Author

Noah Golowich

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Preprint Sep 2026

The Fine-Grained Complexity of Approximate Nash Equilibrium and Free Games

We study the fine-grained complexity of computing approximate Nash equilibria and approximating the value of free games in the regime where the approximation error vanishes. Under the PCP for PPAD and ETH for PPAD conjectures, we show that computing $\varepsilon$-approximate Nash equilibria in 2-player $N$-action norma...

Noah Golowich · 0 citations

#machine learning Preprint Oct 2026

Normal-Form Correlation in Markov Games

There has been a surge of recent work on correlated equilibrium concepts in Markov games. However, existing results focus on concepts weaker than normal-form correlated equilibria (NFCEs), leaving open the more challenging question of computing such equilibria, which goes back to the seminal work of Papadimitriou and R...

I. Anagnostides, Constantinos Daskalakis, Gabriele Farina et al. · 0 citations

#machine learning Preprint Jun 2024

Breaking the $T^{2/3}$ Barrier for Sequential Calibration

It is proved that the relationship between SPR and calibrated forecasting is bidirectional: not only do lower bounds for SPR translate into lower bounds for calibration, but algorithms for SPR also translate into new algorithms for calibrated forecasting.

Y. Dagan, Constantinos Daskalakis, Maxwell Fishelson et al. · 20 citations · ⚡2