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Alina Beygelzimer
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- affiliation: Yahoo! Research, USA
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2020 – today
- 2023
- [i24]Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan:
Has the Machine Learning Review Process Become More Arbitrary as the Field Has Grown? The NeurIPS 2021 Consistency Experiment. CoRR abs/2306.03262 (2023) - 2022
- [i23]Charvi Rastogi, Ivan Stelmakh, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, Zhenyu Xue, Hal Daumé III, Emma Pierson, Nihar B. Shah:
How do Authors' Perceptions of their Papers Compare with Co-authors' Perceptions and Peer-review Decisions? CoRR abs/2211.12966 (2022) - 2021
- [j10]Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Hugo Larochelle:
Improving Reproducibility in Machine Learning Research(A Report from the NeurIPS 2019 Reproducibility Program). J. Mach. Learn. Res. 22: 164:1-164:20 (2021) - [e3]Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan:
Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual. 2021 [contents] - 2020
- [i22]Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Hugo Larochelle:
Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program). CoRR abs/2003.12206 (2020)
2010 – 2019
- 2019
- [c36]Alina Beygelzimer, Dávid Pál, Balázs Szörényi, Devanathan Thiruvenkatachari, Chen-Yu Wei, Chicheng Zhang:
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case. ICML 2019: 624-633 - [c35]Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro:
Contextual Memory Trees. ICML 2019: 6026-6035 - [e2]Alina Beygelzimer, Daniel Hsu:
Conference on Learning Theory, COLT 2019, 25-28 June 2019, Phoenix, AZ, USA. Proceedings of Machine Learning Research 99, PMLR 2019 [contents] - [e1]Hanna M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Roman Garnett:
Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada. 2019 [contents] - [i21]Alina Beygelzimer, Dávid Pál, Balázs Szörényi, Devanathan Thiruvenkatachari, Chen-Yu Wei, Chicheng Zhang:
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case. CoRR abs/1902.02244 (2019) - 2018
- [c34]Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, Hanna M. Wallach:
A Reductions Approach to Fair Classification. ICML 2018: 60-69 - [i20]Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, Hanna M. Wallach:
A Reductions Approach to Fair Classification. CoRR abs/1803.02453 (2018) - [i19]Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro:
Contextual Memory Trees. CoRR abs/1807.06473 (2018) - 2017
- [c33]Alina Beygelzimer, Francesco Orabona, Chicheng Zhang:
Efficient Online Bandit Multiclass Learning with Õ(√T) Regret. ICML 2017: 488-497 - [i18]Alina Beygelzimer, Francesco Orabona, Chicheng Zhang:
Efficient Online Bandit Multiclass Learning with $\tilde{O}(\sqrt{T})$ Regret. CoRR abs/1702.07958 (2017) - 2016
- [j9]Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro:
Learning Reductions That Really Work. Proc. IEEE 104(1): 136-147 (2016) - [c32]Alina Beygelzimer, Satyen Kale, Haipeng Luo:
Optimal and Adaptive Algorithms for Online Boosting. IJCAI 2016: 4120-4124 - [c31]Alina Beygelzimer, Daniel J. Hsu, John Langford, Chicheng Zhang:
Search Improves Label for Active Learning. NIPS 2016: 3342-3350 - [i17]Alina Beygelzimer, Daniel J. Hsu, John Langford, Chicheng Zhang:
Search Improves Label for Active Learning. CoRR abs/1602.07265 (2016) - 2015
- [c30]Alina Beygelzimer, Satyen Kale, Haipeng Luo:
Optimal and Adaptive Algorithms for Online Boosting. ICML 2015: 2323-2331 - [c29]Alina Beygelzimer, Elad Hazan, Satyen Kale, Haipeng Luo:
Online Gradient Boosting. NIPS 2015: 2458-2466 - [i16]Alina Beygelzimer, Satyen Kale, Haipeng Luo:
Optimal and Adaptive Algorithms for Online Boosting. CoRR abs/1502.02651 (2015) - [i15]Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro:
Learning Reductions that Really Work. CoRR abs/1502.02704 (2015) - [i14]Alina Beygelzimer, Elad Hazan, Satyen Kale, Haipeng Luo:
Online Gradient Boosting. CoRR abs/1506.04820 (2015) - 2014
- [c28]Alekh Agarwal, Alina Beygelzimer, Daniel J. Hsu, John Langford, Matus Telgarsky:
Scalable Non-linear Learning with Adaptive Polynomial Expansions. NIPS 2014: 2051-2059 - [i13]Alina Beygelzimer, John Langford, Yury Lifshits, Gregory B. Sorkin, Alexander L. Strehl:
Conditional Probability Tree Estimation Analysis and Algorithms. CoRR abs/1408.2031 (2014) - [i12]Alekh Agarwal, Alina Beygelzimer, Daniel J. Hsu, John Langford, Matus Telgarsky:
Scalable Nonlinear Learning with Adaptive Polynomial Expansions. CoRR abs/1410.0440 (2014) - 2013
- [c27]Alina Beygelzimer, Anton Riabov, Daby M. Sow, Deepak S. Turaga, Octavian Udrea:
Big Data Exploration Via Automated Orchestration of Analytic Workflows. ICAC 2013: 153-158 - 2012
- [c26]Alina Beygelzimer, John Langford, David M. Pennock:
Learning performance of prediction markets with Kelly bettors. AAMAS 2012: 1317-1318 - [i11]Alina Beygelzimer, John Langford, David M. Pennock:
Learning Performance of Prediction Markets with Kelly Bettors. CoRR abs/1201.6655 (2012) - [i10]Alice X. Zheng, Irina Rish, Alina Beygelzimer:
Efficient Test Selection in Active Diagnosis via Entropy Approximation. CoRR abs/1207.1418 (2012) - 2011
- [c25]Alina Beygelzimer, John Langford, Lihong Li, Lev Reyzin, Robert E. Schapire:
Contextual Bandit Algorithms with Supervised Learning Guarantees. AISTATS 2011: 19-26 - 2010
- [c24]Alina Beygelzimer, Daniel J. Hsu, John Langford, Tong Zhang:
Agnostic Active Learning Without Constraints. NIPS 2010: 199-207 - [i9]Alina Beygelzimer, John Langford, Lihong Li, Lev Reyzin, Robert E. Schapire:
An Optimal High Probability Algorithm for the Contextual Bandit Problem. CoRR abs/1002.4058 (2010) - [i8]Alina Beygelzimer, Daniel J. Hsu, John Langford, Tong Zhang:
Agnostic Active Learning Without Constraints. CoRR abs/1006.2588 (2010)
2000 – 2009
- 2009
- [j8]Maria-Florina Balcan, Alina Beygelzimer, John Langford:
Agnostic active learning. J. Comput. Syst. Sci. 75(1): 78-89 (2009) - [c23]Alina Beygelzimer, John Langford, Pradeep Ravikumar:
Error-Correcting Tournaments. ALT 2009: 247-262 - [c22]Alina Beygelzimer, John Langford, Bianca Zadrozny:
Tutorial summary: Reductions in machine learning. ICML 2009: 12 - [c21]Alina Beygelzimer, Sanjoy Dasgupta, John Langford:
Importance weighted active learning. ICML 2009: 49-56 - [c20]Alina Beygelzimer, John Langford:
The offset tree for learning with partial labels. KDD 2009: 129-138 - [c19]Alina Beygelzimer, John Langford, Yury Lifshits, Gregory B. Sorkin, Alexander L. Strehl:
Conditional Probability Tree Estimation Analysis and Algorithms. UAI 2009: 51-58 - [i7]Alina Beygelzimer, John Langford, Pradeep Ravikumar:
Error-Correcting Tournaments. CoRR abs/0902.3176 (2009) - [i6]Alina Beygelzimer, John Langford, Yury Lifshits, Gregory B. Sorkin, Alexander L. Strehl:
Conditional Probability Tree Estimation Analysis and Algorithms. CoRR abs/0903.4217 (2009) - 2008
- [j7]Maria-Florina Balcan, Nikhil Bansal, Alina Beygelzimer, Don Coppersmith, John Langford, Gregory B. Sorkin:
Robust reductions from ranking to classification. Mach. Learn. 72(1-2): 139-153 (2008) - [c18]Alina Beygelzimer, Aaron Kershenbaum, Kang-Won Lee, Vasileios Pappas:
The benefits of directional antennas in heterogeneouswireless ad-hoc networks. MASS 2008: 442-449 - [c17]Mudhakar Srivatsa, Bong Jun Ko, Alina Beygelzimer, Venkateshwara Madduri:
Scalable Topology Discovery and Link State Detection Using Routing Events. SRDS 2008: 165-174 - [i5]Alina Beygelzimer, John Langford:
The Offset Tree for Learning with Partial Labels. CoRR abs/0812.4044 (2008) - [i4]Alina Beygelzimer, Sanjoy Dasgupta, John Langford:
Importance Weighted Active Learning. CoRR abs/0812.4952 (2008) - 2007
- [c16]Maria-Florina Balcan, Nikhil Bansal, Alina Beygelzimer, Don Coppersmith, John Langford, Gregory B. Sorkin:
Robust Reductions from Ranking to Classification. COLT 2007: 604-619 - [c15]Alina Beygelzimer, Jeffrey O. Kephart, Irina Rish:
Evaluation of Optimization Methods for Network Bottleneck Diagnosis. ICAC 2007: 20 - 2006
- [c14]Maria-Florina Balcan, Alina Beygelzimer, John Langford:
Agnostic active learning. ICML 2006: 65-72 - [c13]Alina Beygelzimer, Sham M. Kakade, John Langford:
Cover trees for nearest neighbor. ICML 2006: 97-104 - 2005
- [j6]Alina Beygelzimer, Mitsunori Ogihara:
The enumerability of P collapses P to NC. Theor. Comput. Sci. 345(2-3): 248-259 (2005) - [j5]Irina Rish, Mark Brodie, Sheng Ma, Natalia Odintsova, Alina Beygelzimer, Genady Grabarnik, Karina Hernandez:
Adaptive diagnosis in distributed systems. IEEE Trans. Neural Networks 16(5): 1088-1109 (2005) - [c12]Alina Beygelzimer, John Langford, Bianca Zadrozny:
Weighted One-Against-All. AAAI 2005: 720-725 - [c11]John Langford, Alina Beygelzimer:
Sensitive Error Correcting Output Codes. COLT 2005: 158-172 - [c10]Alina Beygelzimer, Varsha Dani, Thomas P. Hayes, John Langford, Bianca Zadrozny:
Error limiting reductions between classification tasks. ICML 2005: 49-56 - [c9]Alina Beygelzimer, Mark Brodie, Sheng Ma, Irina Rish:
Test-based diagnosis: tree and matrix representations. Integrated Network Management 2005: 529-542 - [c8]Alina Beygelzimer, Emre Erdogan, Sheng Ma, Irina Rish:
Statictical Models for Unequally Spaced Time Series. SDM 2005: 626-630 - [c7]Alice X. Zheng, Irina Rish, Alina Beygelzimer:
Efficient Test Selection in Active Diagnosis via Entropy Approximation. UAI 2005: 675- - 2004
- [c6]Alina Beygelzimer, Geoffrey Grinstein, Ralph Linsker, Irina Rish:
Improving Network Robustness. ICAC 2004: 322-323 - [c5]Alina Beygelzimer, Mitsunori Ogihara:
The Enumerability of P Collapses P to NC. MFCS 2004: 346-355 - [i3]Alina Beygelzimer, Varsha Dani, Thomas P. Hayes, John Langford:
Reductions Between Classification Tasks. Electron. Colloquium Comput. Complex. TR04 (2004) - 2003
- [j4]Alina Beygelzimer, Mitsunori Ogihara:
The (Non)Enumerability of the Determinant and the Rank. Theory Comput. Syst. 36(4): 359-374 (2003) - [c4]Alina Beygelzimer, Irina Rish:
Approximability of Probability Distributions. NIPS 2003: 377-384 - 2002
- [j3]Alina Beygelzimer, Stanislaw P. Radziszowski:
On halving line arrangements. Discret. Math. 257(2-3): 267-283 (2002) - [j2]Alina Beygelzimer, Chang-Shing Perng, Sheng Ma:
Fast ordering of large categorical datasets for visualization. Intell. Data Anal. 6(4): 379-395 (2002) - [c3]Alina Beygelzimer, Mitsunori Ogihara:
On the Enumerability of the Determinant and the Rank. IFIP TCS 2002: 59-70 - [c2]Alina Beygelzimer, Irina Rish:
Inference Complexity as a Model-Selection Criterion for Learning Bayesian Networks. KR 2002: 558-567 - [i2]Alina Beygelzimer, Mitsunori Ogihara:
On the Enumerability of the Determinant and the Rank. Electron. Colloquium Comput. Complex. TR02 (2002) - 2001
- [c1]Alina Beygelzimer, Chang-Shing Perng, Sheng Ma:
Fast ordering of large categorical datasets for better visualization. KDD 2001: 239-244
1990 – 1999
- 1999
- [j1]Alina Beygelzimer, Lane A. Hemaspaandra, Christopher M. Homan, Jörg Rothe:
One-way functions in worst-case cryptography: algebraic and security properties are on the house. SIGACT News 30(4): 25-40 (1999) - [i1]Alina Beygelzimer, Lane A. Hemaspaandra, Christopher M. Homan, Jörg Rothe:
One-Way Functions in Worst-Case Cryptography: Algebraic and Security Properties. CoRR cs.CC/9911007 (1999)
Coauthor Index
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