我们证明了3台计算量子量子交互协议与有效的挑战者和有效对手之间的紧密平行重复定理。我们还证明,在合理的假设下,在并行重复下,4台式计算协议的安全性通常不会降低。这些反映了Bellare,Impagliazzo和Naor的经典结果[BIN97]。最后,我们证明所有量子参数系统都可以一致地编译到等效的3-序列参数系统,从而反映了量子证明系统的转换[KW00,KKMV07]。As immediate applications, we show how to derive hardness amplification theorems for quantum bit commitment schemes (answering a question of Yan [ Yan22 ]), EFI pairs (answering a question of Brakerski, Canetti, and Qian [ BCQ23 ]), public-key quantum money schemes (answering a question of Aaronson and Christiano [ AC13 ]), and quantum零知识参数系统。我们还为量子谓词推导了XOR引理[YAO82]作为推论。
在成功完成该模块后,学生应能够:LO1使用概率LO2设计的原理分析和设计重要的信号处理和机器学习(SPML)算法(SPML)算法,设计可易和有效的递归计算流量,用于在线过滤,以在线过滤和预测标准工程的LO3指定和替代设备的Steelarize in Startien felients in Startion interation felients in Startien felients in Startien felient in lo1 in lo1 in lo1 in lo1 in lo1 in lo1 in lo1, (过滤,均衡和系统识别); and implement Kalman filters in nonstationary filtering scenarios LO5 Compare parametric and nonparametric techniques for temporal and spatio-temporal regression problems LO6 Derive optimal classifiers based on matched probability models, and compare them to off-the-shelf classifiers ( k -means, EM) LO7 Implement optimal transport (OT) solutions to problems of (i) resource allocation, and (ii) training-data repair for AI公平(AIF)研究生属性:负责任地行动的水平 - 独立思考 - 不断发展 - 增强 - 有效地进行交流 - 增强了 - 增强
资料来源:彭博和 DBi。数据截至 2024 年 12 月 31 日 短期利率:指投资于从期限为 2 年或更短的固定收益工具中获得收益的期货合约 中期利率:指投资于从期限为 10 年或更短但超过 2 年的固定收益工具中获得收益的期货合约 长期利率:指投资于从期限超过 10 年的固定收益工具中获得收益的期货合约 EAFE:MSCI EAFE 指数。新兴市场:MSCI 新兴市场指数
Explain how the use of different energy resources affects the environment and the economy (SE- M-A6) Analyze positive and negative effects of human actions on ecosystems (LS-H-D4) (SE-H-A7) Identify resources humans derive from ecosystems (SE-M-A1) Rationale and suggested sequence for reading: The intent of this pack is to build knowledge round the coral reef, especially about the biodiversity with in the珊瑚礁和对人类和自然的礁石的威胁。包装随着文本的进展而增加,从事实语句和息肉图开始,整个珊瑚礁都是从建造的动物开始的,然后使用书面和视觉来源进行探索生物多样性。最复杂的文本描述了对礁石的威胁,包装以一篇文章结束,该文章将生物多样性和威胁的概念融合在一起,而螃蟹将礁石从入侵的海星中拯救出来。学生会发现,随着单词在不同的环境中重复的单词重复时,他们会发现越来越易于访问的第2层和域特异性词汇,并且发现该生态系统的微妙平衡将支持他们学习其他生态系统,海洋生命以及自然和人类对环境的影响的能力。ELA/读写能力的共同核心变化:
在美国和其他国家,人工智能 (AI) 正在改变包括财务报告和审计在内的所有商业领域。公司不再依赖耗时的手动流程和统计抽样,而是能够自动从各种来源收集和输入数据,从而增强其识别异常、管理风险和获得预测见解的能力。与此同时,人工智能还为审计师带来了新的能力——这将帮助美国和跨国公司不仅将其财务报告提升到新的水平,而且还能从其审计程序中获得更大的价值。
在美国和其他国家,人工智能 (AI) 正在改变包括财务报告和审计在内的所有业务领域。公司不再依赖耗时的手动流程和统计抽样,而是能够自动从各种来源收集和输入数据,从而增强其识别异常、管理风险和获得预测见解的能力。与此同时,人工智能还为审计师带来了新的能力——这将帮助美国和跨国公司不仅将其财务报告提升到新的水平,而且还能从审计中获得更大的价值。
Abstract In many real-world reinforcement learning (RL) problems, besides optimizing the main objective function, an agent must concurrently avoid violating a number of constraints.In particular, besides optimizing performance, it is crucial to guar- antee the safety of an agent during training as well as deployment (e.g., a robot should avoid taking actions - exploratory or not - which irrevocably harm its hard- ware).To incorporate safety in RL, we derive algorithms under the framework of constrained Markov decision processes (CMDPs), an extension of the standard Markov decision processes (MDPs) augmented with constraints on expected cu- mulative costs.Our approach hinges on a novel Lyapunov method.We define and present a method for constructing Lyapunov functions, which provide an ef- fective way to guarantee the global safety of a behavior policy during training via a set of local linear constraints.Leveraging these theoretical underpinnings, we show how to use the Lyapunov approach to systematically transform dynamic programming (DP) and RL algorithms into their safe counterparts.To illustrate their effectiveness, we evaluate these algorithms in several CMDP planning and decision-making tasks on a safety benchmark domain.Our results show that our proposed method significantly outperforms existing baselines in balancing con- straint satisfaction and performance.