Philippe Rigollet

91 papers A* 22A 8B 1Journal 59Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	YuriiFormer: A Suite of Nesterov-Accelerated Transformers. CoRR Aleksandr Zimin, Yury Polyanskiy, Philippe Rigollet
2025	J	`jnl`	Covariance Alignment: From Maximum Likelihood Estimation to Gromov-Wasserstein. SIAM J. Math. Data Sci. Yanjun Han, Philippe Rigollet, George Stepaniants
2025	J	`jnl`	Critical attention scaling in long-context transformers. CoRR Shi Chen, Zhengjiang Lin, Yury Polyanskiy, Philippe Rigollet
2025	J	`jnl`	Gaussian mixture layers for neural networks. CoRR Sinho Chewi, Philippe Rigollet, Yuling Yan
2025	J	`jnl`	Gaussian mixture layers for neural networks. Trans. Mach. Learn. Res. Sinho Chewi, Philippe Rigollet, Yuling Yan
2025	J	`jnl`	Normalization in Attention Dynamics. CoRR Nikita Karagodin, Shu Ge, Yury Polyanskiy, Philippe Rigollet
2025	J	`jnl`	On the Structure of Stationary Solutions to McKean-Vlasov Equations with Applications to Noisy Transformers. CoRR Krishnakumar Balasubramanian, Sayan Banerjee, Philippe Rigollet
2025	J	`jnl`	Quantitative Clustering in Mean-Field Transformer Models. CoRR Shi Chen, Zhengjiang Lin, Yury Polyanskiy, Philippe Rigollet
2025	J	`jnl`	Residual connections provably mitigate oversmoothing in graph neural networks. CoRR Ziang Chen, Zhengjiang Lin, Shi Chen, Yury Polyanskiy, Philippe Rigollet
2025	J	`jnl`	Splat Regression Models. CoRR Mara Daniels, Philippe Rigollet
2025	J	`jnl`	Synchronization of mean-field models on the circle. CoRR Yury Polyanskiy, Philippe Rigollet, Andrew Yao
2025	J	`jnl`	The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS). CoRR Andrew Ferguson, Marisa Lafleur, Lars Ruthotto, Jesse Thaler, Yuan-Sen Ting, Pratyush Tiwary, Soledad Villar, E. Paulo Alves, Jeremy Avigad, Simon Billinge, Camille L. Bilodeau, Keith Brown, Emmanuel J. Candès, Arghya Chattopadhyay, Bingqing Cheng, Jonathan Clausen, Connor W. Coley, Andrew J. Connolly, Fred Daum, Sijia S. Dong, Chrisy Xiyu Du, Cora Dvorkin, Cristiano Fanelli, Eric B. Ford, Luis Manuel Frutos, Nicolás García Trillos, Cecilia Garraffo, Robert Ghrist, Rafael Gómez-Bombarelli, Gianluca Guadagni, Sreelekha Guggilam, Sergei Gukov, Juan B. Gutierrez, Salman Habib, Johannes Hachmann, Boris Hanin, Philip C. Harris, Murray Holland, Elizabeth Holm, Hsin-Yuan Huang, Shih-Chieh Hsu, Nick Jackson, Olexandr Isayev, Heng Ji, Aggelos K. Katsaggelos, Jeremy Kepner, Yannis G. Kevrekidis, Michelle P. Kuchera, J. Nathan Kutz, Branislava Lalic, Ann Lee, Matt LeBlanc, Josiah Lim, Rebecca Lindsey, Yongmin Liu, Peter Y. Lu, Sudhir Malik, Vuk Mandic, Vidya B. Manian, Emeka P. Mazi, Pankaj Mehta, Peter Melchior, Brice Ménard, Jennifer Ngadiuba, Stella Offner, Elsa Olivetti, Shyue Ping Ong, Christopher Rackauckas, Philippe Rigollet, Chad Risko, Philip Romero, Grant M. Rotskoff, Brett Savoie, Uros Seljak, David Shih, Gary Shiu, Dima Shlyakhtenko, Eva Silverstein, Taylor Sparks, Thomas Strohmer, Christopher Stubbs, Stephen Thomas, Suriyanarayanan Vaikuntanathan, René Vidal, Francisco Villaescusa-Navarro, Gregory Voth, Benjamin Wandelt, Rachel Ward, Melanie Weber, Risa Wechsler, Stephen Whitelam, Olaf Wiest, Mike Williams, Zhuoran Yang, Yaroslava G. Yingling, Bin Yu, Shuwen Yue, Ann Zabludoff, Huimin Zhao, Tong Zhang
2025	J	`jnl`	The Mean-Field Dynamics of Transformers. CoRR Philippe Rigollet
2025	J	`jnl`	The power of fine-grained experts: Granularity boosts expressivity in Mixture of Experts. CoRR Enric Boix-Adserà, Philippe Rigollet
2024	J	`jnl`	An Algorithmic Solution to the Blotto Game Using Multimarginal Couplings. Oper. Res. Vianney Perchet, Philippe Rigollet, Thibaut Le Gouic
2024	A*	`conf`	Clustering in Causal Attention Masking. NeurIPS Nikita Karagodin, Yury Polyanskiy, Philippe Rigollet
2024	J	`jnl`	Clustering in Causal Attention Masking. CoRR Nikita Karagodin, Yury Polyanskiy, Philippe Rigollet
2024	J	`jnl`	Dynamic metastability in the self-attention model. CoRR Borjan Geshkovski, Hugo Koubbi, Yury Polyanskiy, Philippe Rigollet
2024	J	`jnl`	Measure-to-measure interpolation using Transformers. CoRR Borjan Geshkovski, Philippe Rigollet, Domènec Ruiz-Balet
2023	J	`jnl`	A mathematical perspective on Transformers. CoRR Borjan Geshkovski, Cyril Letrouit, Yury Polyanskiy, Philippe Rigollet
2023	A	`conf`	Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery. AISTATS Tyler Maunu, Thibaut Le Gouic, Philippe Rigollet
2023	J	`jnl`	Covariance alignment: from maximum likelihood estimation to Gromov-Wasserstein. CoRR Yanjun Han, Philippe Rigollet, George Stepaniants
2023	J	`jnl`	Learning Gaussian Mixtures Using the Wasserstein-Fisher-Rao Gradient Flow. CoRR Yuling Yan, Kaizheng Wang, Philippe Rigollet
2023	J	`jnl`	Optimal transport for automatic alignment of untargeted metabolomic data. CoRR Marie Breeur, George Stepaniants, Pekka Keski-Rahkonen, Philippe Rigollet, Vivian Viallon
2023	J	`jnl`	Sparse Multi-Reference Alignment: Phase Retrieval, Uniform Uncertainty Principles and the Beltway Problem. Found. Comput. Math. Subhroshekhar Ghosh, Philippe Rigollet
2023	A*	`conf`	The emergence of clusters in self-attention dynamics. NeurIPS Borjan Geshkovski, Cyril Letrouit, Yury Polyanskiy, Philippe Rigollet
2023	J	`jnl`	The emergence of clusters in self-attention dynamics. CoRR Borjan Geshkovski, Cyril Letrouit, Yury Polyanskiy, Philippe Rigollet
2022	A*	`conf`	An Algorithmic Solution to the Blotto Game using Multi-marginal Couplings. EC Vianney Perchet, Philippe Rigollet, Thibaut Le Gouic
2022	J	`jnl`	An algorithmic solution to the Blotto game using multi-marginal couplings. CoRR Vianney Perchet, Philippe Rigollet, Thibaut Le Gouic
2022	A*	`conf`	GULP: a prediction-based metric between representations. NeurIPS Enric Boix-Adserà, Hannah Lawrence, George Stepaniants, Philippe Rigollet
2022	J	`jnl`	GULP: a prediction-based metric between representations. CoRR Enric Boix Adserà, Hannah Lawrence, George Stepaniants, Philippe Rigollet
2022	J	`jnl`	Gaussian discrepancy: A probabilistic relaxation of vector balancing. Discret. Appl. Math. Sinho Chewi, Patrik Gerber, Philippe Rigollet, Paxton Turner
2022	A	`conf`	Rejection sampling from shape-constrained distributions in sublinear time. AISTATS Sinho Chewi, Patrik R. Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet
2022	A*	`conf`	The query complexity of sampling from strongly log-concave distributions in one dimension. COLT Sinho Chewi, Patrik R. Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet
2022	A*	`conf`	Variational inference via Wasserstein gradient flows. NeurIPS Marc Lambert, Sinho Chewi, Francis R. Bach, Silvère Bonnabel, Philippe Rigollet
2022	J	`jnl`	Variational inference via Wasserstein gradient flows. CoRR Marc Lambert, Sinho Chewi, Francis R. Bach, Silvère Bonnabel, Philippe Rigollet
2021	A	`conf`	A Statistical Perspective on Coreset Density Estimation. AISTATS Paxton Turner, Jingbo Liu, Philippe Rigollet
2021	A	`conf`	Efficient Interpolation of Density Estimators. AISTATS Paxton Turner, Jingbo Liu, Philippe Rigollet
2021	A	`conf`	Fast and Smooth Interpolation on Wasserstein Space. AISTATS Sinho Chewi, Julien Clancy, Thibaut Le Gouic, Philippe Rigollet, George Stepaniants, Austin J. Stromme
2021	J	`jnl`	Gaussian Determinantal Processes: a new model for directionality in data. CoRR Subhro Ghosh, Philippe Rigollet
2021	J	`jnl`	Gaussian discrepancy: a probabilistic relaxation of vector balancing. CoRR Sinho Chewi, Patrik Gerber, Philippe Rigollet, Paxton Turner
2021	J	`jnl`	Multi-Reference Alignment for sparse signals, Uniform Uncertainty Principles and the Beltway Problem. CoRR Subhro Ghosh, Philippe Rigollet
2021	A*	`conf`	Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm. COLT Sinho Chewi, Chen Lu, Kwangjun Ahn, Xiang Cheng, Thibaut Le Gouic, Philippe Rigollet
2021	J	`jnl`	Rejection sampling from shape-constrained distributions in sublinear time. CoRR Sinho Chewi, Patrik Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet
2021	J	`jnl`	The query complexity of sampling from strongly log-concave distributions in one dimension. CoRR Sinho Chewi, Patrik Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet
2020	J	`jnl`	A Statistical Perspective on Coreset Density Estimation. CoRR Paxton Turner, Jingbo Liu, Philippe Rigollet
2020	A*	`conf`	Balancing Gaussian vectors in high dimension. COLT Paxton Turner, Raghu Meka, Philippe Rigollet
2020	J	`jnl`	Efficient Interpolation of Density Estimators. CoRR Paxton Turner, Jingbo Liu, Philippe Rigollet
2020	A	`conf`	Estimation Rates for Sparse Linear Cyclic Causal Models. UAI Jan-Christian Hütter, Philippe Rigollet
2020	A*	`conf`	Exponential ergodicity of mirror-Langevin diffusions. NeurIPS Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet, Austin J. Stromme
2020	J	`jnl`	Exponential ergodicity of mirror-Langevin diffusions. CoRR Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet, Austin J. Stromme
2020	A*	`conf`	Gradient descent algorithms for Bures-Wasserstein barycenters. COLT Sinho Chewi, Tyler Maunu, Philippe Rigollet, Austin J. Stromme
2020	J	`jnl`	Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm. CoRR Sinho Chewi, Chen Lu, Kwangjun Ahn, Xiang Cheng, Thibaut Le Gouic, Philippe Rigollet
2020	A*	`conf`	SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence. NeurIPS Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet
2020	J	`jnl`	SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence. CoRR Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet
2019	J	`jnl`	Balancing Gaussian vectors in high dimension. CoRR Raghu Meka, Philippe Rigollet, Paxton Turner
2019	J	`jnl`	Estimation of Monge Matrices. CoRR Jan-Christian Hütter, Cheng Mao, Philippe Rigollet, Elina Robeva
2019	A*	`conf`	Power analysis of knockoff filters for correlated designs. NeurIPS Jingbo Liu, Philippe Rigollet
2019	J	`jnl`	Power analysis of knockoff filters for correlated designs. CoRR Jingbo Liu, Philippe Rigollet
2019	A	`conf`	Statistical Optimal Transport via Factored Couplings. AISTATS Aden Forrow, Jan-Christian Hütter, Mor Nitzan, Philippe Rigollet, Geoffrey Schiebinger, Jonathan Weed
2019	J	`jnl`	The Sample Complexity of Multireference Alignment. SIAM J. Math. Data Sci. Amelia Perry, Jonathan Weed, Afonso S. Bandeira, Philippe Rigollet, Amit Singer
2018	A*	`ed.`	Conference On Learning Theory, COLT 2018, Stockholm, Sweden, 6-9 July 2018. COLT Sébastien Bubeck, Vianney Perchet, Philippe Rigollet
2018	A*	`conf`	Conference on Learning Theory 2018: Preface. COLT Sébastien Bubeck, Philippe Rigollet
2018	B	`conf`	Minimax Rates and Efficient Algorithms for Noisy Sorting. ALT Cheng Mao, Jonathan Weed, Philippe Rigollet
2018	J	`jnl`	Sparse Gaussian ICA. CoRR Nilin Abrahamsen, Philippe Rigollet
2018	J	`jnl`	Statistical Optimal Transport via Geodesic Hubs. CoRR Aden Forrow, Jan-Christian Hütter, Mor Nitzan, Geoffrey Schiebinger, Philippe Rigollet, Jonathan Weed
2018	A	`conf`	Teacher Improves Learning by Selecting a Training Subset. AISTATS Yuzhe Ma, Robert Nowak, Philippe Rigollet, Xuezhou Zhang, Xiaojin Zhu
2018	J	`jnl`	Teacher Improves Learning by Selecting a Training Subset. CoRR Yuzhe Ma, Robert Nowak, Philippe Rigollet, Xuezhou Zhang, Xiaojin Zhu
2017	A*	`conf`	Learning Determinantal Point Processes with Moments and Cycles. ICML John Urschel, Victor-Emmanuel Brunel, Ankur Moitra, Philippe Rigollet
2017	J	`jnl`	Minimax Rates and Efficient Algorithms for Noisy Sorting. CoRR Cheng Mao, Jonathan Weed, Philippe Rigollet
2017	—	`conf`	Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration. NIPS Jason M. Altschuler, Jonathan Weed, Philippe Rigollet
2017	J	`jnl`	Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration. CoRR Jason M. Altschuler, Jonathan Weed, Philippe Rigollet
2017	A*	`conf`	Rates of estimation for determinantal point processes. COLT Victor-Emmanuel Brunel, Ankur Moitra, Philippe Rigollet, John Urschel
2017	J	`jnl`	The sample complexity of multi-reference alignment. CoRR Amelia Perry, Jonathan Weed, Afonso S. Bandeira, Philippe Rigollet, Amit Singer
2016	J	`jnl`	Exact recovery in the Ising blockmodel. CoRR Quentin Berthet, Philippe Rigollet, Piyush Srivastava
2016	A*	`conf`	Online learning in repeated auctions. COLT Jonathan Weed, Vianney Perchet, Philippe Rigollet
2015	A*	`conf`	Batched Bandit Problems. COLT Vianney Perchet, Philippe Rigollet, Sylvain Chassang, Erik Snowberg
2015	J	`jnl`	Online learning in repeated auctions. CoRR Jonathan Weed, Vianney Perchet, Philippe Rigollet
2013	J	`jnl`	Aggregation of Affine Estimators. CoRR Dong Dai, Philippe Rigollet, Lucy Xia, Tong Zhang
2013	J	`jnl`	Bounded regret in stochastic multi-armed bandits CoRR Sébastien Bubeck, Vianney Perchet, Philippe Rigollet
2013	A*	`conf`	Bounded regret in stochastic multi-armed bandits. COLT Sébastien Bubeck, Vianney Perchet, Philippe Rigollet
2013	A*	`conf`	Complexity Theoretic Lower Bounds for Sparse Principal Component Detection. COLT Quentin Berthet, Philippe Rigollet
2013	J	`jnl`	Computational Lower Bounds for Sparse PCA CoRR Quentin Berthet, Philippe Rigollet
2012	J	`jnl`	Deviation Optimal Learning using Greedy Q-aggregation CoRR Dong Dai, Philippe Rigollet, Tong Zhang
2011	J	`jnl`	Neyman-Pearson Classification, Convexity and Stochastic Constraints. J. Mach. Learn. Res. Philippe Rigollet, Xin Tong
2011	A*	`conf`	Neyman-Pearson classification under a strict constraint. COLT Philippe Rigollet, Xin Tong
2011	J	`jnl`	Neyman-Pearson classification, convexity and stochastic constraints CoRR Philippe Rigollet, Xin Tong
2011	J	`jnl`	The multi-armed bandit problem with covariates CoRR Vianney Perchet, Philippe Rigollet
2010	A*	`conf`	Nonparametric Bandits with Covariates. COLT Philippe Rigollet, Assaf Zeevi
2007	J	`jnl`	Generalization Error Bounds in Semi-supervised Classification Under the Cluster Assumption. J. Mach. Learn. Res. Philippe Rigollet
2006	J	`jnl`	Generalization error bounds in semi-supervised classification under the cluster assumption CoRR Philippe Rigollet