Rahul Savani

ORCID

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 86

Top Venues

Publications

John Fearnley, Paul W. Goldberg, Alexandros Hollender, Rahul Savani
The Complexity of Computing KKT Solutions of Quadratic Programs. STOC (2024)
Michaela Borzechowski, John Fearnley, Spencer Gordon, Rahul Savani, Patrick Schnider, Simon Weber
Two Choices are Enough for P-LCPs, USOs, and Colorful Tangents. CoRR (2024)
Nelson Vadori, Rahul Savani
Ordinal Potential-based Player Rating. AISTATS (2024)
Ariyan Bighashdel, Yongzhao Wang, Stephen McAleer, Rahul Savani, Frans A. Oliehoek
Policy Space Response Oracles: A Survey. CoRR (2024)
Michaela Borzechowski, John Fearnley, Spencer Gordon, Rahul Savani, Patrick Schnider, Simon Weber
Two Choices Are Enough for P-LCPs, USOs, and Colorful Tangents. ICALP (2024)
Joseph Jerome, Leandro Sánchez-Betancourt, Rahul Savani, Martin Herdegen
Mbt-gym: Reinforcement learning for model-based limit order book trading. ICAIF (2023)
John Fearnley, Paul Goldberg, Alexandros Hollender, Rahul Savani
The Complexity of Gradient Descent: CLS = PPAD ∩ PLS. J. ACM 70 (1) (2023)
Antonia Tsili, Matthew Dyer, Vladimir Gusev, Piotr Krysta, Rahul Savani
First Order Methods for Geometric Optimization of Crystal Structures. CoRR (2023)
John Fearnley, Paul W. Goldberg, Alexandros Hollender, Rahul Savani
The Complexity of Computing KKT Solutions of Quadratic Programs. CoRR (2023)
Nelson Vadori, Rahul Savani
Ordinal Potential-based Player Rating. CoRR (2023)
Andrea Coletta, Joseph Jerome, Rahul Savani, Svitlana Vyetrenko
Conditional Generators for Limit Order Book Environments: Explainability, Challenges, and Robustness. ICAIF (2023)
Andrea Coletta, Joseph Jerome, Rahul Savani, Svitlana Vyetrenko
Conditional Generators for Limit Order Book Environments: Explainability, Challenges, and Robustness. CoRR (2023)
Joseph Jerome, Leandro Sánchez-Betancourt, Rahul Savani, Martin Herdegen
Model-based gym environments for limit order book trading. CoRR (2022)
Ian M. Gemp, Rahul Savani, Marc Lanctot, Yoram Bachrach, Thomas W. Anthony, Richard Everett, Andrea Tacchetti, Tom Eccles, János Kramár
Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent. AAMAS (2022)
James Butterworth, Rahul Savani, Karl Tuyls
Generative Models over Neural Controllers for Transfer Learning. PPSN (1) (2022)
Joseph Jerome, Gregory Palmer, Rahul Savani
Market Making with Scaled Beta Policies. ICAIF (2022)
John Fearnley, Dömötör Pálvölgyi, Rahul Savani
A Faster Algorithm for Finding Tarski Fixed Points. ACM Trans. Algorithms 18 (3) (2022)
Nelson Vadori, Rahul Savani, Thomas Spooner, Sumitra Ganesh
Consensus Multiplicative Weights Update: Learning to Learn using Projector-based Game Signatures. ICML (2022)
Joseph Jerome, Gregory Palmer, Rahul Savani
Market Making with Scaled Beta Policies. CoRR (2022)
Nelson Vadori, Rahul Savani, Thomas Spooner, Sumitra Ganesh
Consensus Multiplicative Weights Update: Learning to Learn using Projector-based Game Signatures. CoRR (2021)
Nestoras Chalkidis, Rahul Savani
Trading via selective classification. ICAIF (2021)
Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, Rahul Savani
Difference Rewards Policy Gradients. AAMAS (2021)
Jacopo Castellini, Frans A. Oliehoek, Rahul Savani, Shimon Whiteson
Analysing factorizations of action-value networks for cooperative multi-agent reinforcement learning. Auton. Agents Multi Agent Syst. 35 (2) (2021)
Nestoras Chalkidis, Rahul Savani
Trading via Selective Classification. CoRR (2021)
John Fearnley, Rahul Savani
A Faster Algorithm for Finding Tarski Fixed Points. STACS (2021)
Rahul Savani
The Complexity of Gradient Descent (Invited Talk). FSTTCS (2021)
Ian M. Gemp, Rahul Savani, Marc Lanctot, Yoram Bachrach, Thomas W. Anthony, Richard Everett, Andrea Tacchetti, Tom Eccles, János Kramár
Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent. CoRR (2021)
John Fearnley, Martin Gairing, Matthias Mnich, Rahul Savani
Reachability Switching Games. Log. Methods Comput. Sci. 17 (2) (2021)
John Fearnley, Paul W. Goldberg, Alexandros Hollender, Rahul Savani
The complexity of gradient descent: CLS = PPAD ∩ PLS. STOC (2021)
Argyrios Deligkas, John Fearnley, Rahul Savani
Tree Polymatrix Games are PPAD-hard. CoRR (2020)
Thomas Spooner, Rahul Savani
Robust Market Making via Adversarial Reinforcement Learning. AAMAS (2020)
Thomas Spooner, Rahul Savani
A Natural Actor-Critic Algorithm with Downside Risk Constraints. CoRR (2020)
John Fearnley, Rasmus Ibsen-Jensen, Rahul Savani
One-Clock Priced Timed Games are PSPACE-hard. CoRR (2020)
Gregory Palmer, Mark Green, Emma Boyland, Yales Stefano Rios Vasconcelos, Rahul Savani, Alex Singleton
A deep learning approach to identify unhealthy advertisements in street view images. CoRR (2020)
Thomas Spooner, Rahul Savani
Robust Market Making via Adversarial Reinforcement Learning. IJCAI (2020)
Thomas Spooner, Rahul Savani
Robust Market Making via Adversarial Reinforcement Learning. CoRR (2020)
Argyrios Deligkas, John Fearnley, Rahul Savani
Tree Polymatrix Games Are PPAD-Hard. ICALP (2020)
John Fearnley, Rasmus Ibsen-Jensen, Rahul Savani
One-Clock Priced Timed Games are PSPACE-hard. LICS (2020)
Gregory Palmer, Benjamin Schnieders, Rahul Savani, Karl Tuyls, Joscha-David Fossel, Harry Flore
The Automated Inspection of Opaque Liquid Vaccines. CoRR (2020)
Gregory Palmer, Benjamin Schnieders, Rahul Savani, Karl Tuyls, Joscha-David Fossel, Harry Flore
The Automated Inspection of Opaque Liquid Vaccines. ECAI (2020)
John Fearnley, Rahul Savani
A faster algorithm for finding Tarski fixed points. CoRR (2020)
John Fearnley, Paul W. Goldberg, Alexandros Hollender, Rahul Savani
The Complexity of Gradient Descent: CLS = PPAD ∩ PLS. CoRR (2020)
Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, Rahul Savani
Difference Rewards Policy Gradients. CoRR (2020)
John Fearnley, Spencer Gordon, Ruta Mehta, Rahul Savani
Unique end of potential line. J. Comput. Syst. Sci. 114 (2020)
Alex Singleton, Alexandros Alexiou, Rahul Savani
Mapping the geodemographics of digital inequality in Great Britain: An integration of machine learning into small area estimation. Comput. Environ. Urban Syst. 82 (2020)
Jacopo Castellini, Frans A. Oliehoek, Rahul Savani, Shimon Whiteson
The Representational Capacity of Action-Value Networks for Multi-Agent Reinforcement Learning. AAMAS (2019)
John Fearnley, Spencer Gordon, Ruta Mehta, Rahul Savani
Unique End of Potential Line. ICALP (2019)
Martin Gairing, Rahul Savani
Computing Stable Outcomes in Symmetric Additively Separable Hedonic Games. Math. Oper. Res. 44 (3) (2019)
James Butterworth, Rahul Savani, Karl Tuyls
Evolving Indoor Navigational Strategies Using Gated Recurrent Units In NEAT. CoRR (2019)
Gregory Palmer, Rahul Savani, Karl Tuyls
Negative Update Intervals in Deep Multi-Agent Reinforcement Learning. AAMAS (2019)
Martin Gairing, Rahul Savani
Preface to the Special Issue on Algorithmic Game Theory. Theory Comput. Syst. 63 (1) (2019)
Jacopo Castellini, Frans A. Oliehoek, Rahul Savani, Shimon Whiteson
The Representational Capacity of Action-Value Networks for Multi-Agent Reinforcement Learning. CoRR (2019)
Artur Czumaj, Argyrios Deligkas, Michail Fasoulakis, John Fearnley, Marcin Jurdzinski, Rahul Savani
Distributed Methods for Computing Approximate Equilibria. Algorithmica 81 (3) (2019)
James Butterworth, Rahul Savani, Karl Tuyls
Evolving indoor navigational strategies using gated recurrent units in NEAT. GECCO (Companion) (2019)
Thomas Spooner, John Fearnley, Rahul Savani, Andreas Koukorinis
Market Making via Reinforcement Learning. AAMAS (2018)
John Fearnley, Spencer Gordon, Ruta Mehta, Rahul Savani
Unique End of Potential Line. CoRR (2018)
Argyrios Deligkas, John Fearnley, Rahul Savani
Inapproximability results for constrained approximate Nash equilibria. Inf. Comput. 262 (2018)
Gregory Palmer, Karl Tuyls, Daan Bloembergen, Rahul Savani
Lenient Multi-Agent Deep Reinforcement Learning. AAMAS (2018)
John Fearnley, Martin Gairing, Matthias Mnich, Rahul Savani
Reachability Switching Games. ICALP (2018)
Gregory Palmer, Rahul Savani, Karl Tuyls
Negative Update Intervals in Deep Multi-Agent Reinforcement Learning. CoRR (2018)
John Fearnley, Spencer Gordon, Ruta Mehta, Rahul Savani
End of Potential Line. CoRR (2018)
Frans A. Oliehoek, Rahul Savani, Jose Gallego-Posada, Elise van der Pol, Roderich Groß
Beyond Local Nash Equilibria for Adversarial Networks. CoRR (2018)
Richard Klíma, Daan Bloembergen, Rahul Savani, Karl Tuyls, Alexander Wittig, Andrei Sapera, Dario Izzo
Space Debris Removal: Learning to Cooperate and the Price of Anarchy. Frontiers Robotics AI 5 (2018)
Thomas Spooner, John Fearnley, Rahul Savani, Andreas Koukorinis
Market Making via Reinforcement Learning. CoRR (2018)
John Fearnley, Rahul Savani
The Complexity of All-switches Strategy Improvement. Log. Methods Comput. Sci. 14 (4) (2018)
Frans A. Oliehoek, Rahul Savani, Jose Gallego-Posada, Elise van der Pol, Roderich Groß
Beyond Local Nash Equilibria for Adversarial Networks. BNCAI (2018)
Argyrios Deligkas, John Fearnley, Rahul Savani
Computing Constrained Approximate Equilibria in Polymatrix Games. SAGT (2017)
Argyrios Deligkas, John Fearnley, Rahul Savani
Computing Constrained Approximate Equilibria in Polymatrix Games. CoRR (2017)
Frans A. Oliehoek, Rahul Savani, Jose Gallego-Posada, Elise van der Pol, Edwin D. de Jong, Roderich Gross
GANGs: Generative Adversarial Network Games. CoRR (2017)
John Fearnley, Martin Gairing, Matthias Mnich, Rahul Savani
Reachability Switching Games. CoRR (2017)
Frans A. Oliehoek, Rahul Savani, Elliot Adderton, Xia Cui, David Jackson, Phil Jimmieson, John Christopher Jones, Keith Kennedy, Ben Mason, Adam Plumbley, Luke Dawson
LiftUpp: Support to develop learner performance. CoRR (2017)
Argyrios Deligkas, John Fearnley, Rahul Savani, Paul G. Spirakis
Computing Approximate Nash Equilibria in Polymatrix Games. Algorithmica 77 (2) (2017)
Frans A. Oliehoek, Rahul Savani, Elliot Adderton, Xia Cui, David Jackson, Phil Jimmieson, John Christopher Jones, Keith Kennedy, Ben Mason, Adam Plumbley, Luke Dawson
LiftUpp: Support to Develop Learner Performance. AIED (2017)
Gregory Palmer, Karl Tuyls, Daan Bloembergen, Rahul Savani
Lenient Multi-Agent Deep Reinforcement Learning. CoRR (2017)
Karl Tuyls, Julien Pérolat, Marc Lanctot, Georg Ostrovski, Rahul Savani, Joel Z. Leibo, Toby Ord, Thore Graepel, Shane Legg
Symmetric Decomposition of Asymmetric Games. CoRR (2017)
John Fearnley, Spencer Gordon, Ruta Mehta, Rahul Savani
CLS: New Problems and Completeness. CoRR (2017)
John Fearnley, Rahul Savani
Finding Approximate Nash Equilibria of Bimatrix Games via Payoff Queries. ACM Trans. Economics and Comput. 4 (4) (2016)
Artur Czumaj, Argyrios Deligkas, Michail Fasoulakis, John Fearnley, Marcin Jurdzinski, Rahul Savani
Distributed Methods for Computing Approximate Equilibria. WINE (2016)
Argyrios Deligkas, John Fearnley, Tobenna Peter Igwe, Rahul Savani
An Empirical Study on Computing Equilibria in Polymatrix Games. CoRR (2016)
John Fearnley, Paul W. Goldberg, Rahul Savani, Troels Bjerre Sørensen
Approximate Well-supported Nash Equilibria Below Two-thirds. Algorithmica 76 (2) (2016)
Richard Klíma, Daan Bloembergen, Rahul Savani, Karl Tuyls, Daniel Hennes, Dario Izzo
Space Debris Removal: A Game Theoretic Analysis. Games 7 (3) (2016)
Argyrios Deligkas, John Fearnley, Rahul Savani
Inapproximability Results for Approximate Nash Equilibria. CoRR (2016)
Argyrios Deligkas, John Fearnley, Tobenna Peter Igwe, Rahul Savani
An Empirical Study on Computing Equilibria in Polymatrix Games. AAMAS (2016)
Richard Klíma, Daan Bloembergen, Rahul Savani, Karl Tuyls, Daniel Hennes, Dario Izzo
Space Debris Removal: A Game Theoretic Analysis. ECAI (2016)
John Fearnley, Rahul Savani
The Complexity of All-switches Strategy Improvement. SODA (2016)
Argyrios Deligkas, John Fearnley, Rahul Savani
Inapproximability Results for Approximate Nash Equilibria. WINE (2016)
John Fearnley, Rahul Savani
The Complexity of the Simplex Method. STOC (2015)
John Fearnley, Martin Gairing, Paul W. Goldberg, Rahul Savani
Learning equilibria of games via payoff queries. J. Mach. Learn. Res. 16 (2015)
Rahul Savani, Bernhard von Stengel
Unit Vector Games. CoRR (2015)
John Fearnley, Tobenna Peter Igwe, Rahul Savani
An Empirical Study of Finding Approximate Equilibria in Bimatrix Games. SEA (2015)
John Fearnley, Rahul Savani
The Complexity of All-switches Strategy Improvement. CoRR (2015)
Artur Czumaj, Argyrios Deligkas, Michail Fasoulakis, John Fearnley, Marcin Jurdzinski, Rahul Savani
Distributed Methods for Computing Approximate Equilibria. CoRR (2015)
Rahul Savani, Bernhard von Stengel
Game Theory Explorer: software for the applied game theorist. Comput. Manag. Sci. 12 (1) (2015)
John Fearnley, Tobenna Peter Igwe, Rahul Savani
An Empirical Study of Finding Approximate Equilibria in Bimatrix Games. CoRR (2015)
Martin Gairing, Rahul Savani
Computing stable outcomes in symmetric additively-separable hedonic games. CoRR (2015)
Mingyu Guo, Argyrios Deligkas, Rahul Savani
Increasing VCG Revenue by Decreasing the Quality of Items. AAAI (2014)
Yoram Bachrach, Rahul Savani, Nisarg Shah
Cooperative max games and agent failures. AAMAS (2014)
John Fearnley, Rahul Savani
Finding approximate Nash equilibria of bimatrix games via payoff queries. EC (2014)
Argyrios Deligkas, John Fearnley, Rahul Savani, Paul G. Spirakis
Computing Approximate Nash Equilibria in Polymatrix Games. WINE (2014)
Argyrios Deligkas, John Fearnley, Rahul Savani, Paul G. Spirakis
Computing Approximate Nash Equilibria in Polymatrix Games. CoRR (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Rahul Savani