680 research outputs found
The Fundamental Nature of the Log Loss Function
The standard loss functions used in the literature on probabilistic
prediction are the log loss function, the Brier loss function, and the
spherical loss function; however, any computable proper loss function can be
used for comparison of prediction algorithms. This note shows that the log loss
function is most selective in that any prediction algorithm that is optimal for
a given data sequence (in the sense of the algorithmic theory of randomness)
under the log loss function will be optimal under any computable proper mixable
loss function; on the other hand, there is a data sequence and a prediction
algorithm that is optimal for that sequence under either of the two other
standard loss functions but not under the log loss function.Comment: 12 page
Technology of bot creation for wide class of logic approach-based applications
The article proposes information technology for computer-aided design and
implementation of bots on the base of logical approach. The general approach to creation of
bots with use of a complex of logical and linguistic models is described. The general scheme
of work of the web-oriented system with use of a chat bot is developed. The model of logic of
actions is presented and the theorem proving method what can be used for the formal
description of process of creation of bots is described. An example of using a logical model to
create a bot is described
Prediction with Expert Advice under Discounted Loss
We study prediction with expert advice in the setting where the losses are
accumulated with some discounting---the impact of old losses may gradually
vanish. We generalize the Aggregating Algorithm and the Aggregating Algorithm
for Regression to this case, propose a suitable new variant of exponential
weights algorithm, and prove respective loss bounds.Comment: 26 pages; expanded (2 remarks -> theorems), some misprints correcte
Para-transit and micro-transportation in the transport service provision system during the military period
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