Comput. Theory 13 (4) (2021)
Srinivasan Arunachalam, Yihui Quek, John A. Smolin
Private learning implies quantum stability. CoRR (2021)
Yihui Quek, Srinivasan Arunachalam, John A. Smolin
Private learning implies quantum stability. NeurIPS (2021)
Srinivasan Arunachalam, Oded Regev, Penghui Yao
On the Gaussian surface area of spectrahedra. Electron. Colloquium Comput. Complex. 28 (2021)
Srinivasan Arunachalam, João F. Doriguello
Matrix hypercontractivity, streaming algorithms and LDCs: the large alphabet case. Electron. Colloquium Comput. Complex. 28 (2021)
Srinivasan Arunachalam, Penghui Yao
Positive spectrahedrons: Geometric properties, Invariance principles and Pseudorandom generators. CoRR (2021)
Srinivasan Arunachalam, Alex B. Grilo, Tom Gur, Igor Carboni Oliveira, Aarthi Sundaram
Quantum learning algorithms imply circuit lower bounds. FOCS (2021)
Srinivasan Arunachalam, Alex Bredariol Grilo, Aarthi Sundaram
Quantum Hardness of Learning Shallow Classical Circuits. SIAM J. Comput. 50 (3) (2021)
Srinivasan Arunachalam, Supartha Podder
Communication Memento: Memoryless Communication Complexity. ITCS (2021)
Srinivasan Arunachalam, Penghui Yao
Positive spectrahedrons: Geometric properties, Invariance principles and Pseudorandom generators. Electron. Colloquium Comput. Complex. 28 (2021)
Anurag Anshu, Srinivasan Arunachalam, Tomotaka Kuwahara, Mehdi Soleimanifar
Sample-efficient learning of quantum many-body systems. CoRR (2020)
Srinivasan Arunachalam, Reevu Maity
Quantum Boosting. ICML (2020)
Srinivasan Arunachalam, Supartha Podder
Communication memento: Memoryless communication complexity. CoRR (2020)
Srinivasan Arunachalam, Alex Bredariol Grilo, Tom Gur, Igor Carboni Oliveira, Aarthi Sundaram
Quantum learning algorithms imply circuit lower bounds. Electron. Colloquium Comput. Complex. 27 (2020)
Yunchao Liu, Srinivasan Arunachalam, Kristan Temme
A rigorous and robust quantum speed-up in supervised machine learning. CoRR (2020)
Srinivasan Arunachalam, Reevu Maity
Quantum Boosting. CoRR (2020)
Srinivasan Arunachalam, Péter Vrana, Jeroen Zuiddam
The Asymptotic Induced Matching Number of Hypergraphs: Balanced Binary Strings. Electron. J. Comb. 27 (3) (2020)
Srinivasan Arunachalam, Alex B. Grilo, Henry Yuen
Quantum statistical query learning. CoRR (2020)
Srinivasan Arunachalam, Aleksandrs Belovs, Andrew M. Childs, Robin Kothari, Ansis Rosmanis, Ronald de Wolf
Quantum Coupon Collector. CoRR (2020)
Srinivasan Arunachalam, Sourav Chakraborty, Michal Koucký, Nitin Saurabh, Ronald de Wolf
Improved Bounds on Fourier Entropy and Min-Entropy. STACS (2020)
Srinivasan Arunachalam, Alex B. Grilo, Tom Gur, Igor Carboni Oliveira, Aarthi Sundaram
Quantum learning algorithms imply circuit lower bounds. CoRR (2020)
Srinivasan Arunachalam, Aleksandrs Belovs, Andrew M. Childs, Robin Kothari, Ansis Rosmanis, Ronald de Wolf
Quantum Coupon Collector. TQC (2020)
Anurag Anshu, Srinivasan Arunachalam, Tomotaka Kuwahara, Mehdi Soleimanifar
Sample-efficient learning of quantum many-body systems. FOCS (2020)
Srinivasan Arunachalam, Sourav Chakraborty, Troy Lee, Manaswi Paraashar, Ronald de Wolf
Two New Results About Quantum Exact Learning. ICALP (2019)
Srinivasan Arunachalam, Alex Bredariol Grilo, Aarthi Sundaram
Quantum hardness of learning shallow classical circuits. Electron. Colloquium Comput. Complex. 26 (2019)
Srinivasan Arunachalam, Péter Vrana, Jeroen Zuiddam
The asymptotic induced matching number of hypergraphs: balanced binary strings. CoRR (2019)
Srinivasan Arunachalam, Jop Briët, Carlos Palazuelos
Quantum Query Algorithms Are Completely Bounded Forms. SIAM J. Comput. 48 (3) (2019)
Srinivasan Arunachalam, Alex Bredariol Grilo, Aarthi Sundaram
Quantum hardness of learning shallow classical circuits. CoRR (2019)
András Gilyén, Srinivasan Arunachalam, Nathan Wiebe
Optimizing quantum optimization algorithms via faster quantum gradient computation. SODA (2019)
Srinivasan Arunachalam, Sourav Chakraborty, Troy Lee, Ronald de Wolf
Two new results about quantum exact learning. CoRR (2018)
Srinivasan Arunachalam, Jop Briët, Carlos Palazuelos
Quantum Query Algorithms are Completely Bounded Forms. ITCS (2018)
Srinivasan Arunachalam, Sourav Chakraborty, Michal Koucký, Nitin Saurabh, Ronald de Wolf
Improved bounds on Fourier entropy and Min-entropy. CoRR (2018)
Srinivasan Arunachalam, Ronald de Wolf
Optimal Quantum Sample Complexity of Learning Algorithms. J. Mach. Learn. Res. 19 (2018)
Srinivasan Arunachalam, Sourav Chakraborty, Michal Koucký, Nitin Saurabh, Ronald de Wolf
Improved bounds on Fourier entropy and Min-entropy. Electron. Colloquium Comput. Complex. 25 (2018)
Srinivasan Arunachalam, Abel Molina, Vincent Russo
Quantum Hedging in Two-Round Prover-Verifier Interactions. TQC (2017)
András Gilyén, Srinivasan Arunachalam, Nathan Wiebe
Optimizing quantum optimization algorithms via faster quantum gradient computation. CoRR (2017)
Srinivasan Arunachalam, Ronald de Wolf
Optimizing the number of gates in quantum search. Quantum Inf. Comput. 17 (3&4) (2017)
Srinivasan Arunachalam, Ronald de Wolf
Optimal Quantum Sample Complexity of Learning Algorithms. Computational Complexity Conference (2017)
Srinivasan Arunachalam, Jop Briët, Carlos Palazuelos
Quantum Query Algorithms are Completely Bounded Forms. CoRR (2017)
Srinivasan Arunachalam, Ronald de Wolf
Guest Column: A Survey of Quantum Learning Theory. SIGACT News 48 (2) (2017)
Srinivasan Arunachalam, Ronald de Wolf
A Survey of Quantum Learning Theory. CoRR (2017)
Srinivasan Arunachalam, Ilias S. Kotsireas
Hard satisfiable 3-SAT instances via autocorrelation. J. Satisf. Boolean Model. Comput. 10 (1) (2016)
Srinivasan Arunachalam, Ronald de Wolf
Optimal Quantum Sample Complexity of Learning Algorithms. CoRR (2016)
Srinivasan Arunachalam, Ronald de Wolf
Optimizing the Number of Gates in Quantum Search. CoRR (2015)
Srinivasan Arunachalam, Nathaniel Johnston, Vincent Russo
Is absolute separability determined by the partial transpose? Quantum Inf. Comput. 15 (7&8) (2015)
Srinivasan Arunachalam, Vlad Gheorghiu, Tomas Jochym-O'Connor, Michele Mosca, Priyaa Varshinee Srinivasan
On the Robustness of Bucket Brigade Quantum RAM. TQC (2015)
Srinivasan Arunachalam, Abel Molina, Vincent Russo
Quantum hedging in two-round prover-verifier interactions. CoRR (2013)