Although theories of emotion associate negative emotional symptoms with cognitive biases in information processing, they rarely specify the details. Here, we characterize cognitive biases in information processing of pleasant and unpleasant information, an ...
While technology is often claimed to be “democratizing”, the technologizing of society has more often yielded undemocratic or even anti-democratic outcomes. Is technology fundamentally at odds with democracy, or is it merely a rich and infinitely-adaptable ...
A fundamental problem arising in many areas of machine learning is the evaluation of the likelihood of a given observation under different nominal distributions. Frequently, these nominal distributions are themselves estimated from data, which makes them s ...
The likelihood function is a fundamental component in Bayesian statistics. However, evaluating the likelihood of an observation is computationally intractable in many applications. In this paper, we propose a non-parametric approximation of the likelihood ...
News entities must select and filter the coverage they broadcast through their respective channels since the set of world events is too large to be treated exhaustively. The subjective nature of this filtering induces biases due to, among other things, res ...
To investigate the mechanisms of perceptual learning, we recently introduced a paradigm in which incorrect, reverse feedback followed after some but not all vernier presentations. This feedback paradigm exerted a strong effect on performance that seemed to ...
