We care about entropy in machine learning for two main reasons. First, because we want machines to teach us something new - particularly in situations where personally we couldn't derive any significant meaning. Read Entropy in Machine Learning Lesson ...
Althoughentropyhas a narrow scientific meaning, its broader meaning is more commonly used. "Boredom is a sign of a bigger problem than just idleness; it's a lack of interests and passions." And it's this state of entropy that wastes your time and drives you deeper into your worst state....
The goal of the paper is to give the physical meaning of these mutual relations. Here we take the concept of linear stationary filter and loss of entropy in it as basic. In the first part of the paper the account is given for the case of discrete time, and in the second part we ...
If we naively calculate the predictive entropy directly from the probabilities of the generated sequence of tokens, we conflate the uncertainty of the model over the meaning of its answer with the uncertainty over the exact tokens used to express that meaning. For example, even if the model is...
Next, we will plot the loss to see whether the model is improving – meaning the error decreases with each epoch until it can no longer improve. # plotting the loss of the models fig, ax = plt.subplots(figsize=(8,5)) plt.plot(history.history['loss']) plt.plot(history.history['val...
This can be given a direct interpretation, which is connected with the meaning of I(X,Y|f). Whenever random variable Y depends on X, Eq. (2.3.102) prescribes the emission of symbols according to the probability distribution of Eq. (2.3.97), where f maximizes the mutual information I(...
My Own Meaning – A Writing Workshop Reflection December 21, 2012byJen Serendipity I don’t believe things happen for a reason, or are meant to be. Things just happen. When I’m open to new experiences, sometimes those things bring delight. One Sunday afternoon, I brought the children to...
One should note that DFT, first-principles and ab initio calculations are used interchangeably as they have the same meaning in this work. In the past decade, fitting ab initio PESs with machine learning (ML) algorithms have gained increasing momentum, and the ML-fitted PESs are termed machine...
Information in information theory is not related to meaning. Shannon wrote: “The semantic aspects of communication are irrelevant to the technical ones.” Information is a measure of the freedom we have when choosing a message. So, it is not about what is being transmitted, but what could be...
This can be given a direct interpretation, which is connected with the meaning of I(X,Y|f). Whenever random variable Y depends on X, Eq. (5) prescribes the emission of symbols according to the probability distribution of Eq. (1), where f maximizes the mutual information I(X,Y|f). ...