Zvi M. Kedem

Zvi M. Kedem, Kirthi Krishna Muntimadugu

Inaccurate circuits make possible the conservation of limited resources, such as energy. But effective design of such circuits requires an understanding of resulting tradeoffs between accuracy and design parameters, such as voltages and speed of execution. Although studies of tradeoffs have been done on specific circuits, the applicability of those studies is narrow. This paper presents a comprehensive and mathematically rigorous method for analyzing a large class of inaccurate circuits for addition. Furthermore, it presents new, fast algorithms for the computation of key statistical measures of inaccuracy in such adders, thus helping hardware architects explore the design space with greater confidence.

Rohit R Muthyala, Davi Geiger, Zvi M. Kedem

Counting the number of clusters, when these clusters overlap significantly is a challenging problem in machine learning. We argue that a purely mathematical quantum theory, formulated using the path integral technique, when applied to non-physics modeling leads to non-physics quantum theories that are statistical in nature. We show that a quantum theory can be a more robust statistical theory to separate data to count overlapping clusters. The theory is also confirmed from data simulations.This works identify how quantum theory can be effective in counting clusters and hope to inspire the field to further apply such techniques.