Brian Brubach

42 papers A* 9A 3B 3C 2Journal 21Unranked 3
YearRankTypeTitle / Venue / Authors
2025 J jnl
Improved Guarantees for Offline Stochastic Matching via New Ordered Contention Resolution Schemes.
Math. Oper. Res.
Brian Brubach, Nathaniel Grammel, Will Ma, Aravind Srinivasan
2025 J jnl
Online Matching Frameworks Under Stochastic Rewards, Product Ranking, and Unknown Patience.
Oper. Res.
Brian Brubach, Nathaniel Grammel, Will Ma, Aravind Srinivasan
2024 A* conf
Implications of Distance over Redistricting Maps: Central and Outlier Maps.
AAAI
Seyed A. Esmaeili, Darshan Chakrabarti, Hayley Grape, Brian Brubach
2022 J jnl
Centralized Fairness for Redistricting.
CoRR
Seyed A. Esmaeili, Hayley Grape, Brian Brubach
2022 — conf
Characterizing Properties and Trade-offs of Centralized Delegation Mechanisms in Liquid Democracy.
FAccT
Brian Brubach, Audrey Ballarin, Heeba Nazeer
2022 J jnl
Characterizing Properties and Trade-offs of Centralized Delegation Mechanisms in Liquid Democracy.
CoRR
Brian Brubach, Audrey Ballarin, Heeba Nazeer
2022 A* conf
Fair Labeled Clustering.
KDD
Seyed A. Esmaeili, Sharmila Duppala, John P. Dickerson, Brian Brubach
2022 J jnl
Fair Labeled Clustering.
CoRR
Seyed A. Esmaeili, Sharmila Duppala, John P. Dickerson, Brian Brubach
2021 — conf
Approximating Two-Stage Stochastic Supplier Problems.
APPROX-RANDOM
Brian Brubach, Nathaniel Grammel, David G. Harris, Aravind Srinivasan, Leonidas Tsepenekas, Anil Vullikanti
2021 A* conf
Fair Clustering Under a Bounded Cost.
NeurIPS
Seyed A. Esmaeili, Brian Brubach, Aravind Srinivasan, John Dickerson
2021 J jnl
Fair Clustering Under a Bounded Cost.
CoRR
Seyed A. Esmaeili, Brian Brubach, Aravind Srinivasan, John P. Dickerson
2021 A* conf
Fairness, Semi-Supervised Learning, and More: A General Framework for Clustering with Stochastic Pairwise Constraints.
AAAI
Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Aravind Srinivasan, Leonidas Tsepenekas
2021 J jnl
Fairness, Semi-Supervised Learning, and More: A General Framework for Clustering with Stochastic Pairwise Constraints.
CoRR
Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Aravind Srinivasan, Leonidas Tsepenekas
2021 A conf
Follow Your Star: New Frameworks for Online Stochastic Matching with Known and Unknown Patience.
AISTATS
Nathaniel Grammel, Brian Brubach, Will Ma, Aravind Srinivasan
2021 A* conf
Improved Guarantees for Offline Stochastic Matching via new Ordered Contention Resolution Schemes.
NeurIPS
Brian Brubach, Nathaniel Grammel, Will Ma, Aravind Srinivasan
2021 J jnl
Improved Guarantees for Offline Stochastic Matching via new Ordered Contention Resolution Schemes.
CoRR
Brian Brubach, Nathaniel Grammel, Will Ma, Aravind Srinivasan
2021 — conf
It's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks.
NeurIPS Datasets and Benchmarks
Michelle Bao, Angela Zhou, Samantha Zottola, Brian Brubach, Sarah Desmarais, Aaron Horowitz, Kristian Lum, Suresh Venkatasubramanian
2021 J jnl
It's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks.
CoRR
Michelle Bao, Angela Zhou, Samantha Zottola, Brian Brubach, Sarah Desmarais, Aaron Horowitz, Kristian Lum, Suresh Venkatasubramanian
2020 A* conf
A Pairwise Fair and Community-preserving Approach to k-Center Clustering.
ICML
Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas
2020 J jnl
A Pairwise Fair and Community-preserving Approach to k-Center Clustering.
CoRR
Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas
2020 J jnl
Algorithms to Approximate Column-sparse Packing Problems.
ACM Trans. Algorithms
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2020 J jnl
Approximation Algorithms for Radius-Based, Two-Stage Stochastic Clustering Problems with Budget Constraints.
CoRR
Brian Brubach, Nathaniel Grammel, David G. Harris, Aravind Srinivasan, Leonidas Tsepenekas, Anil Vullikanti
2020 J jnl
Attenuate Locally, Win Globally: Attenuation-Based Frameworks for Online Stochastic Matching with Timeouts.
Algorithmica
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2020 J jnl
Improved Approximation Algorithms for Stochastic-Matching Problems.
CoRR
Marek Adamczyk, Brian Brubach, Fabrizio Grandoni, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2020 — —
Markets, Elections, and Microbes: Data-driven Algorithms from Theory to Practice.
Brian Brubach
2020 A* conf
Meddling Metrics: the Effects of Measuring and Constraining Partisan Gerrymandering on Voter Incentives.
EC
Brian Brubach, Aravind Srinivasan, Shawn Zhao
2020 J jnl
Online Stochastic Matching: New Algorithms and Bounds.
Algorithmica
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2020 A* conf
Probabilistic Fair Clustering.
NeurIPS
Seyed A. Esmaeili, Brian Brubach, Leonidas Tsepenekas, John Dickerson
2020 J jnl
Probabilistic Fair Clustering.
CoRR
Seyed A. Esmaeili, Brian Brubach, Leonidas Tsepenekas, John P. Dickerson
2019 J jnl
Vertex-weighted Online Stochastic Matching with Patience Constraints.
CoRR
Brian Brubach, Nathaniel Grammel, Aravind Srinivasan
2018 B conf
A Succinct Four Russians Speedup for Edit Distance Computation and One-against-many Banded Alignment.
CPM
Brian Brubach, Jay Ghurye
2018 A* conf
Algorithms to Approximate Column-Sparse Packing Problems.
SODA
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2018 J jnl
Attenuate Locally, Win Globally: An Attenuation-based Framework for Online Stochastic Matching with Timeouts.
CoRR
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2018 B conf
Fast Matching-based Approximations for Maximum Duo-Preservation String Mapping and its Weighted Variant.
CPM
Brian Brubach
2017 J jnl
Algorithms to Approximate Column-Sparse Packing Problems.
CoRR
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2017 A conf
Attenuate Locally, Win Globally: An Attenuation-based Framework for Online Stochastic Matching with Timeouts.
AAMAS
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2017 C conf
Better Greedy Sequence Clustering with Fast Banded Alignment.
WABI
Brian Brubach, Jay Ghurye, Mihai Pop, Aravind Srinivasan
2016 C conf
Further Improvement in Approximating the Maximum Duo-Preservation String Mapping Problem.
WABI
Brian Brubach
2016 A conf
New Algorithms, Better Bounds, and a Novel Model for Online Stochastic Matching.
ESA
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2016 J jnl
New Algorithms, Better Bounds, and a Novel Model for Online Stochastic Matching.
CoRR
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
2014 B conf
Improved Bound for Online Square-into-Square Packing.
WAOA
Brian Brubach
2014 J jnl
Improved Online Square-into-Square Packing.
CoRR
Brian Brubach