The guessing of a function behind a discrete mapping between nite spaces using only the information provided by positive examples is shown to be in principle optimally handled by a lookup table combined with a random process. We explore the implications of this result for the construction of intelligent approxi-mators.

Researchers are rapidly developing new automated techniques to scale political speech on an ideological dimension. Yet, the task has proven difficult across many settings. Political advertisements, in particular, have eluded such efforts. Candidates air relatively few ads, containing limited policy information, and there is little agreement about how to model political speech in the campaign, m...

The guessing of a function behind a discrete mapping between nite spaces using only the information provided by positive examples is shown to be in principle optimally handled by a lookup table combined with a random process. We explore the implications of this result for the construction of intelligent approximators.

94.7 Steganography...................................................................... 1260 94.8 Key Distribution .................................................................. 1260 94.9 Key Management ................................................................. 1260 94.10 Public versus Proprietary Algorithms and Systems.......... 1260 94.11 Classic Attacks..............................

Knowledge discovery in biomedical data using supervised methods assumes that the contain structure relevant to class if a classifier can be trained assign case correct better than by guessing. In this setting, acceptance or rejection of scientific hypothesis may depend critically on ability classify cases randomly, without high classification performance being primary goal. Random forests are o...

This study investigated the potential of recognising arousal in motor activity collected by wrist-worn accelerometers. We hypothesise that emotional emerges from generalised central nervous system which embeds affective states within activity. formulate detection as a statistical problem separating two sets - under and without arousal. propose novel test regime based on machine learning assumin...

Guessing random additive noise decoding (GRAND) is a noise-centric method, which suitable for low-latency communications, as it supports error correction codes that generate short codewords. GRAND estimates transmitted codewords by guessing the patterns altered them during transmission. The process requires testing of are arranged in increasing order Hamming weight. This approach fitting binary...

We develop an information-theoretic view of the stochastic block model, a popular statistical model for the large-scale structure of complex networks. A graph G from such a model is generated by first assigning vertex labels at random from a finite alphabet, and then connecting vertices with edge probabilities depending on the labels of the endpoints. In the case of the symmetric two-group mode...

We develop an information-theoretic view of the stochastic block model, a popular statistical model for the large-scale structure of complex networks. A graph G from such a model is generated by first assigning vertex labels at random from a finite alphabet, and then connecting vertices with edge probabilities depending on the labels of the endpoints. In the case of the symmetric two-group mode...

Many researchers have investigated implicit and explicit aspects in human behaviors. The Sequence Learning (SL) paradigm is one of the approaches used to investigate these aspects. The learning performance in SL tasks has been broadly studied. However, the guessing phenomenon has not yet been investigated, although it plays important part in a variety of human behaviors. The SL paradigm was ada...