Abstract. A well-known result by Stein shows that regularized estimators with small bias often yield better estimates than unbiased estimators. In this paper, we adapt this spirit ...
Parameter variation is detrimental to a processor’s frequency and leakage power. One proposed technique to mitigate it is Fine-Grain Body Biasing (FGBB), where different parts o...
Radu Teodorescu, Jun Nakano, Abhishek Tiwari, Jose...
In this paper, we investigate how deviation in evaluation activities may reveal bias on the part of reviewers and controversy on the part of evaluated objects. We focus on a `data...
A major problem in machine learning is that of inductive bias: how to choose a learner's hypothesis space so that it is large enough to contain a solution to the problem bein...
Abstract. Taking neuromodulation as a mechanism underlying emotions, this paper investigates how such a mechanism can bias an artificial neural network towards exploration of new ...