Brian Brubach

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 37

Top Topics

Approximation Algorithms

Packing Problem

Top Venues

Publications

Seyed A. Esmaeili, Darshan Chakrabarti, Hayley Grape, Brian Brubach
Implications of Distance over Redistricting Maps: Central and Outlier Maps. AAAI (2024)
Brian Brubach, Audrey Ballarin, Heeba Nazeer
Characterizing Properties and Trade-offs of Centralized Delegation Mechanisms in Liquid Democracy. FAccT (2022)
Brian Brubach, Audrey Ballarin, Heeba Nazeer
Characterizing Properties and Trade-offs of Centralized Delegation Mechanisms in Liquid Democracy. CoRR (2022)
Seyed A. Esmaeili, Sharmila Duppala, John P. Dickerson, Brian Brubach
Fair Labeled Clustering. CoRR (2022)
Seyed A. Esmaeili, Hayley Grape, Brian Brubach
Centralized Fairness for Redistricting. CoRR (2022)
Seyed A. Esmaeili, Sharmila Duppala, John P. Dickerson, Brian Brubach
Fair Labeled Clustering. KDD (2022)
Nathaniel Grammel, Brian Brubach, Will Ma, Aravind Srinivasan
Follow Your Star: New Frameworks for Online Stochastic Matching with Known and Unknown Patience. AISTATS (2021)
Seyed A. Esmaeili, Brian Brubach, Aravind Srinivasan, John P. Dickerson
Fair Clustering Under a Bounded Cost. CoRR (2021)
Brian Brubach, Nathaniel Grammel, David G. Harris, Aravind Srinivasan, Leonidas Tsepenekas, Anil Vullikanti
Approximating Two-Stage Stochastic Supplier Problems. APPROX-RANDOM (2021)
Brian Brubach, Nathaniel Grammel, Will Ma, Aravind Srinivasan
Improved Guarantees for Offline Stochastic Matching via new Ordered Contention Resolution Schemes. CoRR (2021)
Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Aravind Srinivasan, Leonidas Tsepenekas
Fairness, Semi-Supervised Learning, and More: A General Framework for Clustering with Stochastic Pairwise Constraints. CoRR (2021)
Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Aravind Srinivasan, Leonidas Tsepenekas
Fairness, Semi-Supervised Learning, and More: A General Framework for Clustering with Stochastic Pairwise Constraints. AAAI (2021)
Brian Brubach, Nathaniel Grammel, Will Ma, Aravind Srinivasan
Improved Guarantees for Offline Stochastic Matching via new Ordered Contention Resolution Schemes. NeurIPS (2021)
Michelle Bao, Angela Zhou, Samantha Zottola, Brian Brubach, Sarah Desmarais, Aaron Horowitz, Kristian Lum, Suresh Venkatasubramanian
It's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks. NeurIPS Datasets and Benchmarks (2021)
Michelle Bao, Angela Zhou, Samantha Zottola, Brian Brubach, Sarah Desmarais, Aaron Horowitz, Kristian Lum, Suresh Venkatasubramanian
It's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks. CoRR (2021)
Seyed A. Esmaeili, Brian Brubach, Aravind Srinivasan, John Dickerson
Fair Clustering Under a Bounded Cost. NeurIPS (2021)
Seyed A. Esmaeili, Brian Brubach, Leonidas Tsepenekas, John P. Dickerson
Probabilistic Fair Clustering. CoRR (2020)
Brian Brubach, Nathaniel Grammel, David G. Harris, Aravind Srinivasan, Leonidas Tsepenekas, Anil Vullikanti
Approximation Algorithms for Radius-Based, Two-Stage Stochastic Clustering Problems with Budget Constraints. CoRR (2020)
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
Attenuate Locally, Win Globally: Attenuation-Based Frameworks for Online Stochastic Matching with Timeouts. Algorithmica 82 (1) (2020)
Marek Adamczyk, Brian Brubach, Fabrizio Grandoni, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
Improved Approximation Algorithms for Stochastic-Matching Problems. CoRR (2020)
Seyed A. Esmaeili, Brian Brubach, Leonidas Tsepenekas, John Dickerson
Probabilistic Fair Clustering. NeurIPS (2020)
Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas
A Pairwise Fair and Community-preserving Approach to k-Center Clustering. ICML (2020)
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
Algorithms to Approximate Column-sparse Packing Problems. ACM Trans. Algorithms 16 (1) (2020)
Brian Brubach, Aravind Srinivasan, Shawn Zhao
Meddling Metrics: the Effects of Measuring and Constraining Partisan Gerrymandering on Voter Incentives. EC (2020)
Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas
A Pairwise Fair and Community-preserving Approach to k-Center Clustering. CoRR (2020)
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
Online Stochastic Matching: New Algorithms and Bounds. Algorithmica 82 (10) (2020)
Brian Brubach, Nathaniel Grammel, Aravind Srinivasan
Vertex-weighted Online Stochastic Matching with Patience Constraints. CoRR (2019)
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
Algorithms to Approximate Column-Sparse Packing Problems. SODA (2018)
Brian Brubach, Jay Ghurye
A Succinct Four Russians Speedup for Edit Distance Computation and One-against-many Banded Alignment. CPM (2018)
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
Attenuate Locally, Win Globally: An Attenuation-based Framework for Online Stochastic Matching with Timeouts. CoRR (2018)
Brian Brubach
Fast Matching-based Approximations for Maximum Duo-Preservation String Mapping and its Weighted Variant. CPM (2018)
Brian Brubach, Jay Ghurye, Mihai Pop, Aravind Srinivasan
Better Greedy Sequence Clustering with Fast Banded Alignment. WABI (2017)
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
Attenuate Locally, Win Globally: An Attenuation-based Framework for Online Stochastic Matching with Timeouts. AAMAS (2017)
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
Algorithms to Approximate Column-Sparse Packing Problems. CoRR (2017)
Brian Brubach
Further Improvement in Approximating the Maximum Duo-Preservation String Mapping Problem. WABI (2016)
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
New Algorithms, Better Bounds, and a Novel Model for Online Stochastic Matching. ESA (2016)
Brian Brubach, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
New Algorithms, Better Bounds, and a Novel Model for Online Stochastic Matching. CoRR (2016)
Brian Brubach
Improved Online Square-into-Square Packing. CoRR (2014)
Brian Brubach
Improved Bound for Online Square-into-Square Packing. WAOA (2014)