default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDJonathan Weed
Person information
- affiliation: New York University, Courant Institute of Mathematical Sciences and Center for Data Science, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[j9]Natalie S. Frank, Jonathan Niles-Weed:
Existence and Minimax Theorems for Adversarial Surrogate Risks in Binary Classification. J. Mach. Learn. Res. 25: 58:1-58:41 (2024)- [i34]Parnian Kassraie, Aram-Alexandre Pooladian, Michal Klein, James Thornton, Jonathan Niles-Weed, Marco Cuturi:
Progressive Entropic Optimal Transport Solvers. CoRR abs/2406.05061 (2024) - [i33]Yanjun Han, Jonathan Niles-Weed:
Approximate independence of permutation mixtures. CoRR abs/2408.09341 (2024) - [i32]Aram-Alexandre Pooladian, Jonathan Niles-Weed:
Plug-in estimation of Schrödinger bridges. CoRR abs/2408.11686 (2024) - [i31]Yifan Chen, Xiaoou Cheng, Jonathan Niles-Weed, Jonathan Weare:
Convergence of Unadjusted Langevin in High Dimensions: Delocalization of Bias. CoRR abs/2408.13115 (2024) - [i30]Xin Bing, Florentina Bunea, Jonathan Niles-Weed, Marten H. Wegkamp:
Learning large softmax mixtures with warm start EM. CoRR abs/2409.09903 (2024) - 2023
- [j8]Eustasio del Barrio, Alberto González-Sanz
, Jean-Michel Loubes, Jonathan Niles-Weed:
An Improved Central Limit Theorem and Fast Convergence Rates for Entropic Transportation Costs. SIAM J. Math. Data Sci. 5(3): 639-669 (2023) - [j7]Jonathan Niles-Weed, Ilias Zadik:
It Was "All" for "Nothing": Sharp Phase Transitions for Noiseless Discrete Channels. IEEE Trans. Inf. Theory 69(8): 5188-5202 (2023) - [c24]Shuyu Liu, Florentina Bunea, Jonathan Niles-Weed:
Asymptotic confidence sets for random linear programs. COLT 2023: 3919-3940 - [c23]Elchanan Mossel, Jonathan Niles-Weed, Youngtak Sohn, Nike Sun, Ilias Zadik:
Sharp thresholds in inference of planted subgraphs. COLT 2023: 5573-5577 - [c22]Aram-Alexandre Pooladian, Vincent Divol, Jonathan Niles-Weed:
Minimax estimation of discontinuous optimal transport maps: The semi-discrete case. ICML 2023: 28128-28150 - [c21]Tom Tirer, Haoxiang Huang, Jonathan Niles-Weed:
Perturbation Analysis of Neural Collapse. ICML 2023: 34301-34329 - [c20]Natalie Frank, Jonathan Niles-Weed:
The Adversarial Consistency of Surrogate Risks for Binary Classification. NeurIPS 2023 - [i29]Elchanan Mossel, Jonathan Niles-Weed, Youngtak Sohn, Nike Sun, Ilias Zadik:
Sharp thresholds in inference of planted subgraphs. CoRR abs/2302.14830 (2023) - [i28]Natalie Frank, Jonathan Niles-Weed:
The Adversarial Consistency of Surrogate Risks for Binary Classification. CoRR abs/2305.09956 (2023) - [i27]Michal Klein, Aram-Alexandre Pooladian, Pierre Ablin, Eugène Ndiaye, Jonathan Niles-Weed, Marco Cuturi:
Learning Costs for Structured Monge Displacements. CoRR abs/2306.11895 (2023) - 2022
- [j6]De Huang, Jonathan Niles-Weed, Joel A. Tropp, Rachel A. Ward:
Matrix Concentration for Products. Found. Comput. Math. 22(6): 1767-1799 (2022) - [j5]Dylan J. Altschuler, Jonathan Niles-Weed:
The discrepancy of random rectangular matrices. Random Struct. Algorithms 60(4): 551-593 (2022) - [j4]Jason M. Altschuler, Jonathan Niles-Weed, Austin J. Stromme:
Asymptotics for Semidiscrete Entropic Optimal Transport. SIAM J. Math. Anal. 54(2): 1718-1741 (2022) - [c19]Sheng Liu, Aakash Kaku, Weicheng Zhu, Matan Leibovich, Sreyas Mohan, Boyang Yu, Haoxiang Huang, Laure Zanna, Narges Razavian, Jonathan Niles-Weed, Carlos Fernandez-Granda:
Deep Probability Estimation. ICML 2022: 13746-13781 - [c18]Aram-Alexandre Pooladian, Marco Cuturi, Jonathan Niles-Weed:
Debiaser Beware: Pitfalls of Centering Regularized Transport Maps. ICML 2022: 17830-17847 - [c17]Yunzi Ding, Jonathan Niles-Weed:
Asymptotics of smoothed Wasserstein distances in the small noise regime. NeurIPS 2022 - [c16]Jiaqi Xi, Jonathan Niles-Weed:
Distributional Convergence of the Sliced Wasserstein Process. NeurIPS 2022 - [c15]Dmitriy Kunisky, Jonathan Niles-Weed:
Strong recovery of geometric planted matchings. SODA 2022: 834-876 - [i26]Eustasio del Barrio, Alberto González-Sanz, Jean-Michel Loubes, Jonathan Niles-Weed:
An improved central limit theorem and fast convergence rates for entropic transportation costs. CoRR abs/2204.09105 (2022) - [i25]Elchanan Mossel, Jonathan Niles-Weed, Nike Sun, Ilias Zadik:
On the Second Kahn-Kalai Conjecture. CoRR abs/2209.03326 (2022) - [i24]Elchanan Mossel, Jonathan Niles-Weed, Nike Sun, Ilias Zadik:
A second moment proof of the spread lemma. CoRR abs/2209.11347 (2022) - [i23]Tom Tirer, Haoxiang Huang, Jonathan Niles-Weed:
Perturbation Analysis of Neural Collapse. CoRR abs/2210.16658 (2022) - 2021
- [c14]De Huang, Jonathan Niles-Weed, Rachel A. Ward:
Streaming k-PCA: Efficient guarantees for Oja's algorithm, beyond rank-one updates. COLT 2021: 2463-2498 - [c13]Jonathan Niles-Weed, Ilias Zadik:
It was "all" for "nothing": sharp phase transitions for noiseless discrete channels. COLT 2021: 3546-3547 - [i22]Dylan J. Altschuler, Jonathan Niles-Weed:
The Discrepancy of Random Rectangular Matrices. CoRR abs/2101.04036 (2021) - [i21]De Huang, Jonathan Niles-Weed, Rachel A. Ward:
Streaming k-PCA: Efficient guarantees for Oja's algorithm, beyond rank-one updates. CoRR abs/2102.03646 (2021) - [i20]Jonathan Niles-Weed, Ilias Zadik:
It was "all" for "nothing": sharp phase transitions for noiseless discrete channels. CoRR abs/2102.12422 (2021) - [i19]Dmitriy Kunisky, Jonathan Niles-Weed:
Strong recovery of geometric planted matchings. CoRR abs/2107.05567 (2021) - 2020
- [j3]Ziv Goldfeld, Kristjan H. Greenewald, Jonathan Niles-Weed, Yury Polyanskiy:
Convergence of Smoothed Empirical Measures With Applications to Entropy Estimation. IEEE Trans. Inf. Theory 66(7): 4368-4391 (2020) - [c12]Marco Cuturi, Olivier Teboul, Jonathan Niles-Weed, Jean-Philippe Vert:
Supervised Quantile Normalization for Low Rank Matrix Factorization. ICML 2020: 2269-2279 - [c11]Sheng Liu, Jonathan Niles-Weed, Narges Razavian, Carlos Fernandez-Granda:
Early-Learning Regularization Prevents Memorization of Noisy Labels. NeurIPS 2020 - [c10]Jonathan Niles-Weed, Ilias Zadik:
The All-or-Nothing Phenomenon in Sparse Tensor PCA. NeurIPS 2020 - [i18]Marco Cuturi, Olivier Teboul, Jonathan Niles-Weed, Jean-Philippe Vert:
Supervised Quantile Normalization for Low-rank Matrix Approximation. CoRR abs/2002.03229 (2020) - [i17]Gonzalo E. Mena, Amin Nejatbakhsh, Erdem Varol, Jonathan Niles-Weed:
Sinkhorn EM: An Expectation-Maximization algorithm based on entropic optimal transport. CoRR abs/2006.16548 (2020) - [i16]Sheng Liu, Jonathan Niles-Weed, Narges Razavian, Carlos Fernandez-Granda:
Early-Learning Regularization Prevents Memorization of Noisy Labels. CoRR abs/2007.00151 (2020) - [i15]Jonathan Niles-Weed, Ilias Zadik:
The All-or-Nothing Phenomenon in Sparse Tensor PCA. CoRR abs/2007.11138 (2020)
2010 – 2019
- 2019
- [j2]Amelia Perry, Jonathan Weed, Afonso S. Bandeira, Philippe Rigollet, Amit Singer:
The Sample Complexity of Multireference Alignment. SIAM J. Math. Data Sci. 1(3): 497-517 (2019) - [c9]Aden Forrow, Jan-Christian Hütter, Mor Nitzan, Philippe Rigollet, Geoffrey Schiebinger, Jonathan Weed:
Statistical Optimal Transport via Factored Couplings. AISTATS 2019: 2454-2465 - [c8]Jonathan Weed, Quentin Berthet:
Estimation of smooth densities in Wasserstein distance. COLT 2019: 3118-3119 - [c7]Ziv Goldfeld, Kristjan H. Greenewald, Jonathan Weed, Yury Polyanskiy:
Optimality of the Plug-in Estimator for Differential Entropy Estimation under Gaussian Convolutions. ISIT 2019: 892-896 - [c6]Jason M. Altschuler, Francis R. Bach, Alessandro Rudi, Jonathan Niles-Weed:
Massively scalable Sinkhorn distances via the Nyström method. NeurIPS 2019: 4429-4439 - [c5]Gonzalo Mena, Jonathan Niles-Weed:
Statistical bounds for entropic optimal transport: sample complexity and the central limit theorem. NeurIPS 2019: 4543-4553 - [i14]Gonzalo Mena, Jonathan Weed:
Statistical bounds for entropic optimal transport: sample complexity and the central limit theorem. CoRR abs/1905.11882 (2019) - [i13]Ziv Goldfeld, Kristjan H. Greenewald, Yury Polyanskiy, Jonathan Weed:
Convergence of Smoothed Empirical Measures with Applications to Entropy Estimation. CoRR abs/1905.13576 (2019) - 2018
- [j1]Jonathan Weed:
Approximately Certifying the Restricted Isometry Property is Hard. IEEE Trans. Inf. Theory 64(8): 5488-5497 (2018) - [c4]Cheng Mao, Jonathan Weed, Philippe Rigollet:
Minimax Rates and Efficient Algorithms for Noisy Sorting. ALT 2018: 821-847 - [c3]Jonathan Weed:
An explicit analysis of the entropic penalty in linear programming. COLT 2018: 1841-1855 - [i12]Jonathan Weed:
An explicit analysis of the entropic penalty in linear programming. CoRR abs/1806.01879 (2018) - [i11]Aden Forrow, Jan-Christian Hütter, Mor Nitzan, Geoffrey Schiebinger, Philippe Rigollet, Jonathan Weed:
Statistical Optimal Transport via Geodesic Hubs. CoRR abs/1806.07348 (2018) - [i10]Jason M. Altschuler, Francis R. Bach, Alessandro Rudi, Jonathan Weed:
Approximating the Quadratic Transportation Metric in Near-Linear Time. CoRR abs/1810.10046 (2018) - [i9]Jason M. Altschuler, Francis R. Bach, Alessandro Rudi, Jonathan Weed:
Massively scalable Sinkhorn distances via the Nyström method. CoRR abs/1812.05189 (2018) - 2017
- [c2]Jason M. Altschuler, Jonathan Weed, Philippe Rigollet:
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration. NIPS 2017: 1964-1974 - [i8]Jonathan Weed:
Approximately certifying the restricted isometry property is hard. CoRR abs/1704.00468 (2017) - [i7]Jason M. Altschuler, Jonathan Weed, Philippe Rigollet:
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration. CoRR abs/1705.09634 (2017) - [i6]Amelia Perry, Jonathan Weed, Afonso S. Bandeira, Philippe Rigollet, Amit Singer:
The sample complexity of multi-reference alignment. CoRR abs/1707.00943 (2017) - [i5]Cheng Mao, Jonathan Weed, Philippe Rigollet:
Minimax Rates and Efficient Algorithms for Noisy Sorting. CoRR abs/1710.10388 (2017) - [i4]Afonso S. Bandeira, Ben Blum-Smith, Amelia Perry, Jonathan Weed, Alexander S. Wein:
Estimation under group actions: recovering orbits from invariants. CoRR abs/1712.10163 (2017) - 2016
- [c1]Jonathan Weed, Vianney Perchet, Philippe Rigollet:
Online learning in repeated auctions. COLT 2016: 1562-1583 - [i3]Mehtaab Sawhney, Jonathan Weed:
Further results on arc and bar k-visibility graphs. CoRR abs/1601.01231 (2016) - 2015
- [i2]Jonathan Weed:
Multinational War is Hard. CoRR abs/1503.00141 (2015) - [i1]Jonathan Weed, Vianney Perchet, Philippe Rigollet:
Online learning in repeated auctions. CoRR abs/1511.05720 (2015)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-22 21:17 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
