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ORCIDGuru Guruganesh
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2020 – today
- 2024
[c25]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- [c24]Guru Guruganesh, Aranyak Mehta, Di Wang, Kangning Wang:
Prior-Independent Auctions for Heterogeneous Bidders. SODA 2024: 1-18 - [c23]Guru Guruganesh
, Jon Schneider, Joshua R. Wang:
Prior-Free Mechanism with Welfare Guarantees. WWW 2024: 135-143 - [i22]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 abs/2401.16198 (2024) - 2023
- [c22]Paul Duetting, Guru Guruganesh, Jon Schneider, Joshua Ruizhi Wang:
Optimal No-Regret Learning for One-Sided Lipschitz Functions. ICML 2023: 8836-8850 - [c21]Guru Guruganesh, Jon Schneider, Joshua R. Wang, Junyao Zhao:
The Power of Menus in Contract Design. EC 2023: 818-848 - [c20]Ashwinkumar Badanidiyuru, Zhe Feng, Guru Guruganesh:
Learning to Bid in Contextual First Price Auctions✱. WWW 2023: 3489-3497 - [i21]Guru Guruganesh, Jon Schneider, Joshua R. Wang, Junyao Zhao:
The Power of Menus in Contract Design. CoRR abs/2306.12667 (2023) - [i20]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 abs/2310.04418 (2023) - 2022
- [j4]Kshipra Bhawalkar, Guru Guruganesh, Sébastien Lahaie, Andrés Perlroth, Balasubramanian Sivan:
Research Challenges in Internet Ad Markets: Vignettes on Complex Environments. SIGecom Exch. 20(2): 48-61 (2022) - [j3]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): 33:1-33:50 (2022) - [c19]Gagan Aggarwal, Kshipra Bhawalkar, Guru Guruganesh, Andrés Perlroth:
Maximizing Revenue in the Presence of Intermediaries. ITCS 2022: 1:1-1:22 - [c18]Mingda Qiao, Guru Guruganesh, Ankit Singh Rawat, Kumar Avinava Dubey, Manzil Zaheer:
A Fourier Approach to Mixture Learning. NeurIPS 2022 - [i19]Guru Guruganesh, Aranyak Mehta, Di Wang, Kangning Wang:
Prior-Independent Auctions for Heterogeneous Bidders. CoRR abs/2207.09429 (2022) - [i18]Mingda Qiao, Guru Guruganesh, Ankit Singh Rawat, Avinava Dubey, Manzil Zaheer:
A Fourier Approach to Mixture Learning. CoRR abs/2210.02415 (2022) - 2021
- [j2]C. J. Argue, Anupam Gupta, Ziye Tang, Guru Guruganesh:
Chasing Convex Bodies with Linear Competitive Ratio. J. ACM 68(5): 32:1-32:10 (2021) - [c17]Zhe Feng, Guru Guruganesh, Christopher Liaw, Aranyak Mehta, Abhishek Sethi:
Convergence Analysis of No-Regret Bidding Algorithms in Repeated Auctions. AAAI 2021: 5399-5406 - [c16]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: 1245-1255 - [c15]Sreenivas Gollapudi, Guru Guruganesh, Kostas Kollias, Pasin Manurangsi, Renato Paes Leme, Jon Schneider:
Contextual Recommendations and Low-Regret Cutting-Plane Algorithms. NeurIPS 2021: 22498-22508 - [c14]Guru Guruganesh, Allen Liu, Jon Schneider, Joshua R. Wang:
Margin-Independent Online Multiclass Learning via Convex Geometry. NeurIPS 2021: 29156-29167 - [c13]Guru Guruganesh, Jon Schneider, Joshua R. Wang:
Contracts under Moral Hazard and Adverse Selection. EC 2021: 563-582 - [c12]C. J. Argue, Anupam Gupta, Guru Guruganesh, Ziye Tang:
Chasing convex bodies with linear competitive ratio (invited paper). STOC 2021: 5 - [i17]Sreenivas Gollapudi, Guru Guruganesh, Kostas Kollias, Pasin Manurangsi, Renato Paes Leme, Jon Schneider:
Contextual Recommendations and Low-Regret Cutting-Plane Algorithms. CoRR abs/2106.04819 (2021) - [i16]Ashwinkumar Badanidiyuru, Zhe Feng, Guru Guruganesh:
Learning to Bid in Contextual First Price Auctions. CoRR abs/2109.03173 (2021) - [i15]Guru Guruganesh, Allen Liu, Jon Schneider, Joshua R. Wang:
Margin-Independent Online Multiclass Learning via Convex Geometry. CoRR abs/2111.08057 (2021) - [i14]Gagan Aggarwal, Kshipra Bhawalkar, Guru Guruganesh, Andrés Perlroth:
Maximizing revenue in the presence of intermediaries. CoRR abs/2111.10472 (2021) - 2020
- [c11]C. J. Argue, Anupam Gupta, Guru Guruganesh:
Dimension-Free Bounds for Chasing Convex Functions. COLT 2020: 219-241 - [c10]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 - [c9]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: 854-873 - [c8]C. J. Argue, Anupam Gupta, Guru Guruganesh, Ziye Tang:
Chasing Convex Bodies with Linear Competitive Ratio. SODA 2020: 1519-1524 - [i13]C. J. Argue, Anupam Gupta, Guru Guruganesh:
Dimension-Free Bounds on Chasing Convex Functions. CoRR abs/2005.14058 (2020) - [i12]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 abs/2007.14062 (2020) - [i11]Zhe Feng, Guru Guruganesh, Christopher Liaw, Aranyak Mehta, Abhishek Sethi:
Convergence Analysis of No-Regret Bidding Algorithms in Repeated Auctions. CoRR abs/2009.06136 (2020) - [i10]Guru Guruganesh, Jon Schneider, Joshua R. Wang:
Contracts under Moral Hazard and Adverse Selection. CoRR abs/2010.06742 (2020) - [i9]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 abs/2010.11821 (2020)
2010 – 2019
- 2019
- [c7]Anupam Gupta, Guru Guruganesh, Binghui Peng, David Wajc:
Stochastic Online Metric Matching. ICALP 2019: 67:1-67:14 - [i8]Anupam Gupta, Guru Guruganesh, Binghui Peng, David Wajc:
Stochastic Online Metric Matching. CoRR abs/1904.09284 (2019) - [i7]C. J. Argue, Anupam Gupta, Guru Guruganesh, Ziye Tang:
Chasing Convex Bodies with Linear Competitive Ratio. CoRR abs/1905.11877 (2019) - 2018
- [j1]Nikhil Bansal, Anupam Gupta, Guru Guruganesh:
On the Lovász Theta Function for Independent Sets in Sparse Graphs. SIAM J. Comput. 47(3): 1039-1055 (2018) - [c6]Björn Feldkord, Matthias Feldotto, Anupam Gupta, Guru Guruganesh, Amit Kumar, Sören Riechers, David Wajc:
Fully-Dynamic Bin Packing with Little Repacking. ICALP 2018: 51:1-51:24 - [i6]Sepehr Abbasi Zadeh, Nikhil Bansal, Guru Guruganesh, Aleksandar Nikolov, Roy Schwartz, Mohit Singh:
Sticky Brownian Rounding and its Applications to Constraint Satisfaction Problems. CoRR abs/1812.07769 (2018) - 2017
- [c5]Guru Guruganesh, Jennifer Iglesias, R. Ravi, Laura Sanità:
Single-Sink Fractionally Subadditive Network Design. ESA 2017: 46:1-46:13 - [c4]Guru Guruganesh, Euiwoong Lee:
Understanding the Correlation Gap For Matchings. FSTTCS 2017: 32:1-32:15 - [i5]Guru Guruganesh, Jennifer Iglesias, R. Ravi, Laura Sanità:
Single-sink Fractionally Subadditive Network Design. CoRR abs/1707.01487 (2017) - [i4]Guru Guruganesh, Euiwoong Lee:
Understanding the Correlation Gap for Matchings. CoRR abs/1710.06339 (2017) - [i3]Anupam Gupta, Guru Guruganesh, Amit Kumar, David Wajc:
Fully-Dynamic Bin Packing with Limited Repacking. CoRR abs/1711.02078 (2017) - 2016
- [c3]Anupam Gupta, Guru Guruganesh, Melanie Schmidt:
Approximation Algorithms for Aversion k-Clustering via Local k-Median. ICALP 2016: 66:1-66:13 - 2015
- [c2]Guru Guruganesh, Laura Sanità, Chaitanya Swamy:
Improved Region-Growing and Combinatorial Algorithms for k-Route Cut Problems (Extended Abstract). SODA 2015: 676-695 - [c1]Nikhil Bansal, Anupam Gupta, Guru Guruganesh:
On the Lovász Theta function for Independent Sets in Sparse Graphs. STOC 2015: 193-200 - [i2]Nikhil Bansal, Anupam Gupta, Guru Guruganesh:
On the Lovász Theta function for Independent Sets in Sparse Graphs. CoRR abs/1504.04767 (2015) - 2014
- [i1]Guru Guruganesh, Laura Sanità, Chaitanya Swamy:
Improved Region-Growing and Combinatorial Algorithms for $k$-Route Cut Problems. CoRR abs/1410.5105 (2014)
Coauthor Index
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