A Simple Geometric Proof of the Optimality of the Sequential Probability Ratio Test for Symmetric Bernoulli Hypotheses.

Gregory Valiant University of California, Berkeley, USA http://www.eecs.berkeley.edu/~gvaliant/ https://dl.acm.org/profile/81350582572 Chirag Pabbaraju Gregory Valiant Rishi Verma A Simple Geometric Proof of the Optimality of the Sequential Probability Ratio Test for Symmetric Bernoulli Hypotheses. 365-384 2026 SOSA https://doi.org/10.1137/1.9781611978964.29 conf/sosa/2026 db/conf/sosa/sosa2026.html#PabbarajuVV26

Shivam Garg 0001 Chirag Pabbaraju Kirankumar Shiragur Gregory Valiant Testing with Non-identically Distributed Samples. 2025 2025 Trans. Mach. Learn. Res. https://openreview.net/forum?id=FUzvztzBlW db/journals/tmlr/tmlr2025.html#GargPSV25 streams/journals/tmlr

Joey Rivkin Gregory Valiant Paul Valiant A Generalized Trace Reconstruction Problem: Recovering a String of Probabilities. 1657-1667 2025 STOC https://doi.org/10.1145/3717823.3718315 https://www.wikidata.org/entity/Q135686004 conf/stoc/2025 db/conf/stoc/stoc2025.html#RivkinVV25 Guy Blanc Gregory Valiant Adaptive and Oblivious Statistical Adversaries Are Equivalent. 2031-2042 2025 STOC https://doi.org/10.1145/3717823.3718193 https://www.wikidata.org/entity/Q135685618 conf/stoc/2025 db/conf/stoc/stoc2025.html#BlancV25

Spencer Compton Gregory Valiant Attainability of Two-Point Testing Rates for Finite-Sample Location Estimation. 2025 February abs/2502.05730 CoRR https://doi.org/10.48550/arXiv.2502.05730 db/journals/corr/corr2502.html#abs-2502-05730 streams/journals/corr

Chirag Pabbaraju Gregory Valiant Rishi Verma A Simple Geometric Proof of the Optimality of the Sequential Probability Ratio Test for Symmetric Bernoulli Hypotheses. 2025 October abs/2510.15790 CoRR https://doi.org/10.48550/arXiv.2510.15790 db/journals/corr/corr2510.html#abs-2510-15790 streams/journals/corr

Steven Cao Gregory Valiant Percy Liang On the Entropy Calibration of Language Models. 2025 November abs/2511.11966 CoRR https://doi.org/10.48550/arXiv.2511.11966 db/journals/corr/corr2511.html#abs-2511-11966 streams/journals/corr

Annie Marsden Vatsal Sharan Aaron Sidford Gregory Valiant Efficient Convex Optimization Requires Superlinear Memory. 41:1-41:37 2024 December 71 J. ACM 6 https://doi.org/10.1145/3689208 https://www.wikidata.org/entity/Q130948513 db/journals/jacm/jacm71.html#MarsdenSSV24 streams/journals/jacm

Gregory Valiant Matrix Multiplication in Quadratic Time and Energy? Towards a Fine-Grained Energy-Centric Church-Turing Thesis. 96:1-96:13 2024 ITCS https://doi.org/10.4230/LIPIcs.ITCS.2024.96 conf/innovations/2024 db/conf/innovations/innovations2024.html#Valiant24 Spencer Compton Gregory Valiant Near-Optimal Mean Estimation with Unknown, Heteroskedastic Variances. 194-200 2024 STOC https://doi.org/10.1145/3618260.3649754 conf/stoc/2024 db/conf/stoc/stoc2024.html#ComptonV24

Guy Blanc Gregory Valiant Adaptive and oblivious statistical adversaries are equivalent. 2024 abs/2410.13548 CoRR https://doi.org/10.48550/arXiv.2410.13548 db/journals/corr/corr2410.html#abs-2410-13548 streams/journals/corr

Omar Salemohamed Laurent Charlin Shivam Garg 0001 Vatsal Sharan Gregory Valiant Discovering Data Structures: Nearest Neighbor Search and Beyond. 2024 abs/2411.03253 CoRR https://doi.org/10.48550/arXiv.2411.03253 db/journals/corr/corr2411.html#abs-2411-03253 streams/journals/corr

Joey Rivkin Gregory Valiant Paul Valiant A Generalized Trace Reconstruction Problem: Recovering a String of Probabilities. 2024 abs/2412.00674 CoRR https://doi.org/10.48550/arXiv.2412.00674 db/journals/corr/corr2412.html#abs-2412-00674 streams/journals/corr

Steven Cao Percy Liang Gregory Valiant One-sided Matrix Completion from Two Observations Per Row. 3599-3624 2023 ICML https://proceedings.mlr.press/v202/cao23d.html conf/icml/2023 db/conf/icml/icml2023.html#CaoLV23 Annie Marsden Vatsal Sharan Aaron Sidford Gregory Valiant Efficient Convex Optimization Requires Superlinear Memory (Extended Abstract). 6468-6473 2023 IJCAI https://doi.org/10.24963/ijcai.2023/722 conf/ijcai/2023 db/conf/ijcai/ijcai2023.html#MarsdenSSV23 Mingda Qiao Gregory Valiant Online Pen Testing. 91:1-91:26 2023 ITCS https://doi.org/10.4230/LIPIcs.ITCS.2023.91 conf/innovations/2023 db/conf/innovations/innovations2023.html#QiaoV23 Qian Huang Eric Zelikman Sarah Li Chen Yuhuai Wu Gregory Valiant Percy Liang Lexinvariant Language Models. 2023 NeurIPS http://papers.nips.cc/paper_files/paper/2023/hash/4b734e95f0788a030a69caa987516186-Abstract-Conference.html conf/nips/2023 db/conf/nips/neurips2023.html#HuangZCWVL23

Qian Huang Eric Zelikman Sarah Li Chen Yuhuai Wu Gregory Valiant Percy Liang Lexinvariant Language Models. 2023 abs/2305.16349 CoRR https://doi.org/10.48550/arXiv.2305.16349 db/journals/corr/corr2305.html#abs-2305-16349

Steven Cao Percy Liang Gregory Valiant One-sided Matrix Completion from Two Observations Per Row. 2023 abs/2306.04049 CoRR https://doi.org/10.48550/arXiv.2306.04049 db/journals/corr/corr2306.html#abs-2306-04049

Shivam Garg 0001 Chirag Pabbaraju Kirankumar Shiragur Gregory Valiant Testing with Non-identically Distributed Samples. 2023 abs/2311.11194 CoRR https://doi.org/10.48550/arXiv.2311.11194 db/journals/corr/corr2311.html#abs-2311-11194

Gregory Valiant Matrix Multiplication in Quadratic Time and Energy? Towards a Fine-Grained Energy-Centric Church-Turing Thesis. 2023 abs/2311.16342 CoRR https://doi.org/10.48550/arXiv.2311.16342 db/journals/corr/corr2311.html#abs-2311-16342

Spencer Compton Gregory Valiant Near-Optimal Mean Estimation with Unknown, Heteroskedastic Variances. 2023 abs/2312.02417 CoRR https://doi.org/10.48550/arXiv.2312.02417 db/journals/corr/corr2312.html#abs-2312-02417

Annie Marsden Vatsal Sharan Aaron Sidford Gregory Valiant Efficient Convex Optimization Requires Superlinear Memory. 2390-2430 2022 COLT https://proceedings.mlr.press/v178/marsden22a.html conf/colt/2022 db/conf/colt/colt2022.html#MarsdenSSV22 Jonathan A. Kelner Annie Marsden Vatsal Sharan Aaron Sidford Gregory Valiant Honglin Yuan Big-Step-Little-Step: Efficient Gradient Methods for Objectives with Multiple Scales. 2431-2540 2022 COLT https://proceedings.mlr.press/v178/kelner22a.html conf/colt/2022 db/conf/colt/colt2022.html#KelnerMSSVY22 Shivam Garg 0001 Dimitris Tsipras Percy Liang Gregory Valiant What Can Transformers Learn In-Context? A Case Study of Simple Function Classes. 2022 conf/nips/2022 NeurIPS http://papers.nips.cc/paper_files/paper/2022/hash/c529dba08a146ea8d6cf715ae8930cbe-Abstract-Conference.html db/conf/nips/neurips2022.html#0001TLV22

Brian Axelrod Shivam Garg 0001 Yanjun Han Vatsal Sharan Gregory Valiant On the Statistical Complexity of Sample Amplification. 2022 abs/2201.04315 CoRR https://arxiv.org/abs/2201.04315 db/journals/corr/corr2201.html#abs-2201-04315

Annie Marsden Vatsal Sharan Aaron Sidford Gregory Valiant Efficient Convex Optimization Requires Superlinear Memory. 2022 abs/2203.15260 CoRR https://doi.org/10.48550/arXiv.2203.15260 db/journals/corr/corr2203.html#abs-2203-15260

Theo Jepsen Stephen Ibanez Gregory Valiant Nick McKeown From Sand to Flour: The Next Leap in Granular Computing with NanoSort. 2022 abs/2204.12615 CoRR https://doi.org/10.48550/arXiv.2204.12615 db/journals/corr/corr2204.html#abs-2204-12615

Shivam Garg 0001 Dimitris Tsipras Percy Liang Gregory Valiant What Can Transformers Learn In-Context? A Case Study of Simple Function Classes. 2022 abs/2208.01066 CoRR https://doi.org/10.48550/arXiv.2208.01066 db/journals/corr/corr2208.html#abs-2208-01066

Mingda Qiao Gregory Valiant Online Pen Testing. 2022 abs/2210.00655 CoRR https://doi.org/10.48550/arXiv.2210.00655 db/journals/corr/corr2210.html#abs-2210-00655

Kartik Chandra Chuma Kabaghe Gregory Valiant Beyond Laurel/Yanny: An Autoencoder-Enabled Search for Polyperceivable Audio. 593-598 2021 ACL/IJCNLP (2) https://doi.org/10.18653/v1/2021.acl-short.75 https://aclanthology.org/2021.acl-short.75 conf/acl/2021-2 db/conf/acl/acl2021-2.html#ChandraKV20 Annie Marsden John C. Duchi Gregory Valiant Misspecification in Prediction Problems and Robustness via Improper Learning. 2161-2169 2021 AISTATS http://proceedings.mlr.press/v130/marsden21a.html conf/aistats/2021 db/conf/aistats/aistats2021.html#MarsdenDV21 Mingda Qiao Gregory Valiant Exponential Weights Algorithms for Selective Learning. 3833-3858 2021 COLT http://proceedings.mlr.press/v134/qiao21a.html conf/colt/2021 db/conf/colt/colt2021.html#QiaoV21 Kai Sheng Tai Peter Bailis Gregory Valiant Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training. 10065-10075 2021 ICML http://proceedings.mlr.press/v139/tai21a.html conf/icml/2021 db/conf/icml/icml2021.html#TaiBV21 Mingda Qiao Gregory Valiant Stronger calibration lower bounds via sidestepping. 456-466 2021 STOC https://doi.org/10.1145/3406325.3451050 conf/stoc/2021 db/conf/stoc/stoc2021.html#QiaoV21

Annie Marsden John C. Duchi Gregory Valiant On Misspecification in Prediction Problems and Robustness via Improper Learning. 2021 abs/2101.05234 CoRR https://arxiv.org/abs/2101.05234 db/journals/corr/corr2101.html#abs-2101-05234

Kai Sheng Tai Peter Bailis Gregory Valiant Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training. 2021 abs/2102.08622 CoRR https://arxiv.org/abs/2102.08622 db/journals/corr/corr2102.html#abs-2102-08622

Mingda Qiao Gregory Valiant Exponential Weights Algorithms for Selective Learning. 2021 abs/2106.15662 CoRR https://arxiv.org/abs/2106.15662 db/journals/corr/corr2106.html#abs-2106-15662

Jonathan A. Kelner Annie Marsden Vatsal Sharan Aaron Sidford Gregory Valiant Honglin Yuan Big-Step-Little-Step: Efficient Gradient Methods for Objectives with Multiple Scales. 2021 abs/2111.03137 CoRR https://arxiv.org/abs/2111.03137 db/journals/corr/corr2111.html#abs-2111-03137

Weihao Kong Emma Brunskill Gregory Valiant Sublinear Optimal Policy Value Estimation in Contextual Bandits. 4377-4387 2020 AISTATS http://proceedings.mlr.press/v108/kong20b.html conf/aistats/2020 db/conf/aistats/aistats2020.html#KongBV20 Guy Blanc Neha Gupta 0002 Gregory Valiant Paul Valiant Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process. 483-513 2020 COLT http://proceedings.mlr.press/v125/blanc20a.html conf/colt/2020 db/conf/colt/colt2020.html#BlancGVV20 Brian Axelrod Shivam Garg 0001 Vatsal Sharan Gregory Valiant Sample Amplification: Increasing Dataset Size even when Learning is Impossible. 442-451 2020 ICML http://proceedings.mlr.press/v119/axelrod20a.html conf/icml/2020 db/conf/icml/icml2020.html#Axelrod0SV20 Sen Wu 0002 Hongyang R. Zhang Gregory Valiant Christopher Ré On the Generalization Effects of Linear Transformations in Data Augmentation. 10410-10420 2020 ICML http://proceedings.mlr.press/v119/wu20g.html conf/icml/2020 db/conf/icml/icml2020.html#WuZVR20 Justin Y. Chen Gregory Valiant Paul Valiant Worst-Case Analysis for Randomly Collected Data. 2020 NeurIPS https://proceedings.neurips.cc/paper/2020/hash/d34a281acc62c6bec66425f0ad6dd645-Abstract.html conf/nips/2020 db/conf/nips/neurips2020.html#ChenVV20 Gregory Valiant Paul Valiant Instance Optimal Distribution Testing and Learning. 506-526 2020 Beyond the Worst-Case Analysis of Algorithms https://doi.org/10.1017/9781108637435.029 books/cu/20/R2020 db/books/collections/R2020.html#ValiantV20

Sen Wu 0002 Hongyang R. Zhang Gregory Valiant Christopher Ré On the Generalization Effects of Linear Transformations in Data Augmentation. 2020 abs/2005.00695 CoRR https://arxiv.org/abs/2005.00695 db/journals/corr/corr2005.html#abs-2005-00695

Mingda Qiao Gregory Valiant Stronger Calibration Lower Bounds via Sidestepping. 2020 abs/2012.03454 CoRR https://arxiv.org/abs/2012.03454 db/journals/corr/corr2012.html#abs-2012-03454

Melody Y. Guan Gregory Valiant A Surprising Density of Illusionable Natural Speech. 1871 2019 CogSci https://escholarship.org/uc/item/1f32959f conf/cogsci/2019 db/conf/cogsci/cogsci2019.html#GuanV19 Mingda Qiao Gregory Valiant A Theory of Selective Prediction. 2580-2594 2019 COLT http://proceedings.mlr.press/v99/qiao19a.html conf/colt/2019 db/conf/colt/colt2019.html#QiaoV19 Vatsal Sharan Kai Sheng Tai Peter Bailis Gregory Valiant Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data. 5690-5700 2019 ICML http://proceedings.mlr.press/v97/sharan19a.html conf/icml/2019 db/conf/icml/icml2019.html#SharanTBV19 Kai Sheng Tai Peter Bailis Gregory Valiant Equivariant Transformer Networks. 6086-6095 2019 ICML http://proceedings.mlr.press/v97/tai19a.html conf/icml/2019 db/conf/icml/icml2019.html#TaiBV19 Ramya Korlakai Vinayak Weihao Kong Gregory Valiant Sham M. Kakade Maximum Likelihood Estimation for Learning Populations of Parameters. 6448-6457 2019 ICML http://proceedings.mlr.press/v97/vinayak19a.html conf/icml/2019 db/conf/icml/icml2019.html#VinayakKVK19 Antonio Ginart Melody Y. Guan Gregory Valiant James Zou 0001 Making AI Forget You: Data Deletion in Machine Learning. 3513-3526 2019 NeurIPS https://proceedings.neurips.cc/paper/2019/hash/cb79f8fa58b91d3af6c9c991f63962d3-Abstract.html http://papers.nips.cc/paper/8611-making-ai-forget-you-data-deletion-in-machine-learning conf/nips/2019 db/conf/nips/nips2019.html#GinartGVZ19 Brian Axelrod Ilias Diakonikolas Alistair Stewart Anastasios Sidiropoulos Gregory Valiant A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families. 7721-7733 2019 NeurIPS https://proceedings.neurips.cc/paper/2019/hash/77cdfc1e11e36a23bb030892ee00b8cf-Abstract.html http://papers.nips.cc/paper/8988-a-polynomial-time-algorithm-for-log-concave-maximum-likelihood-via-locally-exponential-families conf/nips/2019 db/conf/nips/nips2019.html#AxelrodDSSV19 Vatsal Sharan Aaron Sidford Gregory Valiant Memory-sample tradeoffs for linear regression with small error. 890-901 2019 STOC https://doi.org/10.1145/3313276.3316403 https://www.wikidata.org/entity/Q130965688 conf/stoc/2019 db/conf/stoc/stoc2019.html#SharanSV19

Kai Sheng Tai Peter Bailis Gregory Valiant Equivariant Transformer Networks. 2019 abs/1901.11399 CoRR http://arxiv.org/abs/1901.11399 db/journals/corr/corr1901.html#abs-1901-11399

Mingda Qiao Gregory Valiant A Theory of Selective Prediction. 2019 abs/1902.04256 CoRR http://arxiv.org/abs/1902.04256 db/journals/corr/corr1902.html#abs-1902-04256

Ramya Korlakai Vinayak Weihao Kong Gregory Valiant Sham M. Kakade Maximum Likelihood Estimation for Learning Populations of Parameters. 2019 abs/1902.04553 CoRR http://arxiv.org/abs/1902.04553 db/journals/corr/corr1902.html#abs-1902-04553

Vatsal Sharan Aaron Sidford Gregory Valiant Memory-Sample Tradeoffs for Linear Regression with Small Error. 2019 abs/1904.08544 CoRR http://arxiv.org/abs/1904.08544 db/journals/corr/corr1904.html#abs-1904-08544

Guy Blanc Neha Gupta 0002 Gregory Valiant Paul Valiant Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process. 2019 abs/1904.09080 CoRR http://arxiv.org/abs/1904.09080 db/journals/corr/corr1904.html#abs-1904-09080

Brian Axelrod Shivam Garg 0001 Vatsal Sharan Gregory Valiant Sample Amplification: Increasing Dataset Size even when Learning is Impossible. 2019 abs/1904.12053 CoRR http://arxiv.org/abs/1904.12053 db/journals/corr/corr1904.html#abs-1904-12053

Melody Y. Guan Gregory Valiant A Surprising Density of Illusionable Natural Speech. 2019 abs/1906.01040 CoRR http://arxiv.org/abs/1906.01040 db/journals/corr/corr1906.html#abs-1906-01040

Antonio Ginart Melody Y. Guan Gregory Valiant James Zou 0001 Making AI Forget You: Data Deletion in Machine Learning. 2019 abs/1907.05012 CoRR http://arxiv.org/abs/1907.05012 db/journals/corr/corr1907.html#abs-1907-05012

Brian Axelrod Ilias Diakonikolas Anastasios Sidiropoulos Alistair Stewart Gregory Valiant A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families. 2019 abs/1907.08306 CoRR http://arxiv.org/abs/1907.08306 db/journals/corr/corr1907.html#abs-1907-08306

Justin Y. Chen Gregory Valiant Paul Valiant How bad is worst-case data if you know where it comes from? 2019 abs/1911.03605 CoRR http://arxiv.org/abs/1911.03605 db/journals/corr/corr1911.html#abs-1911-03605

Weihao Kong Gregory Valiant Emma Brunskill Sublinear Optimal Policy Value Estimation in Contextual Bandits. 2019 abs/1912.06111 CoRR http://arxiv.org/abs/1912.06111 db/journals/corr/corr1912.html#abs-1912-06111

Michela Meister Gregory Valiant A Data Prism: Semi-verified learning in the small-alpha regime. 1530-1546 2018 COLT http://proceedings.mlr.press/v75/meister18a.html conf/colt/2018 db/conf/colt/colt2018.html#MeisterV18 Jacob Steinhardt Moses Charikar Gregory Valiant Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers. 45:1-45:21 2018 ITCS https://doi.org/10.4230/LIPIcs.ITCS.2018.45 conf/innovations/2018 db/conf/innovations/innovations2018.html#SteinhardtCV18 Qingqing Huang 0001 Sham M. Kakade Weihao Kong Gregory Valiant Recovering Structured Probability Matrices. 46:1-46:14 2018 ITCS https://doi.org/10.4230/LIPIcs.ITCS.2018.46 conf/innovations/2018 db/conf/innovations/innovations2018.html#HuangKKV18 Mingda Qiao Gregory Valiant Learning Discrete Distributions from Untrusted Batches. 47:1-47:20 2018 ITCS https://doi.org/10.4230/LIPIcs.ITCS.2018.47 conf/innovations/2018 db/conf/innovations/innovations2018.html#QiaoV18 David Cohen-Steiner Weihao Kong Christian Sohler Gregory Valiant Approximating the Spectrum of a Graph. 1263-1271 2018 KDD https://doi.org/10.1145/3219819.3220119 conf/kdd/2018 db/conf/kdd/kdd2018.html#Cohen-SteinerKS18 Weihao Kong Gregory Valiant Estimating Learnability in the Sublinear Data Regime. 5460-5469 2018 NeurIPS https://proceedings.neurips.cc/paper/2018/hash/8bd39eae38511daad6152e84545e504d-Abstract.html http://papers.nips.cc/paper/7790-estimating-learnability-in-the-sublinear-data-regime conf/nips/2018 db/conf/nips/nips2018.html#KongV18 Shivam Garg 0001 Vatsal Sharan Brian Hu Zhang Gregory Valiant A Spectral View of Adversarially Robust Features. 10159-10169 2018 NeurIPS https://proceedings.neurips.cc/paper/2018/hash/033cc385728c51d97360020ed57776f0-Abstract.html http://papers.nips.cc/paper/8217-a-spectral-view-of-adversarially-robust-features conf/nips/2018 db/conf/nips/nips2018.html#GargSZV18 Kai Sheng Tai Vatsal Sharan Peter Bailis Gregory Valiant Sketching Linear Classifiers over Data Streams. 757-772 2018 SIGMOD Conference https://doi.org/10.1145/3183713.3196930 conf/sigmod/2018 db/conf/sigmod/sigmod2018.html#TaiSBV18 Vatsal Sharan Sham M. Kakade Percy Liang Gregory Valiant Prediction with a short memory. 1074-1087 2018 STOC https://doi.org/10.1145/3188745.3188954 conf/stoc/2018 db/conf/stoc/stoc2018.html#SharanKLV18

Weihao Kong Gregory Valiant Estimating Learnability in the Sublinear Data Regime. 2018 abs/1805.01626 CoRR http://arxiv.org/abs/1805.01626 db/journals/corr/corr1805.html#abs-1805-01626

Brian Axelrod Gregory Valiant An Efficient Algorithm for High-Dimensional Log-Concave Maximum Likelihood. 2018 abs/1811.03204 CoRR http://arxiv.org/abs/1811.03204 db/journals/corr/corr1811.html#abs-1811-03204

Shivam Garg 0001 Vatsal Sharan Brian Hu Zhang Gregory Valiant A Spectral View of Adversarially Robust Features. 2018 abs/1811.06609 CoRR http://arxiv.org/abs/1811.06609 db/journals/corr/corr1811.html#abs-1811-06609

Gregory Valiant Paul Valiant Estimating the Unseen: Improved Estimators for Entropy and Other Properties. 37:1-37:41 2017 64 J. ACM 6 https://doi.org/10.1145/3125643 db/journals/jacm/jacm64.html#ValiantV17

Gregory Valiant Paul Valiant An Automatic Inequality Prover and Instance Optimal Identity Testing. 429-455 2017 46 SIAM J. Comput. 1 https://doi.org/10.1137/151002526 db/journals/siamcomp/siamcomp46.html#ValiantV17

Aditi Raghunathan Gregory Valiant James Zou 0001 Estimating the unseen from multiple populations. 2855-2863 2017 ICML http://proceedings.mlr.press/v70/raghunathan17a.html conf/icml/2017 db/conf/icml/icml2017.html#RaghunathanVZ17 Vatsal Sharan Gregory Valiant Orthogonalized ALS: A Theoretically Principled Tensor Decomposition Algorithm for Practical Use. 3095-3104 2017 ICML http://proceedings.mlr.press/v70/sharan17a.html conf/icml/2017 db/conf/icml/icml2017.html#SharanV17 Vatsal Sharan Sham M. Kakade Percy Liang Gregory Valiant Learning Overcomplete HMMs. 940-949 2017 NIPS https://proceedings.neurips.cc/paper/2017/hash/6aca97005c68f1206823815f66102863-Abstract.html http://papers.nips.cc/paper/6695-learning-overcomplete-hmms conf/nips/2017 db/conf/nips/nips2017.html#SharanKLV17 Kevin Tian Weihao Kong Gregory Valiant Learning Populations of Parameters. 5778-5787 2017 NIPS https://proceedings.neurips.cc/paper/2017/hash/bc4e356fee1972242c8f7eabf4dff517-Abstract.html http://papers.nips.cc/paper/7160-learning-populations-of-parameters conf/nips/2017 db/conf/nips/nips2017.html#TianKV17 Moses Charikar Jacob Steinhardt Gregory Valiant Learning from untrusted data. 47-60 2017 STOC https://doi.org/10.1145/3055399.3055491 conf/stoc/2017 db/conf/stoc/stoc2017.html#CharikarSV17

Vatsal Sharan Gregory Valiant Orthogonalized ALS: A Theoretically Principled Tensor Decomposition Algorithm for Practical Use. 2017 abs/1703.01804 CoRR http://arxiv.org/abs/1703.01804 db/journals/corr/corr1703.html#SharanV17

Jacob Steinhardt Moses Charikar Gregory Valiant Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers. 2017 abs/1703.04940 CoRR http://arxiv.org/abs/1703.04940 db/journals/corr/corr1703.html#SteinhardtCV17

Vatsal Sharan Kai Sheng Tai Peter Bailis Gregory Valiant There and Back Again: A General Approach to Learning Sparse Models. 2017 abs/1706.08146 CoRR http://arxiv.org/abs/1706.08146 db/journals/corr/corr1706.html#SharanTBV17

Aditi Raghunathan Gregory Valiant James Zou 0001 Estimating the unseen from multiple populations. 2017 abs/1707.03854 CoRR http://arxiv.org/abs/1707.03854 db/journals/corr/corr1707.html#RaghunathanVZ17

Michela Meister Gregory Valiant A Data Prism: Semi-Verified Learning in the Small-Alpha Regime. 2017 abs/1708.02740 CoRR http://arxiv.org/abs/1708.02740 db/journals/corr/corr1708.html#abs-1708-02740

Kevin Tian Weihao Kong Gregory Valiant Optimally Learning Populations of Parameters. 2017 abs/1709.02707 CoRR http://arxiv.org/abs/1709.02707 db/journals/corr/corr1709.html#abs-1709-02707

Kai Sheng Tai Vatsal Sharan Peter Bailis Gregory Valiant Finding Heavily-Weighted Features in Data Streams. 2017 abs/1711.02305 CoRR http://arxiv.org/abs/1711.02305 db/journals/corr/corr1711.html#abs-1711-02305

Vatsal Sharan Sham M. Kakade Percy Liang Gregory Valiant Learning Overcomplete HMMs. 2017 abs/1711.02309 CoRR http://arxiv.org/abs/1711.02309 db/journals/corr/corr1711.html#abs-1711-02309

Mingda Qiao Gregory Valiant Learning Discrete Distributions from Untrusted Batches. 2017 abs/1711.08113 CoRR http://arxiv.org/abs/1711.08113 db/journals/corr/corr1711.html#abs-1711-08113

David Cohen-Steiner Weihao Kong Christian Sohler Gregory Valiant Approximating the Spectrum of a Graph. 2017 abs/1712.01725 CoRR http://arxiv.org/abs/1712.01725 db/journals/corr/corr1712.html#abs-1712-01725

Jacob Steinhardt Gregory Valiant Stefan Wager Memory, Communication, and Statistical Queries. 1490-1516 2016 COLT http://proceedings.mlr.press/v49/steinhardt16.html conf/colt/2016 db/conf/colt/colt2016.html#SteinhardtVW16 Michael S. Crouch Andrew McGregor 0001 Gregory Valiant David P. Woodruff Stochastic Streams: Sample Complexity vs. Space Complexity. 32:1-32:15 2016 ESA https://doi.org/10.4230/LIPIcs.ESA.2016.32 conf/esa/2016 db/conf/esa/esa2016.html#CrouchMVW16 Jacob Steinhardt Gregory Valiant Moses Charikar Avoiding Imposters and Delinquents: Adversarial Crowdsourcing and Peer Prediction. 4439-4447 2016 NIPS https://proceedings.neurips.cc/paper/2016/hash/0a87257e5308197df43230edf4ad1dae-Abstract.html http://papers.nips.cc/paper/6440-avoiding-imposters-and-delinquents-adversarial-crowdsourcing-and-peer-prediction conf/nips/2016 db/conf/nips/nips2016.html#SteinhardtVC16 Gregory Valiant Paul Valiant Instance optimal learning of discrete distributions. 142-155 2016 STOC https://doi.org/10.1145/2897518.2897641 conf/stoc/2016 db/conf/stoc/stoc2016.html#ValiantV16

Weihao Kong Gregory Valiant Spectrum Estimation from Samples. 2016 abs/1602.00061 CoRR http://arxiv.org/abs/1602.00061 db/journals/corr/corr1602.html#KongV16

Qingqing Huang 0001 Sham M. Kakade Weihao Kong Gregory Valiant Recovering Structured Probability Matrices. 2016 abs/1602.06586 CoRR http://arxiv.org/abs/1602.06586 db/journals/corr/corr1602.html#HuangKKV16

Gregory Valiant Paul Valiant Information Theoretically Secure Databases. 2016 abs/1605.02646 CoRR http://arxiv.org/abs/1605.02646 db/journals/corr/corr1605.html#ValiantV16

Jacob Steinhardt Gregory Valiant Moses Charikar Avoiding Imposters and Delinquents: Adversarial Crowdsourcing and Peer Prediction. 2016 abs/1606.05374 CoRR http://arxiv.org/abs/1606.05374 db/journals/corr/corr1606.html#SteinhardtVC16

Moses Charikar Jacob Steinhardt Gregory Valiant Learning from Untrusted Data. 2016 abs/1611.02315 CoRR http://arxiv.org/abs/1611.02315 db/journals/corr/corr1611.html#CharikarSV16

Sham M. Kakade Percy Liang Vatsal Sharan Gregory Valiant Prediction with a Short Memory. 2016 abs/1612.02526 CoRR http://arxiv.org/abs/1612.02526 db/journals/corr/corr1612.html#KakadeLSV16

Gregory Valiant Paul Valiant Information Theoretically Secure Databases. TR16-078 2016 TR16 Electron. Colloquium Comput. Complex. https://eccc.weizmann.ac.il/report/2016/078 db/journals/eccc/eccc23.html#ValiantV16

Gregory Valiant Finding Correlations in Subquadratic Time, with Applications to Learning Parities and the Closest Pair Problem. 13:1-13:45 2015 62 J. ACM 2 https://doi.org/10.1145/2728167 db/journals/jacm/jacm62.html#Valiant15

Bhaswar B. Bhattacharya Gregory Valiant Testing Closeness With Unequal Sized Samples. 2611-2619 2015 NIPS https://proceedings.neurips.cc/paper/2015/hash/5cce8dede893813f879b873962fb669f-Abstract.html http://papers.nips.cc/paper/5908-testing-closeness-with-unequal-sized-samples conf/nips/2015 db/conf/nips/nips2015.html#BhattacharyaV15

Bhaswar B. Bhattacharya Gregory Valiant Testing Closeness With Unequal Sized Samples. 2015 abs/1504.04599 CoRR http://arxiv.org/abs/1504.04599 db/journals/corr/corr1504.html#BhattacharyaV15

Gregory Valiant Paul Valiant Instance Optimal Learning. 2015 abs/1504.05321 CoRR http://arxiv.org/abs/1504.05321 db/journals/corr/corr1504.html#ValiantV15

Jacob Steinhardt Gregory Valiant Stefan Wager Memory, Communication, and Statistical Queries. TR15-126 2015 TR15 Electron. Colloquium Comput. Complex. https://eccc.weizmann.ac.il/report/2015/126 db/journals/eccc/eccc22.html#SteinhardtVW15

Gregory Valiant Paul Valiant An Automatic Inequality Prover and Instance Optimal Identity Testing. 51-60 2014 FOCS https://doi.org/10.1109/FOCS.2014.14 https://doi.ieeecomputersociety.org/10.1109/FOCS.2014.14 conf/focs/2014 db/conf/focs/focs2014.html#ValiantV14 Adi Livnat Christos H. Papadimitriou Aviad Rubinstein Gregory Valiant Andrew Wan Satisfiability and Evolution. 524-530 2014 FOCS https://doi.org/10.1109/FOCS.2014.62 https://doi.ieeecomputersociety.org/10.1109/FOCS.2014.62 conf/focs/2014 db/conf/focs/focs2014.html#LivnatPRVW14 Alekh Agarwal Sham M. Kakade Nikos Karampatziakis Le Song Gregory Valiant Least Squares Revisited: Scalable Approaches for Multi-class Prediction. 541-549 2014 ICML http://proceedings.mlr.press/v32/agarwala14.html conf/icml/2014 db/conf/icml/icml2014.html#AgarwalKKSV14 Alexandr Andoni Rina Panigrahy Gregory Valiant Li Zhang 0001 Learning Polynomials with Neural Networks. 1908-1916 2014 ICML http://proceedings.mlr.press/v32/andoni14.html conf/icml/2014 db/conf/icml/icml2014.html#AndoniPV014 Alexandr Andoni Rina Panigrahy Gregory Valiant Li Zhang 0001 Learning Sparse Polynomial Functions. 500-510 2014 SODA https://doi.org/10.1137/1.9781611973402.37 conf/soda/2014 db/conf/soda/soda2014.html#AndoniPV014 Siu On Chan Ilias Diakonikolas Paul Valiant Gregory Valiant Optimal Algorithms for Testing Closeness of Discrete Distributions. 1193-1203 2014 SODA https://doi.org/10.1137/1.9781611973402.88 conf/soda/2014 db/conf/soda/soda2014.html#ChanDVV14 Paul Valiant Gregory Valiant Estimating the Unseen: Improved Estimators for Entropy and other Properties. 2157-2165 2013 NIPS https://proceedings.neurips.cc/paper/2013/hash/53c04118df112c13a8c34b38343b9c10-Abstract.html http://papers.nips.cc/paper/5170-estimating-the-unseen-improved-estimators-for-entropy-and-other-properties conf/nips/2013 db/conf/nips/nips2013.html#ValiantV13 Constantinos Daskalakis Ilias Diakonikolas Rocco A. Servedio Gregory Valiant Paul Valiant Testing <i>k</i>-Modal Distributions: Optimal Algorithms via Reductions. 1833-1852 2013 SODA https://doi.org/10.1137/1.9781611973105.131 conf/soda/2013 db/conf/soda/soda2013.html#DaskalakisDSVV13

Elchanan Mossel Anupam Prakash Gregory Valiant Computation in anonymous networks. 2013 CoRR http://arxiv.org/abs/1306.4151 abs/1306.4151 db/journals/corr/corr1306.html#MosselPV13

Siu On Chan Ilias Diakonikolas Gregory Valiant Paul Valiant Optimal Algorithms for Testing Closeness of Discrete Distributions. 2013 CoRR http://arxiv.org/abs/1308.3946 abs/1308.3946 db/journals/corr/corr1308.html#ChanDVV13

Alekh Agarwal Sham M. Kakade Nikos Karampatziakis Le Song Gregory Valiant Least Squares Revisited: Scalable Approaches for Multi-class Prediction. 2013 CoRR http://arxiv.org/abs/1310.1949 abs/1310.1949 db/journals/corr/corr1310.html#AgarwalKKSV13

Gregory Valiant Paul Valiant Instance-by-instance optimal identity testing. TR13-111 2013 TR13 Electron. Colloquium Comput. Complex. https://eccc.weizmann.ac.il/report/2013/111 db/journals/eccc/eccc20.html#ValiantV13

Gregory Valiant Algorithmic Approaches to Statistical Questions. University of California, Berkeley, USA 2012 https://www.escholarship.org/uc/item/6398n1j7

Adam Tauman Kalai Ankur Moitra Gregory Valiant Disentangling Gaussians. 113-120 2012 55 Commun. ACM 2 https://doi.org/10.1145/2076450.2076474 db/journals/cacm/cacm55.html#KalaiMV12

Georg Gottlob Stephanie Tien Lee Gregory Valiant Paul Valiant Size and Treewidth Bounds for Conjunctive Queries. 16:1-16:35 2012 59 J. ACM 3 https://doi.org/10.1145/2220357.2220363 https://www.wikidata.org/entity/Q59259504 db/journals/jacm/jacm59.html#GottlobLVV12

Gregory Valiant Finding Correlations in Subquadratic Time, with Applications to Learning Parities and Juntas. 11-20 2012 FOCS https://doi.org/10.1109/FOCS.2012.27 https://doi.ieeecomputersociety.org/10.1109/FOCS.2012.27 conf/focs/2012 db/conf/focs/focs2012.html#Valiant12

Gregory Valiant Finding Correlations in Subquadratic Time, with Applications to Learning Parities and Juntas with Noise. TR12-006 2012 TR12 Electron. Colloquium Comput. Complex. https://eccc.weizmann.ac.il/report/2012/006 db/journals/eccc/eccc19.html#Valiant12

Gregory Valiant Beating brute-force: Improved algorithms for finding correlations, and related problems. 2012 1 Tiny Trans. Comput. Sci. http://tinytocs.org/vol1/papers/tinytocs-v1-valiant.pdf db/journals/tinytocs/tinytocs1.html#Valiant12

Noam Nisan Michael Schapira Gregory Valiant Aviv Zohar When is it best to best-respond? 16-18 2011 10 SIGecom Exch. 2 https://doi.org/10.1145/1998549.1998552 db/journals/sigecom/sigecom10.html#NisanSVZ11

Gregory Valiant Paul Valiant The Power of Linear Estimators. 403-412 2011 FOCS https://doi.org/10.1109/FOCS.2011.81 https://doi.ieeecomputersociety.org/10.1109/FOCS.2011.81 conf/focs/2011 db/conf/focs/focs2011.html#ValiantV11 Noam Nisan Michael Schapira Gregory Valiant Aviv Zohar Best-Response Mechanisms. 155-165 2011 ICS http://conference.iiis.tsinghua.edu.cn/ICS2011/content/papers/24.html conf/innovations/2011 db/conf/innovations/innovations2011.html#NisanSVZ11 Noam Nisan Michael Schapira Gregory Valiant Aviv Zohar Incentive-compatible distributed greedy protocols. 335-336 2011 PODC https://doi.org/10.1145/1993806.1993871 conf/podc/2011 db/conf/podc/podc2011.html#NisanSVZ11 Noam Nisan Michael Schapira Gregory Valiant Aviv Zohar Best-response auctions. 351-360 2011 EC https://doi.org/10.1145/1993574.1993633 conf/sigecom/2011 db/conf/sigecom/sigecom2011.html#NisanSVZ11 Gregory Valiant Paul Valiant Estimating the unseen: an n/log(n)-sample estimator for entropy and support size, shown optimal via new CLTs. 685-694 2011 STOC https://doi.org/10.1145/1993636.1993727 conf/stoc/2011 db/conf/stoc/stoc2011.html#ValiantV11

Constantinos Daskalakis Ilias Diakonikolas Rocco A. Servedio Gregory Valiant Paul Valiant Testing $k$-Modal Distributions: Optimal Algorithms via Reductions http://arxiv.org/abs/1112.5659 2011 CoRR abs/1112.5659 db/journals/corr/corr1112.html#abs-1112-5659

Gregory Valiant Tim Roughgarden Braess's Paradox in large random graphs. 495-515 2010 37 Random Struct. Algorithms 4 https://doi.org/10.1002/rsa.20325 db/journals/rsa/rsa37.html#ValiantR10

Ho-Lin Chen Tim Roughgarden Gregory Valiant Designing Network Protocols for Good Equilibria. 1799-1832 2010 39 SIAM J. Comput. 5 https://doi.org/10.1137/08072721X db/journals/siamcomp/siamcomp39.html#ChenRV10

Ankur Moitra Gregory Valiant Settling the Polynomial Learnability of Mixtures of Gaussians. 93-102 2010 FOCS https://doi.org/10.1109/FOCS.2010.15 https://doi.ieeecomputersociety.org/10.1109/FOCS.2010.15 conf/focs/2010 db/conf/focs/focs2010.html#MoitraV10 Christos H. Papadimitriou Gregory Valiant A New Look at Selfish Routing. 178-187 2010 ICS http://conference.iiis.tsinghua.edu.cn/ICS2010/content/papers/15.html conf/innovations/2010 db/conf/innovations/innovations2010.html#PapadimitriouV10 Constantinos Daskalakis Rafael M. Frongillo Christos H. Papadimitriou George Pierrakos Gregory Valiant On Learning Algorithms for Nash Equilibria. 114-125 2010 SAGT https://doi.org/10.1007/978-3-642-16170-4_11 conf/sagt/2010 db/conf/sagt/sagt2010.html#DaskalakisFPPV10 Adam Tauman Kalai Ankur Moitra Gregory Valiant Efficiently learning mixtures of two Gaussians. 553-562 2010 STOC https://doi.org/10.1145/1806689.1806765 conf/stoc/2010 db/conf/stoc/stoc2010.html#KalaiMV10

Ankur Moitra Gregory Valiant Settling the Polynomial Learnability of Mixtures of Gaussians http://arxiv.org/abs/1004.4223 2010 CoRR abs/1004.4223 db/journals/corr/corr1004.html#abs-1004-4223

Gregory Valiant Paul Valiant A CLT and tight lower bounds for estimating entropy. TR10-179 2010 TR10 Electron. Colloquium Comput. Complex. https://eccc.weizmann.ac.il/report/2010/179 db/journals/eccc/eccc17.html#ValiantV10b

Gregory Valiant Paul Valiant Estimating the unseen: A sublinear-sample canonical estimator of distributions. TR10-180 2010 TR10 Electron. Colloquium Comput. Complex. https://eccc.weizmann.ac.il/report/2010/180 db/journals/eccc/eccc17.html#ValiantV10c

Georg Gottlob Stephanie Tien Lee Gregory Valiant Size and treewidth bounds for conjunctive queries. 45-54 2009 PODS https://doi.org/10.1145/1559795.1559804 https://www.wikidata.org/entity/Q59259603 conf/pods/2009 db/conf/pods/pods2009.html#GottlobLV09 Constantinos Daskalakis Grant Schoenebeck Gregory Valiant Paul Valiant On the complexity of Nash equilibria of action-graph games. 710-719 2009 SODA https://doi.org/10.1137/1.9781611973068.78 http://dl.acm.org/citation.cfm?id=1496770.1496848 conf/soda/2009 db/conf/soda/soda2009.html#DaskalakisSVV09

Gregory Valiant Paul Valiant Size Bounds for Conjunctive Queries with General Functional Dependencies http://arxiv.org/abs/0909.2030 2009 CoRR abs/0909.2030 db/journals/corr/corr0909.html#abs-0909-2030

Ho-Lin Chen Tim Roughgarden Gregory Valiant Designing networks with good equilibria. 854-863 2008 SODA http://dl.acm.org/citation.cfm?id=1347082.1347176 conf/soda/2008 db/conf/soda/soda2008.html#ChenRV08

Constantinos Daskalakis Grant Schoenebeck Gregory Valiant Paul Valiant On the Complexity of Nash Equilibria of Action-Graph Games http://arxiv.org/abs/0802.1604 2008 CoRR abs/0802.1604 db/journals/corr/corr0802.html#abs-0802-1604

Gregory Valiant Tim Roughgarden Braess's paradox in large random graphs. 296-305 2006 conf/sigecom/2006 EC https://doi.org/10.1145/1134707.1134740 db/conf/sigecom/sigecom2006.html#ValiantR06 Alekh Agarwal Alexandr Andoni Brian Axelrod Peter Bailis Bhaswar B. Bhattacharya Guy Blanc Emma Brunskill Steven Cao Siu On Chan Kartik Chandra Moses Charikar Laurent Charlin Ho-Lin Chen Justin Y. Chen Sarah Li Chen David Cohen-Steiner Spencer Compton Michael S. Crouch Constantinos Daskalakis Ilias Diakonikolas John C. Duchi Rafael M. Frongillo Shivam Garg 0001 Antonio A. GinartAntonio Ginart Georg Gottlob Melody Y. Guan Neha Gupta 0002 Yanjun Han Qian Huang Qingqing Huang 0001 Stephen Ibanez Theo Jepsen Chuma Kabaghe Sham M. Kakade Adam Tauman Kalai Nikos Karampatziakis Jonathan A. Kelner Weihao Kong Stephanie Tien Lee Percy Liang Adi Livnat Annie Marsden Andrew McGregor 0001 Nick McKeown Michela Meister Ankur Moitra Elchanan Mossel Noam Nisan Chirag Pabbaraju Rina Panigrahy Christos H. Papadimitriou George Pierrakos Anupam Prakash Mingda Qiao Aditi Raghunathan Christopher Ré Joey Rivkin Timothy RoughgardenTim Roughgarden Aviad Rubinstein Omar Salemohamed Michael Schapira Grant Schoenebeck Rocco A. Servedio Vatsal Sharan Kirankumar Shiragur Aaron Sidford Anastasios Sidiropoulos Christian Sohler Le Song Jacob Steinhardt Alistair Stewart Kai Sheng Tai Kevin Tian Dimitris Tsipras Paul Valiant Rishi Verma Ramya Korlakai Vinayak Stefan Wager Andrew Wan David P. Woodruff Sen Wu 0002 Yuhuai Wu Honglin Yuan Eric Zelikman Brian Hu Zhang Hongyang R. Zhang Li Zhang 0001 Aviv Zohar James Zou 0001