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The Computational Complexity of Multi-player Concave Games and Kakutani Fixed Points

https://doi.org/10.1145/3580507.3597812

Papadimitriou, Christos ; Vlatakis-Gkaragkounis, Emmanouil-Vasileios ; Zampetakis, Manolis ( July 2023 , Proceedings of the 24th ACM Conference on Economics and Computation)

Free, publicly-accessible full text available July 7, 2024
Public goods games in directed networks

https://doi.org/10.1016/j.geb.2023.02.002

Papadimitriou, Christos ; Peng, Binghui ( May 2023 , Games and Economic Behavior)

Free, publicly-accessible full text available May 1, 2024
The Smoothed Complexity of Policy Iteration for Markov Decision Processes

https://doi.org/10.1145/3564246.3585220

Christ, Miranda ; Yannakakis, Mihalis ( January 2023 , In Proceedings of the 55th ACM Symposium on Theory of Computing (STOC))

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Testing Convex Truncation

De, Anindya ; Nadimpali, Shivam ; Servedio, Rocco A. ( January 2023 , Proceedings of the 2023 {ACM-SIAM} Symposium on Discrete Algorithms)

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Extremal Combinatorics, Iterated Pigeonhole Arguments and Generalizations of PPP

Pasarkar, Amol ; Papadimitriou, Christos H. ; Yannakakis, Mihalis ( January 2023 , 14th Innovations in Theoretical Computer Science Conference)

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Testing and Learning Quantum Juntas Nearly Optimally

Chen, Thomas ; Nadimpali, Shivam ; Yuen, Henry ( January 2023 , Proceedings of the 2023 {ACM-SIAM} Symposium on Discrete Algorithms)

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Memory Bounds for Continual Learning

https://doi.org/10.1109/FOCS54457.2022.00056

Chen, Xi ; Papadimitriou, Christos ; Peng, Binghui ( October 2022 , In Proceedings of the 63rd IEEE Symposium on Foundations of Computer Science (FOCS))

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On the complexity of dynamic mechanism design

https://doi.org/10.1016/j.geb.2022.01.024

Papadimitriou, Christos ; Pierrakos, George ; Psomas, Alexandros ; Rubinstein, Aviad ( March 2022 , Games and Economic Behavior)

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The Hardest Explicit Construction

https://doi.org/10.1109/FOCS52979.2021.00051

Korten, Oliver ( February 2022 , IEEE Annual Symposium on Foundations of Computer Science)

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Bridging the Gap Between Neurons and Cognition Through Assemblies of Neurons

https://doi.org/10.1162/neco_a_01463

Papadimitriou, Christos H. ; Friederici, Angela D. ( January 2022 , Neural Computation)

Abstract During recent decades, our understanding of the brain has advanced dramatically at both the cellular and molecular levels and at the cognitive neurofunctional level; however, a huge gap remains between the microlevel of physiology and the macrolevel of cognition. We propose that computational models based on assemblies of neurons can serve as a blueprint for bridging these two scales. We discuss recently developed computational models of assemblies that have been demonstrated to mediate higher cognitive functions such as the processing of simple sentences, to be realistically realizable by neural activity, and to possess general computational power.
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