One-Way Functions in Worst-Case Cryptography: Algebraic and Security Properties - Alina Beygelzimer; Lane A. Hemaspaandra; Christopher M. Homan; Jörg Rothe (CoRR, 1999)

One-way functions in worst-case cryptography: algebraic and security properties are on the house. - Alina Beygelzimer; Lane A. Hemaspaandra; Christopher M. Homan; Jörg Rothe (SIGACT News, 1999)

Fast ordering of large categorical datasets for better visualization. - Alina Beygelzimer; Chang-Shing Perng; Sheng Ma (KDD, 2001)

Inference Complexity as a Model-Selection Criterion for Learning Bayesian Networks. - Alina Beygelzimer; Irina Rish (KR, 2002)

On halving line arrangements. - Alina Beygelzimer; Stanislaw P. Radziszowski (Discret. Math., 2002)

On the Enumerability of the Determinant and the Rank - Alina Beygelzimer; Mitsunori Ogihara (Electron. Colloquium Comput. Complex., 2002)

Fast ordering of large categorical datasets for visualization. - Alina Beygelzimer; Chang-Shing Perng; Sheng Ma (Intell. Data Anal., 2002)

Approximability of Probability Distributions. - Alina Beygelzimer; Irina Rish (NIPS, 2003)

The (Non)Enumerability of the Determinant and the Rank. - Alina Beygelzimer; Mitsunori Ogihara (Theory Comput. Syst., 2003)

Improving Network Robustness. - Alina Beygelzimer; Geoffrey Grinstein; Ralph Linsker; Irina Rish (ICAC, 2004)

Reductions Between Classification Tasks - Alina Beygelzimer; Varsha Dani; Thomas P. Hayes; John Langford 001 (Electron. Colloquium Comput. Complex., 2004)

Weighted One-Against-All. - Alina Beygelzimer; John Langford 001; Bianca Zadrozny (AAAI, 2005)

Sensitive Error Correcting Output Codes. - John Langford 001; Alina Beygelzimer (COLT, 2005)

Error limiting reductions between classification tasks. - Alina Beygelzimer; Varsha Dani; Thomas P. Hayes; John Langford 001; Bianca Zadrozny (ICML, 2005)

Test-based diagnosis: tree and matrix representations. - Alina Beygelzimer; Mark Brodie; Sheng Ma; Irina Rish (Integrated Network Management, 2005)

Statictical Models for Unequally Spaced Time Series. - Alina Beygelzimer; Emre Erdogan; Sheng Ma; Irina Rish (SDM, 2005)

Efficient Test Selection in Active Diagnosis via Entropy Approximation. - Alice X. Zheng; Irina Rish; Alina Beygelzimer (UAI, 2005)

The enumerability of P collapses P to NC. - Alina Beygelzimer; Mitsunori Ogihara (Theor. Comput. Sci., 2005)

Adaptive diagnosis in distributed systems. - Irina Rish; Mark Brodie; Sheng Ma; Natalia Odintsova; Alina Beygelzimer; Genady Grabarnik; Karina Hernandez (IEEE Trans. Neural Networks, 2005)

Cover trees for nearest neighbor. - Alina Beygelzimer; Sham M. Kakade; John Langford 001 (ICML, 2006)

Evaluation of Optimization Methods for Network Bottleneck Diagnosis. - Alina Beygelzimer; Jeffrey O. Kephart; Irina Rish (ICAC, 2007)

The benefits of directional antennas in heterogeneouswireless ad-hoc networks. - Alina Beygelzimer; Aaron Kershenbaum; Kang-Won Lee; Vasileios Pappas (MASS, 2008)

Scalable Topology Discovery and Link State Detection Using Routing Events. - Mudhakar Srivatsa; Bong Jun Ko; Alina Beygelzimer; Venkateshwara Madduri (SRDS, 2008)

Robust reductions from ranking to classification. - Maria-Florina Balcan; Nikhil Bansal 001; Alina Beygelzimer; Don Coppersmith; John Langford 001; Gregory B. Sorkin (Mach. Learn., 2008)

Error-Correcting Tournaments. - Alina Beygelzimer; John Langford 001; Pradeep Ravikumar (ALT, 2009)

Importance weighted active learning. - Alina Beygelzimer; Sanjoy Dasgupta; John Langford 001 (ICML, 2009)

Tutorial summary: Reductions in machine learning. - Alina Beygelzimer; John Langford 001; Bianca Zadrozny (ICML, 2009)

The offset tree for learning with partial labels. - Alina Beygelzimer; John Langford 001 (KDD, 2009)

Conditional Probability Tree Estimation Analysis and Algorithms. - Alina Beygelzimer; John Langford 001; Yury Lifshits; Gregory B. Sorkin; Alexander L. Strehl (UAI, 2009)

Agnostic active learning. - Maria-Florina Balcan; Alina Beygelzimer; John Langford 001 (J. Comput. Syst. Sci., 2009)

Agnostic Active Learning Without Constraints. - Alina Beygelzimer; Daniel J. Hsu; John Langford 001; Tong Zhang 001 (NIPS, 2010)

An Optimal High Probability Algorithm for the Contextual Bandit Problem - Alina Beygelzimer; John Langford 001; Lihong Li 001; Lev Reyzin; Robert E. Schapire (CoRR, 2010)

Contextual Bandit Algorithms with Supervised Learning Guarantees. - Alina Beygelzimer; John Langford 001; Lihong Li 001; Lev Reyzin; Robert E. Schapire (AISTATS, 2011)

Learning performance of prediction markets with Kelly bettors. - Alina Beygelzimer; John Langford 001; David M. Pennock (AAMAS, 2012)

Big Data Exploration Via Automated Orchestration of Analytic Workflows. - Alina Beygelzimer; Anton Riabov; Daby M. Sow; Deepak S. Turaga; Octavian Udrea (ICAC, 2013)

Scalable Non-linear Learning with Adaptive Polynomial Expansions. - Alekh Agarwal; Alina Beygelzimer; Daniel J. Hsu; John Langford 001; Matus Telgarsky (NIPS, 2014)

Scalable Nonlinear Learning with Adaptive Polynomial Expansions. - Alekh Agarwal; Alina Beygelzimer; Daniel J. Hsu; John Langford 001; Matus Telgarsky (CoRR, 2014)

Optimal and Adaptive Algorithms for Online Boosting. - Alina Beygelzimer; Satyen Kale; Haipeng Luo (ICML, 2015)

Online Gradient Boosting. - Alina Beygelzimer; Elad Hazan; Satyen Kale; Haipeng Luo (NIPS, 2015)

Search Improves Label for Active Learning. - Alina Beygelzimer; Daniel J. Hsu; John Langford 001; Chicheng Zhang (NIPS, 2016)

Learning Reductions That Really Work. - Alina Beygelzimer; Hal Daumé III; John Langford 001; Paul Mineiro (Proc. IEEE, 2016)

Efficient Online Bandit Multiclass Learning with Õ(√T) Regret. - Alina Beygelzimer; Francesco Orabona; Chicheng Zhang (ICML, 2017)

Efficient Online Bandit Multiclass Learning with $ tilde{O}( sqrt{T})$ Regret. - Alina Beygelzimer; Francesco Orabona; Chicheng Zhang (CoRR, 2017)

A Reductions Approach to Fair Classification. - Alekh Agarwal; Alina Beygelzimer; Miroslav Dudík; John Langford 001; Hanna M. Wallach (ICML, 2018)

Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case. - Alina Beygelzimer; Dávid Pál; Balázs Szörényi; Devanathan Thiruvenkatachari; Chen-Yu Wei; Chicheng Zhang (ICML, 2019)

Contextual Memory Trees. - Wen Sun 002; Alina Beygelzimer; Hal Daumé III; John Langford 001; Paul Mineiro (ICML, 2019)

Improving Reproducibility in Machine Learning Research(A Report from the NeurIPS 2019 Reproducibility Program). - Joelle Pineau; Philippe Vincent-Lamarre; Koustuv Sinha; Vincent Larivière; Alina Beygelzimer; Florence d'Alché-Buc; Emily B. Fox; Hugo Larochelle (J. Mach. Learn. Res., 2021)

How do Authors' Perceptions of their Papers Compare with Co-authors' Perceptions and Peer-review Decisions? - Charvi Rastogi; Ivan Stelmakh; Alina Beygelzimer; Yann N. Dauphin; Percy Liang; Jennifer Wortman Vaughan; Zhenyu Xue; Hal Daumé III; Emma Pierson; Nihar B. Shah (CoRR, 2022)

Has the Machine Learning Review Process Become More Arbitrary as the Field Has Grown? The NeurIPS 2021 Consistency Experiment. - Alina Beygelzimer; Yann N. Dauphin; Percy Liang; Jennifer Wortman Vaughan (CoRR, 2023)