
Catastrophe by Design in Population Games: Destabilizing Wasteful Lockedin Technologies
In multiagent environments in which coordination is desirable, the hist...
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Chaos, Extremism and Optimism: Volume Analysis of Learning in Games
We present volume analyses of Multiplicative Weights Updates (MWU) and O...
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From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization
In this paper we investigate the Follow the Regularized Leader dynamics ...
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Smooth markets: A basic mechanism for organizing gradientbased learners
With the success of modern machine learning, it is becoming increasingly...
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Efficiently avoiding saddle points with zero order methods: No gradients required
We consider the case of derivativefree algorithms for nonconvex optimi...
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Poincaré Recurrence, Cycles and Spurious Equilibria in GradientDescentAscent for NonConvex NonConcave ZeroSum Games
We study a wide class of nonconvex nonconcave minmax games that gener...
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From Darwin to Poincaré and von Neumann: Recurrence and Cycles in Evolutionary and Algorithmic Game Theory
Replicator dynamics, the continuoustime analogue of Multiplicative Weig...
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Multiagent Evaluation under Incomplete Information
This paper investigates the evaluation of learned multiagent strategies ...
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Finite Regret and Cycles with Fixed StepSize via Alternating Gradient DescentAscent
Gradient descent is arguably one of the most popular online optimization...
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PREStO: A Systematic Framework for Blockchain Consensus Protocols
The rapid evolution of the blockchain community has brought together sta...
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The route to chaos in routing games: Population increase drives perioddoubling instability, chaos & inefficiency with Price of Anarchy equal to one
We study a learning dynamic model of routing (congestion) games to explo...
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Vortices Instead of Equilibria in MinMax Optimization: Chaos and Butterfly Effects of Online Learning in ZeroSum Games
We establish that algorithmic experiments in zerosum games "fail misera...
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Fast and Furious Learning in ZeroSum Games: Vanishing Regret with NonVanishing Step Sizes
We show for the first time, to our knowledge, that it is possible to rec...
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Oceanic Games: Centralization Risks and Incentives in Blockchain Mining
To participate in the distributed consensus of permissionless blockchain...
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Weighted Voting on the Blockchain: Improving Consensus in Proof of Stake Protocols
Proof of Stake (PoS) protocols rely on voting mechanisms to reach consen...
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Incentives in Ethereum's Hybrid Casper Protocol
We present an overview of hybrid Casper the Friendly Finality Gadget (FF...
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MultiAgent Learning in Network ZeroSum Games is a Hamiltonian System
Zerosum games are natural, if informal, analogues of closed physical sy...
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αRank: MultiAgent Evaluation by Evolution
We introduce αRank, a principled evolutionary dynamics methodology, for...
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Shortdistance commuters in the smart city
This study models and examines commuter's preferences for shortdistance...
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Venn GAN: Discovering Commonalities and Particularities of Multiple Distributions
We propose a GAN design which models multiple distributions effectively ...
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Optimistic mirror descent in saddlepoint problems: Going the extra (gradient) mile
Owing to their connection with generative adversarial networks (GANs), s...
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Mirror descent in saddlepoint problems: Going the extra (gradient) mile
Owing to their connection with generative adversarial networks (GANs), s...
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The Unusual Effectiveness of Averaging in GAN Training
We show empirically that the optimal strategy of parameter averaging in ...
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Rethinking Blockchain Security: Position Paper
Blockchain technology has become almost as famous for incidents involvin...
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Wealth Inequality and the Price of Anarchy
Price of anarchy quantifies the degradation of social welfare in games d...
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Learning Dynamics and the CoEvolution of Competing Sexual Species
We analyze a stylized model of coevolution between any two purely compe...
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Firstorder Methods Almost Always Avoid Saddle Points
We establish that firstorder methods avoid saddle points for almost all...
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Cycles in adversarial regularized learning
Regularized learning is a fundamental technique in online optimization, ...
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Routing Games in the Wild: Efficiency, Equilibration and Regret (LargeScale Field Experiments in Singapore)
Routing games are amongst the most well studied domains of game theory. ...
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Truly Multimodal YouTube8M Video Classification with Video, Audio, and Text
The YouTube8M video classification challenge requires teams to classify...
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Learning Agents in BlackScholes Financial Markets: Consensus Dynamics and Volatility Smiles
BlackScholes (BS) is the standard mathematical model for option pricing...
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Georgios Piliouras
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Assistant Professor at Engineering Systems and Design Singapore University of Technology and Design (SUTD)