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Jerry Li 0001
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Publications
- 2024
- [i70]Sitan Chen, Jerry Li, Allen Liu:
An optimal tradeoff between entanglement and copy complexity for state tomography. CoRR abs/2402.16353 (2024) - 2023
- [c62]Sitan Chen, Brice Huang, Jerry Li, Allen Liu, Mark Sellke:
When Does Adaptivity Help for Quantum State Learning? FOCS 2023: 391-404 - [c58]Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, Anru Zhang:
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions. ICLR 2023 - [c56]Sitan Chen, Jerry Li, Yuanzhi Li, Anru R. Zhang:
Learning Polynomial Transformations via Generalized Tensor Decompositions. STOC 2023: 1671-1684 - 2022
- [c54]Sitan Chen, Jerry Li, Ryan O'Donnell:
Toward Instance-Optimal State Certification With Incoherent Measurements. COLT 2022: 2541-2596 - [c53]Sitan Chen, Jerry Li, Brice Huang, Allen Liu:
Tight Bounds for Quantum State Certification with Incoherent Measurements. FOCS 2022: 1205-1213 - [c52]Sitan Chen, Jerry Li, Yuanzhi Li, Raghu Meka:
Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs. ICLR 2022 - [c51]Sitan Chen, Jerry Li, Yuanzhi Li:
Learning (Very) Simple Generative Models Is Hard. NeurIPS 2022 - [i63]Sitan Chen, Jerry Li, Yuanzhi Li, Raghu Meka:
Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs. CoRR abs/2201.07206 (2022) - [i61]Sitan Chen, Jerry Li, Yuanzhi Li, Anru R. Zhang:
Learning Polynomial Transformations. CoRR abs/2204.04209 (2022) - [i60]Sitan Chen, Brice Huang, Jerry Li, Allen Liu:
Tight Bounds for Quantum State Certification with Incoherent Measurements. CoRR abs/2204.07155 (2022) - [i59]Sitan Chen, Jerry Li, Yuanzhi Li:
Learning (Very) Simple Generative Models Is Hard. CoRR abs/2205.16003 (2022) - [i58]Sitan Chen, Brice Huang, Jerry Li, Allen Liu, Mark Sellke:
Tight Bounds for State Tomography with Incoherent Measurements. CoRR abs/2206.05265 (2022) - [i57]Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, Anru R. Zhang:
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions. CoRR abs/2209.11215 (2022) - [i56]Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li:
The Complexity of NISQ. CoRR abs/2210.07234 (2022) - 2021
- [c45]Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li:
Exponential Separations Between Learning With and Without Quantum Memory. FOCS 2021: 574-585 - [i55]Sitan Chen, Jerry Li, Ryan O'Donnell:
Toward Instance-Optimal State Certification With Incoherent Measurements. CoRR abs/2102.13098 (2021) - [i50]Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li:
A Hierarchy for Replica Quantum Advantage. CoRR abs/2111.05874 (2021) - [i49]Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, Jerry Li:
Exponential separations between learning with and without quantum memory. CoRR abs/2111.05881 (2021) - [i47]Hsin-Yuan Huang, Michael Broughton, Jordan Cotler, Sitan Chen, Jerry Li, Masoud Mohseni, Hartmut Neven, Ryan Babbush, Richard Kueng, John Preskill, Jarrod R. McClean:
Quantum advantage in learning from experiments. CoRR abs/2112.00778 (2021) - 2020
- [c40]Sébastien Bubeck, Sitan Chen, Jerry Li:
Entanglement is Necessary for Optimal Quantum Property Testing. FOCS 2020: 692-703 - [c36]Sitan Chen, Jerry Li, Ankur Moitra:
Learning Structured Distributions From Untrusted Batches: Faster and Simpler. NeurIPS 2020 - [c32]Sitan Chen, Jerry Li, Zhao Song:
Learning mixtures of linear regressions in subexponential time via Fourier moments. STOC 2020: 587-600 - [c30]Sitan Chen, Jerry Li, Ankur Moitra:
Efficiently learning structured distributions from untrusted batches. STOC 2020: 960-973 - [i43]Sitan Chen, Jerry Li, Ankur Moitra:
Learning Structured Distributions From Untrusted Batches: Faster and Simpler. CoRR abs/2002.10435 (2020) - [i41]Sébastien Bubeck, Sitan Chen, Jerry Li:
Entanglement is Necessary for Optimal Quantum Property Testing. CoRR abs/2004.07869 (2020) - 2019
- [i26]Sitan Chen, Jerry Li, Ankur Moitra:
Efficiently Learning Structured Distributions from Untrusted Batches. CoRR abs/1911.02035 (2019) - [i24]Sitan Chen, Jerry Li, Zhao Song:
Learning Mixtures of Linear Regressions in Subexponential Time via Fourier Moments. CoRR abs/1912.07629 (2019)
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