Caches consume a significant amount of power in modern microprocessors while also constraining clock frequency due to their access time. In this paper, we propose a bit-sliced cache, which reduces dynamic power consumption and achieves higher clock frequency as well as increased cache throughput while adding little complexity. Our bit-sliced cache reduces 20-40% of dynamic power for a variety o...

Suppose we are given a proof of knowledge P in which a prover demonstrates that he knows a solution to a given problem instance. Suppose also that we have a secret sharing scheme S on n participants. Then under certain assumptions on P and S, we show how to transform P into a witness indistinguishable protocol, in which the prover demonstrates knowledge of the solution to some subset of n probl...

An incomplete taxonomy is proposed for the knowledge of actions a computer must have if it is to understand stories about people performing these actions. The classification is along two dimensions , Force-why a person should follow the rule, and Form-what the rule looks like. For the most part it seems that any force type may combine with any form type in producing a rule. One example, how to ...

We consider n selfish agents or players, each having a load, who want to place their loads to one of two bins. The agents have an incomplete picture of the world: They know some loads exactly and only a probability distribution for the rest. We study Nash equilibria for this model, we compute the Price of Anarchy for some cases and show that sometimes extra information adversely affects the Div...

This paper proposes to enhance similarity-based classification by virtual attributes from imperfect domain theories. We analyze how properties of the domain theory, such as partialness and vagueness, influence classification accuracy. Experiments in a simple domain suggest that partial knowledge is more useful than vague knowledge. However, for data sets from the UCI Machine Learning Repository...

This paper proposes to enhance similarity-based classification by virtual attributes from imperfect domain theories. We analyze how properties of the domain theory, such as partialness and vagueness, influence classification accuracy. Experiments in a simple domain suggest that partial knowledge is more useful than vague knowledge. However, for data sets from the UCI Machine Learning Repository...

We present two versions of alternating-time temporal logics with uniform strategies, interpreted in a novel way on transition systems for modelling situations in which agents with partial information interact to determine the way the system updates. The logic uATL allows us to model what properties agents can enforce when they act according to strategies based on their knowledge, but we show th...

We describe a scheme for reliable and accurate surface reconstruction when the stereoscopic images contain only ne texture and no stable high level features. The approach uses partial shape information to improve the reliability of the surface computation process { by rst tting an approximate, global, parametric model, and then reening this model via local correspondence processes. A simple yet...

Bayesian and graph models of student knowledge assessment have made significant progress in the last decadeand are challenging the more traditional IRT approach for CAT applications. We review some of the most prominent frameworks in Bayesian knowledge assessment and how they compare to IRT and introduce one such framework in the family of Bayesian models, the POKS (Partial Order Knowlege Struc...

When firms form an alliance, it often involves one firm acquiring an equity stake in its alliance partner. Such an alliance lessens the competition, but induces knowledge transfer within the alliance. This paper explores oligopoly models that capture this important link between partial equity ownership (PEO) and knowledge transfer. We consider an industry consisting of three firms, where firm 1...