Alina Beygelzimer

Publication Activity (10 Years)

Years Active: 1999-2023
Publications (10 Years): 16

Top Topics

Machine Learning

Linear Classification

Multi Armed Bandit Problems

Top Venues

Publications

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 (2023)
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 (2022)
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 (2021)
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 (2020)
Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
Contextual Memory Trees. ICML (2019)
Alina Beygelzimer, Dávid Pál, Balázs Szörényi, Devanathan Thiruvenkatachari, Chen-Yu Wei, Chicheng Zhang
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case. CoRR (2019)
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)
Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, Hanna M. Wallach
A Reductions Approach to Fair Classification. ICML (2018)
Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, Hanna M. Wallach
A Reductions Approach to Fair Classification. CoRR (2018)
Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
Contextual Memory Trees. CoRR (2018)
Alina Beygelzimer, Francesco Orabona, Chicheng Zhang
Efficient Online Bandit Multiclass Learning with $\tilde{O}(\sqrt{T})$ Regret. CoRR (2017)
Alina Beygelzimer, Francesco Orabona, Chicheng Zhang
Efficient Online Bandit Multiclass Learning with Õ(√T) Regret. ICML (2017)
Alina Beygelzimer, Daniel J. Hsu, John Langford, Chicheng Zhang
Search Improves Label for Active Learning. NIPS (2016)
Alina Beygelzimer, Satyen Kale, Haipeng Luo
Optimal and Adaptive Algorithms for Online Boosting. IJCAI (2016)
Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
Learning Reductions That Really Work. Proc. IEEE 104 (1) (2016)
Alina Beygelzimer, Daniel J. Hsu, John Langford, Chicheng Zhang
Search Improves Label for Active Learning. CoRR (2016)
Alina Beygelzimer, Elad Hazan, Satyen Kale, Haipeng Luo
Online Gradient Boosting. CoRR (2015)
Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
Learning Reductions that Really Work. CoRR (2015)
Alina Beygelzimer, Elad Hazan, Satyen Kale, Haipeng Luo
Online Gradient Boosting. NIPS (2015)
Alina Beygelzimer, Satyen Kale, Haipeng Luo
Optimal and Adaptive Algorithms for Online Boosting. ICML (2015)
Alina Beygelzimer, Satyen Kale, Haipeng Luo
Optimal and Adaptive Algorithms for Online Boosting. CoRR (2015)
Alekh Agarwal, Alina Beygelzimer, Daniel J. Hsu, John Langford, Matus Telgarsky
Scalable Nonlinear Learning with Adaptive Polynomial Expansions. CoRR (2014)
Alekh Agarwal, Alina Beygelzimer, Daniel J. Hsu, John Langford, Matus Telgarsky
Scalable Non-linear Learning with Adaptive Polynomial Expansions. NIPS (2014)
Alina Beygelzimer, John Langford, Yury Lifshits, Gregory B. Sorkin, Alexander L. Strehl
Conditional Probability Tree Estimation Analysis and Algorithms. CoRR (2014)
Alina Beygelzimer, Anton Riabov, Daby M. Sow, Deepak S. Turaga, Octavian Udrea
Big Data Exploration Via Automated Orchestration of Analytic Workflows. ICAC (2013)
Alina Beygelzimer, John Langford, David M. Pennock
Learning performance of prediction markets with Kelly bettors. AAMAS (2012)
Alina Beygelzimer, John Langford, David M. Pennock
Learning Performance of Prediction Markets with Kelly Bettors CoRR (2012)
Alice X. Zheng, Irina Rish, Alina Beygelzimer
Efficient Test Selection in Active Diagnosis via Entropy Approximation CoRR (2012)
Alina Beygelzimer, John Langford, Lihong Li, Lev Reyzin, Robert E. Schapire
Contextual Bandit Algorithms with Supervised Learning Guarantees. AISTATS (2011)
Alina Beygelzimer, John Langford, Lihong Li, Lev Reyzin, Robert E. Schapire
An Optimal High Probability Algorithm for the Contextual Bandit Problem CoRR (2010)
Alina Beygelzimer, Daniel J. Hsu, John Langford, Tong Zhang
Agnostic Active Learning Without Constraints CoRR (2010)
Alina Beygelzimer, Daniel J. Hsu, John Langford, Tong Zhang
Agnostic Active Learning Without Constraints. NIPS (2010)
Alina Beygelzimer, John Langford, Pradeep Ravikumar
Error-Correcting Tournaments. ALT (2009)
Alina Beygelzimer, John Langford, Yury Lifshits, Gregory B. Sorkin, Alexander L. Strehl
Conditional Probability Tree Estimation Analysis and Algorithms CoRR (2009)
Alina Beygelzimer, John Langford
The offset tree for learning with partial labels. KDD (2009)
Alina Beygelzimer, John Langford, Yury Lifshits, Gregory B. Sorkin, Alexander L. Strehl
Conditional Probability Tree Estimation Analysis and Algorithms. UAI (2009)
Alina Beygelzimer, John Langford, Bianca Zadrozny
Tutorial summary: Reductions in machine learning. ICML (2009)
Alina Beygelzimer, Sanjoy Dasgupta, John Langford
Importance weighted active learning. ICML (2009)
Maria-Florina Balcan, Alina Beygelzimer, John Langford
Agnostic active learning. J. Comput. Syst. Sci. 75 (1) (2009)
Alina Beygelzimer, John Langford, Pradeep Ravikumar
Error-Correcting Tournaments CoRR (2009)
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) (2008)
Mudhakar Srivatsa, Bong Jun Ko, Alina Beygelzimer, Venkateshwara Madduri
Scalable Topology Discovery and Link State Detection Using Routing Events. SRDS (2008)
Alina Beygelzimer, Sanjoy Dasgupta, John Langford
Importance Weighted Active Learning CoRR (2008)
Alina Beygelzimer, Aaron Kershenbaum, Kang-Won Lee, Vasileios Pappas
The benefits of directional antennas in heterogeneouswireless ad-hoc networks. MASS (2008)
Alina Beygelzimer, John Langford
The Offset Tree for Learning with Partial Labels CoRR (2008)
Maria-Florina Balcan, Nikhil Bansal, Alina Beygelzimer, Don Coppersmith, John Langford, Gregory B. Sorkin
Robust Reductions from Ranking to Classification. COLT (2007)
Alina Beygelzimer, Jeffrey O. Kephart, Irina Rish
Evaluation of Optimization Methods for Network Bottleneck Diagnosis. ICAC (2007)
Maria-Florina Balcan, Alina Beygelzimer, John Langford
Agnostic active learning. ICML (2006)
Alina Beygelzimer, Sham M. Kakade, John Langford
Cover trees for nearest neighbor. ICML (2006)
Alina Beygelzimer, Mitsunori Ogihara
The enumerability of P collapses P to NC. Theor. Comput. Sci. 345 (2-3) (2005)
Alina Beygelzimer, Mark Brodie, Sheng Ma, Irina Rish
Test-based diagnosis: tree and matrix representations. Integrated Network Management (2005)
Alina Beygelzimer, Emre Erdogan, Sheng Ma, Irina Rish
Statictical Models for Unequally Spaced Time Series. SDM (2005)
John Langford, Alina Beygelzimer
Sensitive Error Correcting Output Codes. COLT (2005)
Alina Beygelzimer, John Langford, Bianca Zadrozny
Weighted One-Against-All. AAAI (2005)
Alina Beygelzimer, Varsha Dani, Thomas P. Hayes, John Langford, Bianca Zadrozny
Error limiting reductions between classification tasks. ICML (2005)
Alice X. Zheng, Irina Rish, Alina Beygelzimer
Efficient Test Selection in Active Diagnosis via Entropy Approximation. UAI (2005)
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) (2005)
Alina Beygelzimer, Mitsunori Ogihara
The Enumerability of P Collapses P to NC. MFCS (2004)
Alina Beygelzimer, Varsha Dani, Thomas P. Hayes, John Langford
Reductions Between Classification Tasks Electron. Colloquium Comput. Complex. (077) (2004)
Alina Beygelzimer, Geoffrey Grinstein, Ralph Linsker, Irina Rish
Improving Network Robustness. ICAC (2004)
Alina Beygelzimer, Mitsunori Ogihara
The (Non)Enumerability of the Determinant and the Rank. Theory Comput. Syst. 36 (4) (2003)
Alina Beygelzimer, Irina Rish
Approximability of Probability Distributions. NIPS (2003)
Alina Beygelzimer, Irina Rish
Inference Complexity as a Model-Selection Criterion for Learning Bayesian Networks. KR (2002)
Alina Beygelzimer, Mitsunori Ogihara
On the Enumerability of the Determinant and the Rank Electron. Colloquium Comput. Complex. (016) (2002)
Alina Beygelzimer, Chang-Shing Perng, Sheng Ma
Fast ordering of large categorical datasets for visualization. Intell. Data Anal. 6 (4) (2002)
Alina Beygelzimer, Stanislaw P. Radziszowski
On halving line arrangements. Discret. Math. 257 (2-3) (2002)
Alina Beygelzimer, Mitsunori Ogihara
On the Enumerability of the Determinant and the Rank. IFIP TCS (2002)
Alina Beygelzimer, Chang-Shing Perng, Sheng Ma
Fast ordering of large categorical datasets for better visualization. KDD (2001)
Alina Beygelzimer, Lane A. Hemaspaandra, Christopher M. Homan, Jörg Rothe
One-Way Functions in Worst-Case Cryptography: Algebraic and Security Properties CoRR (1999)
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) (1999)