Intergenerational Learning Program: A Bridge between Generations

Sandy Bridge Spans Generations

Intel’s processor clock has tocked, delivering a nextgeneration architecture for PCs and servers. At the recent Intel Developer’s Forum (IDF), the company unveiled its Sandy Bridge processor architecture, the next tock in its tick-tock roadmap. The new CPU is an evolutionary improvement over its predecessor, Nehalem, tweaking the branch predictor, register renaming, and instruction decoding. Th...

Intergenerational relationship quality across three generations.

OBJECTIVES Studies of intergenerational relationship quality often include one or two generations. This study examined within-family differences and similarities or transmission of positive and negative relationship quality across three generations. METHOD Participants included 633 middle-aged individuals (G2; 52% women, ages 40-60 years), 592 of their offspring (G3; 53% daughters; ages 18-41...

Building a Bridge between Pointer Aliases and Program Dependences

In this paper we present a surprisingly simple reduction of the program dependence problem to the may-alias problem. While both problems are undecidable, providing a bridge between them has great practical importance. Program dependence information is used extensively in compiler optimizations, automatic program parallelizations, code scheduling in super-scalar machines, and in software enginee...

BRIBIP: A Bridge Bidding Program

capable of making decisions in an environment of imperfect information. It is frequently necessary that such decisions be made in real life-as, for example, the decisions made in the day-today running of a firm. As a paradigm of such situations, the game of Contract bridge (3) was chosen, for several reasons: 1) Despite being a game of imperfect information, it is well-defined: in particular, t...

Intergenerational Justice Review Foundation for the Rights of Future Generations

Duality Between Learning Machines: A Bridge Between Supervised and Unsupervised Learning

We exhibit a duality between two perceptrons which allows us to compare the theoretical analysis of supervised and unsupervised learning tasks. The rst perceptron has one output and is asked to learn a classiication of p patterns. The second (dual) perceptron has p outputs and is asked to transmit as much information as possible on a distribution of inputs. We show in particular that the maximu...