We identify the trust management problem as a distinct and important component of security in network services. Aspects of the trust management problem include formulating security policies and security credentials, determining whether particular sets of credentials satisfy the relevant policies

“Having looked at monetary policy from both sides now, I can testify that central banking in practice is as much art as science. Nonetheless, while practicing this dark art, I have always found the science quEite useful.” 2 Alan S. Blinder

This paper reviews recent research that grapples with the question: What happens after an exogenous shock to monetary policy? We argue that this question is interesting because it lies at the center of a particular approach to assessing the empirical plausibility of structural economic models

I develop a general equilibrium model with sticky prices, credit constraints, nominal loans and asset prices. Changes in asset prices modify agents ’ borrowing capacity through collateral value; changes in nominal prices affect real repayments through debt deflation. Monetary policy shocks move

Andrew Warner for generously sharing their data with us. We are particularly grateful to Ben-David, Frankel, Romer, Sachs, Warner and Romain Wacziarg for helpful e-mail exchanges. We have benefited greatly from discussions in seminars at the University of California at Berkeley,

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We propose a new approach to reinforcement learning for control problems which combines value-function approximation with linear architectures and approximate policy iteration. This new approach

Current standard security practices do not provide substantial assurance that the end-to-end behavior of a computing system satisfies important security policies such as confidentiality. An end-to-end confidentiality policy might assert that secret input data cannot be inferred by an attacker

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classification where the there is a large number of classes and a huge number of relevant features needed to distinguish between them. We propose an approach that utilizes the hierarchical topic structure to decompose the classification task into a set of simpler problems, one at each node in the classification