It is believed that CE based variable selection can help to build more explainable models.
We propose a new benchmark corpus to be used for measuring progress in statistical language modeling.
Ranked #22 on Language Modelling on One Billion Word
Given a dataset of careers and incomes, how large a difference of income between any pair of careers would be?
We analyze the histogram of the likelihoods of the input images using the generalized mean, which measures the model's accuracy as a function of the relative risk.
The estimation of an f-divergence between two probability distributions based on samples is a fundamental problem in statistics and machine learning.
Second, we develop an Approximate Bayesian Computation framework to use our model for analyzing genetic data.
Populations and Evolution Probability Applications 92D25, 60J80, 92D15, 60J75
However, the performance of the variational approach depends on the choice of an appropriate variational family.
The state of the art in machine translation (MT) is governed by neural approaches, which typically provide superior translation accuracy over statistical approaches.
A key contribution is that the overall aggregated trading strategies are tested for statistical arbitrage using a novel hypothesis test proposed by Jarrow et al. (2012) on both daily sampled and intraday time-scales.
Sequence models assign probabilities to variable-length sequences such as natural language texts.