Paper

  • No-regret Algorithms for Fair Resource Allocation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    No-regret Algorithms for Fair Resource Allocation

    Abhishek Sinha, Ativ Joshi, Rajarshi Bhattacharjee, Cameron Musco, Mohammad Hajiesmaili p48083-48109 from Advances in Neural Information Processing Systems 36
    Our Price: $0.00
  • No-Regret Bandit Exploration based on Soft Tree Ensemble Model

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    No-Regret Bandit Exploration based on Soft Tree Ensemble Model

    Shogo Iwazaki, Shinya Suzumura p20982-21033 from Advances in Neural Information Processing Systems 37
    Our Price: $0.00
  • No-Regret Learning for Fair Multi-Agent Social Welfare Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    No-Regret Learning for Fair Multi-Agent Social Welfare Optimization

    Mengxiao Zhang, Ramiro Deo-Campo Vuong, Haipeng Luo p57671-57700 from Advances in Neural Information Processing Systems 37
    Our Price: $0.00
  • No-Regret Learning in Dynamic Competition with Reference Effects Under Logit Demand

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    No-Regret Learning in Dynamic Competition with Reference Effects Under Logit Demand

    Mengzi Amy Guo, Donghao Ying, Javad Lavaei, Zuo-Jun Shen p10567-10603 from Advances in Neural Information Processing Systems 36
    Our Price: $0.00
  • No-Regret Learning in Games with Noisy Feedback: Faster Rates and Adaptivity Via Learning Rate Separation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    No-Regret Learning in Games with Noisy Feedback: Faster Rates and Adaptivity Via Learning Rate Separation

    Yu-Guan Hsieh, Kimon Antonakopoulos, Volkan Cevher, Panayotis Mertikopoulos p6544-6556 from Advances in Neural Information Processing Systems 35
    Our Price: $0.00
  • No-regret Learning in Harmonic Games: Extrapolation in the Face of Conflicting Interests

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    No-regret Learning in Harmonic Games: Extrapolation in the Face of Conflicting Interests

    Davide Legacci, Panayotis Mertikopoulos, Christos Papadimitriou, Georgios Piliouras, Bary Pradelski p123637-123674 from Advances in Neural Information Processing Systems 37
    Our Price: $0.00
  • No-Regret Learning with Unbounded Losses: The Case of Logarithmic Pooling

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    No-Regret Learning with Unbounded Losses: The Case of Logarithmic Pooling

    Eric Neyman, Tim Roughgarden p21857-21877 from Advances in Neural Information Processing Systems 36
    Our Price: $0.00
  • No-Regret M${}^{\natural}$-Concave Function Maximization: Stochastic Bandit Algorithms and NP-Hardness of Adversarial Full-Information Setting

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    No-Regret M${}^{\natural}$-Concave Function Maximization: Stochastic Bandit Algorithms and NP-Hardness of Adversarial Full-Information Setting

    Taihei Oki, Shinsaku Sakaue p57418-57438 from Advances in Neural Information Processing Systems 37
    Our Price: $0.00
  • No-Regret Online Prediction with Strategic Experts

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    No-Regret Online Prediction with Strategic Experts

    Omid Sadeghi, Maryam Fazel p54696-54715 from Advances in Neural Information Processing Systems 36
    Our Price: $0.00
  • No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions

    Tiancheng Jin, Junyan Liu, Chloé Rouyer, William Chang, Chen-Yu Wei, Haipeng Luo p38520-38585 from Advances in Neural Information Processing Systems 36
    Our Price: $0.00
  • Nocturne: A Scalable Driving Benchmark for Bringing Multi-Agent Learning One Step Closer to the Real World

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Nocturne: A Scalable Driving Benchmark for Bringing Multi-Agent Learning One Step Closer to the Real World

    Eugene Vinitsky, Nathan Lichtlé, Xiaomeng Yang, Brandon Amos, Jakob Foerster p3962-3974 from Advances in Neural Information Processing Systems 35
    Our Price: $0.00
  • NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification

    Qitian Wu, Wentao Zhao, Zenan Li, David P Wipf, Junchi Yan p27387-27401 from Advances in Neural Information Processing Systems 35
    Our Price: $0.00