Results 11 to 20 of about 577,383 (337)
Evolving Curricula with Regret-Based Environment Design [PDF]
International Conference on Machine Learning, 2022 It remains a significant challenge to train generally capable agents with reinforcement learning (RL). A promising avenue for improving the robustness of RL agents is through the use of curricula.
Jack Parker-Holder +6 more
semanticscholar +1 more source
Regret Minimization and Convergence to Equilibria in General-sum Markov Games [PDF]
International Conference on Machine Learning, 2022 An abundance of recent impossibility results establish that regret minimization in Markov games with adversarial opponents is both statistically and computationally intractable.
Liad Erez +4 more
semanticscholar +1 more source
On the Regret Analysis of Online LQR Control with Predictions [PDF]
American Control Conference, 2021 In this paper, we study the dynamic regret of online linear quadratic regulator (LQR) control with time-varying cost functions and disturbances. We consider the case where a finite look-ahead window of cost functions and disturbances are available at ...
Runyu Zhang, Yingying Li, Na Li
semanticscholar +1 more source
Modelling the Dynamics of Regret Minimization in Large Agent Populations: a Master Equation Approach
International Joint Conference on Artificial Intelligence, 2022 Understanding the learning dynamics in multiagent systems is an important and challenging task. Past research on multi-agent learning mostly focuses on two-agent settings.
Zhen Wang +4 more
semanticscholar +1 more source
Near-optimal no-regret learning for correlated equilibria in multi-player general-sum games [PDF]
Symposium on the Theory of Computing, 2021 Recently, Daskalakis, Fishelson, and Golowich (DFG) (NeurIPS ‘21) showed that if all agents in a multi-player general-sum normal-form game employ Optimistic Multiplicative Weights Update (OMWU), the external regret of every player is O(polylog(T)) after ...
Ioannis Anagnostides +5 more
semanticscholar +1 more source
Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting [PDF]
IEEE Transactions on Information Theory, 2009 Many applications require optimizing an unknown, noisy function that is expensive to evaluate. We formalize this task as a multiarmed bandit problem, where the payoff function is either sampled from a Gaussian process (GP) or has low norm in a ...
Niranjan Srinivas +3 more
semanticscholar +1 more source
Applied Sciences, 2023 In this paper, we analyzed the performance of different transformer models for regret and hope speech detection on two novel datasets. For the regret detection task, we compared the averaged macro-scores of the transformer models to the previous state-of-
G. Sidorov +3 more
semanticscholar +1 more source
Regret after Gender-affirmation Surgery: A Systematic Review and Meta-analysis of Prevalence
Plastic and Reconstructive Surgery, Global Open, 2021 Supplemental Digital Content is available in the text. Background: There is an unknown percentage of transgender and gender non-confirming individuals who undergo gender-affirmation surgeries (GAS) that experiences regret.
V. Bustos +8 more
semanticscholar +1 more source
A Prospective Study of Patterns of Regret in the Year After Hysterectomy
Journal of Patient-Centered Research and Reviews, 2020 Purpose: This study sought to identify patterns of self-reported regret after hysterectomy. Methods: Women undergoing hysterectomy for a benign indication were recruited in the 2 weeks prior to surgery.
Roopina Sangha +5 more
doaj +1 more source
Acta Obstetricia et Gynecologica Scandinavica, 2023 Introduction This study aims to assess the motivations and treatment experiences of women undergoing social egg freezing and to understand the impact of the Covid‐19 pandemic.
Sughashini Murugesu +8 more
doaj +1 more source