Guru Guruganesh

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 46

Top Topics

Competitive Ratio

Top Venues

Publications

Guru Guruganesh, Jon Schneider, Joshua R. Wang
Prior-Free Mechanism with Welfare Guarantees. WWW (2024)
Shanda Li, Chong You, Guru Guruganesh, Joshua Ainslie, Santiago Ontañón, Manzil Zaheer, Sumit Sanghai, Yiming Yang, Sanjiv Kumar, Srinadh Bhojanapalli
Functional Interpolation for Relative Positions improves Long Context Transformers. ICLR (2024)
Guru Guruganesh, Yoav Kolumbus, Jon Schneider, Inbal Talgam-Cohen, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Joshua R. Wang, S. Matthew Weinberg
Contracting with a Learning Agent. CoRR (2024)
Guru Guruganesh, Aranyak Mehta, Di Wang, Kangning Wang
Prior-Independent Auctions for Heterogeneous Bidders. SODA (2024)
Guru Guruganesh, Jon Schneider, Joshua R. Wang, Junyao Zhao
The Power of Menus in Contract Design. CoRR (2023)
Ashwinkumar Badanidiyuru, Zhe Feng, Guru Guruganesh
Learning to Bid in Contextual First Price Auctions✱. WWW (2023)
Shanda Li, Chong You, Guru Guruganesh, Joshua Ainslie, Santiago Ontañón, Manzil Zaheer, Sumit Sanghai, Yiming Yang, Sanjiv Kumar, Srinadh Bhojanapalli
Functional Interpolation for Relative Positions Improves Long Context Transformers. CoRR (2023)
Guru Guruganesh, Jon Schneider, Joshua R. Wang, Junyao Zhao
The Power of Menus in Contract Design. EC (2023)
Paul Duetting, Guru Guruganesh, Jon Schneider, Joshua Ruizhi Wang
Optimal No-Regret Learning for One-Sided Lipschitz Functions. ICML (2023)
Mingda Qiao, Guru Guruganesh, Ankit Singh Rawat, Kumar Avinava Dubey, Manzil Zaheer
A Fourier Approach to Mixture Learning. NeurIPS (2022)
Gagan Aggarwal, Kshipra Bhawalkar, Guru Guruganesh, Andrés Perlroth
Maximizing Revenue in the Presence of Intermediaries. ITCS (2022)
Guru Guruganesh, Aranyak Mehta, Di Wang, Kangning Wang
Prior-Independent Auctions for Heterogeneous Bidders. CoRR (2022)
Sepehr Abbasi Zadeh, Nikhil Bansal, Guru Guruganesh, Aleksandar Nikolov, Roy Schwartz, Mohit Singh
Sticky Brownian Rounding and its Applications to Constraint Satisfaction Problems. ACM Trans. Algorithms 18 (4) (2022)
Mingda Qiao, Guru Guruganesh, Ankit Singh Rawat, Avinava Dubey, Manzil Zaheer
A Fourier Approach to Mixture Learning. CoRR (2022)
Guru Guruganesh, Allen Liu, Jon Schneider, Joshua R. Wang
Margin-Independent Online Multiclass Learning via Convex Geometry. NeurIPS (2021)
Nicholas Monath, Kumar Avinava Dubey, Guru Guruganesh, Manzil Zaheer, Amr Ahmed, Andrew McCallum, Gökhan Mergen, Marc Najork, Mert Terzihan, Bryon Tjanaka, Yuan Wang, Yuchen Wu
Scalable Hierarchical Agglomerative Clustering. KDD (2021)
C. J. Argue, Anupam Gupta, Ziye Tang, Guru Guruganesh
Chasing Convex Bodies with Linear Competitive Ratio. J. ACM 68 (5) (2021)
Sreenivas Gollapudi, Guru Guruganesh, Kostas Kollias, Pasin Manurangsi, Renato Paes Leme, Jon Schneider
Contextual Recommendations and Low-Regret Cutting-Plane Algorithms. CoRR (2021)
Gagan Aggarwal, Kshipra Bhawalkar, Guru Guruganesh, Andrés Perlroth
Maximizing revenue in the presence of intermediaries. CoRR (2021)
Guru Guruganesh, Jon Schneider, Joshua R. Wang
Contracts under Moral Hazard and Adverse Selection. EC (2021)
C. J. Argue, Anupam Gupta, Guru Guruganesh, Ziye Tang
Chasing convex bodies with linear competitive ratio (invited paper). STOC (2021)
Ashwinkumar Badanidiyuru, Zhe Feng, Guru Guruganesh
Learning to Bid in Contextual First Price Auctions. CoRR (2021)
Zhe Feng, Guru Guruganesh, Christopher Liaw, Aranyak Mehta, Abhishek Sethi
Convergence Analysis of No-Regret Bidding Algorithms in Repeated Auctions. AAAI (2021)
Guru Guruganesh, Allen Liu, Jon Schneider, Joshua R. Wang
Margin-Independent Online Multiclass Learning via Convex Geometry. CoRR (2021)
Sreenivas Gollapudi, Guru Guruganesh, Kostas Kollias, Pasin Manurangsi, Renato Paes Leme, Jon Schneider
Contextual Recommendations and Low-Regret Cutting-Plane Algorithms. NeurIPS (2021)
Manzil Zaheer, Guru Guruganesh, Kumar Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontañón, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, Amr Ahmed
Big Bird: Transformers for Longer Sequences. NeurIPS (2020)
C. J. Argue, Anupam Gupta, Guru Guruganesh, Ziye Tang
Chasing Convex Bodies with Linear Competitive Ratio. SODA (2020)
Guru Guruganesh, Jon Schneider, Joshua R. Wang
Contracts under Moral Hazard and Adverse Selection. CoRR (2020)
Nicholas Monath, Avinava Dubey, Guru Guruganesh, Manzil Zaheer, Amr Ahmed, Andrew McCallum, Gökhan Mergen, Marc Najork, Mert Terzihan, Bryon Tjanaka, Yuan Wang, Yuchen Wu
Scalable Bottom-Up Hierarchical Clustering. CoRR (2020)
C. J. Argue, Anupam Gupta, Guru Guruganesh
Dimension-Free Bounds on Chasing Convex Functions. CoRR (2020)
Zhe Feng, Guru Guruganesh, Christopher Liaw, Aranyak Mehta, Abhishek Sethi
Convergence Analysis of No-Regret Bidding Algorithms in Repeated Auctions. CoRR (2020)
Manzil Zaheer, Guru Guruganesh, Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontañón, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, Amr Ahmed
Big Bird: Transformers for Longer Sequences. CoRR (2020)
Sepehr Abbasi Zadeh, Nikhil Bansal, Guru Guruganesh, Aleksandar Nikolov, Roy Schwartz, Mohit Singh
Sticky Brownian Rounding and its Applications to Constraint Satisfaction Problems. SODA (2020)
C. J. Argue, Anupam Gupta, Guru Guruganesh
Dimension-Free Bounds for Chasing Convex Functions. COLT (2020)
Anupam Gupta, Guru Guruganesh, Binghui Peng, David Wajc
Stochastic Online Metric Matching. ICALP (2019)
C. J. Argue, Anupam Gupta, Guru Guruganesh, Ziye Tang
Chasing Convex Bodies with Linear Competitive Ratio. CoRR (2019)
Anupam Gupta, Guru Guruganesh, Binghui Peng, David Wajc
Stochastic Online Metric Matching. CoRR (2019)
Nikhil Bansal, Anupam Gupta, Guru Guruganesh
On the Lovász Theta Function for Independent Sets in Sparse Graphs. SIAM J. Comput. 47 (3) (2018)
Sepehr Abbasi Zadeh, Nikhil Bansal, Guru Guruganesh, Aleksandar Nikolov, Roy Schwartz, Mohit Singh
Sticky Brownian Rounding and its Applications to Constraint Satisfaction Problems. CoRR (2018)
Björn Feldkord, Matthias Feldotto, Anupam Gupta, Guru Guruganesh, Amit Kumar, Sören Riechers, David Wajc
Fully-Dynamic Bin Packing with Little Repacking. ICALP (2018)
Guru Guruganesh, Euiwoong Lee
Understanding the Correlation Gap for Matchings. CoRR (2017)
Guru Guruganesh, Jennifer Iglesias, R. Ravi, Laura Sanità
Single-Sink Fractionally Subadditive Network Design. ESA (2017)
Guru Guruganesh, Jennifer Iglesias, R. Ravi, Laura Sanità
Single-sink Fractionally Subadditive Network Design. CoRR (2017)
Guru Guruganesh, Euiwoong Lee
Understanding the Correlation Gap For Matchings. FSTTCS (2017)
Anupam Gupta, Guru Guruganesh, Amit Kumar, David Wajc
Fully-Dynamic Bin Packing with Limited Repacking. CoRR (2017)
Anupam Gupta, Guru Guruganesh, Melanie Schmidt
Approximation Algorithms for Aversion k-Clustering via Local k-Median. ICALP (2016)
Nikhil Bansal, Anupam Gupta, Guru Guruganesh
On the Lovász Theta function for Independent Sets in Sparse Graphs. STOC (2015)
Guru Guruganesh, Laura Sanità, Chaitanya Swamy
-Route Cut Problems (Extended Abstract). SODA (2015)
Nikhil Bansal, Anupam Gupta, Guru Guruganesh
On the Lovász Theta function for Independent Sets in Sparse Graphs. CoRR (2015)
Guru Guruganesh, Laura Sanità, Chaitanya Swamy
Improved Region-Growing and Combinatorial Algorithms for $k$-Route Cut Problems. CoRR (2014)