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Zero-sum Polymatrix Markov Games: Equilibrium Collapse and Efficient Computation of Nash Equilibria
One such example is two-player zero-sum Markov games, in which efficient ways to compute a Nash equilibrium are known. Inspired by zero-sum polymatrix normal-form games (Cai et al., 2016), we define a class of zero-sum
Maduro raid questions trigger Pentagon review of top AI firm as potential 'supply chain risk'
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Equivariant flow matching
Our main contributions in this work are as follows: 1.
GACL: Exemplar-Free Generalized Analytic Continual Learning
Class incremental learning (CIL) trains a network on sequential tasks with separated categories in each task but suffers from catastrophic forgetting, where models quickly lose previously learned knowledge when acquiring new tasks.
