2023
Bibliographic References tagged with 2023
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H. Sun, Z. Deng, H. Chen, and D. C. Parkes,
“Decision-Aware Conditional GANs for Time Series Data.”, in ICAIF 2023, 2023, pp. 36–45.
H. Sun, Z. Deng, H. Chen, and D. C. Parkes,
“Decision-Aware Conditional GANs for Time Series Data.”, in ICAIF 2023, 2023, pp. 36–45.
M. Gerstgrasser and D. C. Parkes,
“Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning.”, in ICML 2023, 2023, pp. 11213–11236.
M. Gerstgrasser and D. C. Parkes,
“Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning.”, in ICML 2023, 2023, pp. 11213–11236.
H. Zhang and D. C. Parkes,
“Chain-of-Thought Reasoning is a Policy Improvement Operator.”, Workshop on Instruction Tuning and Instruction Following at NeurIPS 2023 , 2023.
H. Zhang and D. C. Parkes,
“Chain-of-Thought Reasoning is a Policy Improvement Operator.”, Workshop on Instruction Tuning and Instruction Following at NeurIPS 2023 , 2023.
S. S. Ravindranath, Y. Jiang, and D. C. Parkes,
“ Data Market Design through Deep Learning.”, in NeurIPS 2023, 2023.
S. S. Ravindranath, Y. Jiang, and D. C. Parkes,
“ Data Market Design through Deep Learning.”, in NeurIPS 2023, 2023.
T. Wang, P. Duetting, D. Ivanov, I. Talgam-Cohen, and D. C. Parkes,
“Deep Contract Design via Discontinuous Networks.”, in Proceedings of the NeurIPS 2023 (Thirty-seventh Conference on Neural Information Processing Systems), 2023.
T. Wang, P. Duetting, D. Ivanov, I. Talgam-Cohen, and D. C. Parkes,
“Deep Contract Design via Discontinuous Networks.”, in Proceedings of the NeurIPS 2023 (Thirty-seventh Conference on Neural Information Processing Systems), 2023.
Y. Yacoby, J. Girash, and D. C. Parkes,
“Empowering First-Year Computer Science Ph.D. Students to Create a Culture that Values Community and Mental Health.”, in Proc. of the The Technical Symposium on Computer Science Education , 2023, pp. 694–700.
Y. Yacoby, J. Girash, and D. C. Parkes,
“Empowering First-Year Computer Science Ph.D. Students to Create a Culture that Values Community and Mental Health.”, in Proc. of the The Technical Symposium on Computer Science Education , 2023, pp. 694–700.
M. V. X. Ferreira and D. C. Parkes,
“Credible Decentralized Exchange Design via Verifiable Sequencing Rules”, in Proceedings of the 55th Annual ACM Symposium on Theory of Computing (STOC 2023), 2023, pp. 723–736.
M. V. X. Ferreira and D. C. Parkes,
“Credible Decentralized Exchange Design via Verifiable Sequencing Rules”, in Proceedings of the 55th Annual ACM Symposium on Theory of Computing (STOC 2023), 2023, pp. 723–736.
Z. Deng, H. Sun, S. Wu, L. Zhang, and D. C. Parkes,
“Reinforcement Learning with Stepwise Fairness Constraints.”, in Proceedings of the 26th International Conference on Artificial Intelligence and Statistics (AISTATS) , 2023, pp. 10594–10618.
Z. Deng, H. Sun, S. Wu, L. Zhang, and D. C. Parkes,
“Reinforcement Learning with Stepwise Fairness Constraints.”, in Proceedings of the 26th International Conference on Artificial Intelligence and Statistics (AISTATS) , 2023, pp. 10594–10618.
X. Wang et al.,
“Platform Behavior under Market Shocks: A Simulation Framework and Reinforcement-Learning Based Study.”, in Proc. of the International World Wide Web Conference (WWW ’23), 2023, pp. 3592–3602.
X. Wang et al.,
“Platform Behavior under Market Shocks: A Simulation Framework and Reinforcement-Learning Based Study.”, in Proc. of the International World Wide Web Conference (WWW ’23), 2023, pp. 3592–3602.
J. Watson-Daniels, D. C. Parkes, and B. Ustun,
“Predictive Multiplicity in Probabilistic Classification”, in Proc. of Association for the Advancement of Artificial Intelligence, AAAI, 2023, pp. 10306–10314.
J. Watson-Daniels, D. C. Parkes, and B. Ustun,
“Predictive Multiplicity in Probabilistic Classification”, in Proc. of Association for the Advancement of Artificial Intelligence, AAAI, 2023, pp. 10306–10314.