Max Hopkins

47 papers A* 15A 1B 3Journal 27
YearRankTypeTitle / Venue / Authors
2026 J jnl
High Rate Efficient Local List Decoding from HDX.
CoRR
Yotam Dikstein, Max Hopkins, Russell Impagliazzo, Toniann Pitassi
2025 J jnl
Approximate Replicability in Learning.
CoRR
Max Hopkins, Russell Impagliazzo, Christopher Ye
2025 B conf
Do PAC-Learners Learn the Marginal Distribution?
ALT
Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan
2025 J jnl
From Generative to Episodic: Sample-Efficient Replicable Reinforcement Learning.
CoRR
Max Hopkins, Sihan Liu, Christopher Ye, Yuichi Yoshida
2025 A* conf
Hypercontractivity on HDX II: Symmetrization and q-Norms.
STOC
Max Hopkins
2025 A* conf
The Role of Randomness in Stability.
ICML
Max Hopkins, Shay Moran
2025 J jnl
The Role of Randomness in Stability.
CoRR
Max Hopkins, Shay Moran
2024 A* conf
Chernoff Bounds and Reverse Hypercontractivity on HDX.
FOCS
Yotam Dikstein, Max Hopkins
2024 J jnl
Chernoff Bounds and Reverse Hypercontractivity on HDX.
CoRR
Yotam Dikstein, Max Hopkins
2024 J jnl
Chernoff Bounds and Reverse Hypercontractivity on HDX.
Electron. Colloquium Comput. Complex.
Yotam Dikstein, Max Hopkins
2024 — —
High Dimensional Expanders in Analysis and Computation
Max Hopkins
2024 J jnl
Hypercontractivity on HDX II: Symmetrization and q-Norms.
CoRR
Max Hopkins
2024 J jnl
Realizable Learning is All You Need.
TheoretiCS
Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan
2024 A* conf
Replicability in High Dimensional Statistics.
FOCS
Max Hopkins, Russell Impagliazzo, Daniel M. Kane, Sihan Liu, Christopher Ye
2024 J jnl
Replicability in High Dimensional Statistics.
CoRR
Max Hopkins, Russell Impagliazzo, Daniel Kane, Sihan Liu, Christopher Ye
2023 J jnl
Do PAC-Learners Learn the Marginal Distribution?
CoRR
Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan
2023 B conf
Robust Empirical Risk Minimization with Tolerance.
ALT
Robi Bhattacharjee, Max Hopkins, Akash Kumar, Hantao Yu, Kamalika Chaudhuri
2023 A* conf
Sampling Equilibria: Fast No-Regret Learning in Structured Games.
SODA
Daniel Beaglehole, Max Hopkins, Daniel Kane, Sihan Liu, Shachar Lovett
2023 A* conf
Stability Is Stable: Connections between Replicability, Privacy, and Adaptive Generalization.
STOC
Mark Bun, Marco Gaboardi, Max Hopkins, Russell Impagliazzo, Rex Lei, Toniann Pitassi, Satchit Sivakumar, Jessica Sorrell
2023 J jnl
Stability is Stable: Connections between Replicability, Privacy, and Adaptive Generalization.
CoRR
Mark Bun, Marco Gaboardi, Max Hopkins, Russell Impagliazzo, Rex Lei, Toniann Pitassi, Satchit Sivakumar, Jessica Sorrell
2022 A* conf
Active Learning Polynomial Threshold Functions.
NeurIPS
Omri Ben-Eliezer, Max Hopkins, Chutong Yang, Hantao Yu
2022 J jnl
Active Learning Polynomial Threshold Functions.
CoRR
Omri Ben-Eliezer, Max Hopkins, Chutong Yang, Hantao Yu
2022 A conf
Eigenstripping, Spectral Decay, and Edge-Expansion on Posets.
APPROX/RANDOM
Jason Gaitonde, Max Hopkins, Tali Kaufman, Shachar Lovett, Ruizhe Zhang
2022 J jnl
Eigenstripping, Spectral Decay, and Edge-Expansion on Posets.
CoRR
Jason Gaitonde, Max Hopkins, Tali Kaufman, Shachar Lovett, Ruizhe Zhang
2022 A* conf
Explicit Lower Bounds Against Ω(n)-Rounds of Sum-of-Squares.
FOCS
Max Hopkins, Ting-Chun Lin
2022 J jnl
Explicit Lower Bounds Against Ω(n)-Rounds of Sum-of-Squares.
CoRR
Max Hopkins, Ting-Chun Lin
2022 J jnl
Explicit Lower Bounds Against Ω(n)-Rounds of Sum-of-Squares.
Electron. Colloquium Comput. Complex.
Max Hopkins, Ting-Chun Lin
2022 A* conf
High Dimensional Expanders: Eigenstripping, Pseudorandomness, and Unique Games.
SODA
Mitali Bafna, Max Hopkins, Tali Kaufman, Shachar Lovett
2022 A* conf
Hypercontractivity on high dimensional expanders.
STOC
Mitali Bafna, Max Hopkins, Tali Kaufman, Shachar Lovett
2022 A* conf
Realizable Learning is All You Need.
COLT
Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan
2022 J jnl
Robust Empirical Risk Minimization with Tolerance.
CoRR
Robi Bhattacharjee, Max Hopkins, Akash Kumar, Hantao Yu, Kamalika Chaudhuri
2021 A* conf
Bounded Memory Active Learning through Enriched Queries.
COLT
Max Hopkins, Daniel Kane, Shachar Lovett, Michal Moshkovitz
2021 J jnl
Bounded Memory Active Learning through Enriched Queries.
CoRR
Max Hopkins, Daniel Kane, Shachar Lovett, Michal Moshkovitz
2021 J jnl
Hypercontractivity on High Dimensional Expanders: a Local-to-Global Approach for Higher Moments.
CoRR
Mitali Bafna, Max Hopkins, Tali Kaufman, Shachar Lovett
2021 J jnl
Hypercontractivity on High Dimensional Expanders: a Local-to-Global Approach for Higher Moments.
Electron. Colloquium Comput. Complex.
Mitali Bafna, Max Hopkins, Tali Kaufman, Shachar Lovett
2021 J jnl
Realizable Learning is All You Need.
CoRR
Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan
2020 J jnl
High Dimensional Expanders: Random Walks, Pseudorandomness, and Unique Games.
CoRR
Max Hopkins, Tali Kaufman, Shachar Lovett
2020 J jnl
High Dimensional Expanders: Random Walks, Pseudorandomness, and Unique Games.
Electron. Colloquium Comput. Complex.
Max Hopkins, Tali Kaufman, Shachar Lovett
2020 A* conf
Noise-tolerant, Reliable Active Classification with Comparison Queries.
COLT
Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan
2020 J jnl
Noise-tolerant, Reliable Active Classification with Comparison Queries.
CoRR
Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan
2020 A* conf
Point Location and Active Learning: Learning Halfspaces Almost Optimally.
FOCS
Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan
2020 J jnl
Point Location and Active Learning: Learning Halfspaces Almost Optimally.
CoRR
Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan
2020 A* conf
The Power of Comparisons for Actively Learning Linear Classifiers.
NeurIPS
Max Hopkins, Daniel Kane, Shachar Lovett
2019 J jnl
A Novel CMB Component Separation Method: Hierarchical Generalized Morphological Component Analysis.
CoRR
Sebastian Wagner-Carena, Max Hopkins, Ana Diaz Rivero, Cora Dvorkin
2019 J jnl
The Power of Comparisons for Actively Learning Linear Classifiers.
CoRR
Max Hopkins, Daniel M. Kane, Shachar Lovett
2018 B conf
Simulated Annealing for JPEG Quantization.
DCC
Max Hopkins, Michael Mitzenmacher, Sebastian Wagner-Carena
2017 J jnl
Simulated Annealing for JPEG Quantization.
CoRR
Max Hopkins, Michael Mitzenmacher, Sebastian Wagner-Carena