Author Archives: Amir massoud Farahmand

Tumblr and I

I have used Tumblr microblogging service to organize my machine learning-related stuff for a while. You can see it here. Although I really like the ease of tumbling, there is a big problem here: it doesn’t naturally come with searching … Continue reading

Posted in miscellaneous | 1 Comment

Approximate Dynamic Programming with Gaussian Processes

Marc Deisenroth, Jan Peter, and Carl E. Rasmussen, “Approximate Dynamic Programming with Gaussian Processes,” ACC 2008. Similar to what we’ve done, without proofs. Formalized in a Bayesian setting (GP). [ | | | | | | | | | | … Continue reading

Posted in Gaussian Processes, Papers, Reinforcement Learning | Leave a comment

Life Goes on in Tehran

Take a look at this photoblog: Life Goes on in Tehran. I like it because it is close to what I’ve seen there (and it is not the same as what I’ve seen on CNN!). [ | | | | … Continue reading

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Evidence Contrary to the Statistical View of Boosting

In this recent JMLR paper, David Mease and Abraham Wyner experimentally show that the statistical viewpoint to boosting, which is defined as a stagewise optimization problem, does not give a sufficient interpretation for understanding the behavior of boosting algorithms (I … Continue reading

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Good Writing by Marc H. Raibert

In this short piece of advice, Marc H. Raibert tells you about the way you can produce good writings. His advices are simple. He foremost suggestion is that you must believe you can write produce a good writing, and for … Continue reading

Posted in Effective Writing and Presentation | 3 Comments

Fractional Calculus and more

I found this paper[1] about the fractional variational principle. I didn’t know anything about fractional derivative/integration before taking a look at this paper. If you like to know more, you can check here. It gives the basic ideas. Beside this … Continue reading

Posted in Papers | 2 Comments

Lectures Notes on Convex Analysis [+ Optimization]

Christian L√ČONARD, “A Set of Lecture Notes on Convex Optimization with Some Applications to Probability Theory“, Lecture Notes, 2006. [ | | | | | | | | | | | | | | | | | | | | … Continue reading

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Probability Inequalities and Machine Learning

Michael Steele has this course on “Probability Inequalities and Machine Learning”. This is the kind of course I’ve really liked to take. Anyway, for most of us who cannot attend the course, following his suggested reading may help somewhat. There … Continue reading

Posted in Boosting, Concentration Inequalities, To Read | Leave a comment

Walter J. Freeman, “Happiness doesn’t Come in Bottles”

Have you ever felt that you are not happy from you life even if you have *objectively* successful life (e.g. a lot of money, many publications, and etc.)? And have you asked yourself what was wrong with your life? Accidentally, … Continue reading

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Have you seen Scholarpedia? It is a wiki project on scientific subjects that are written by experts of the field and are peer reviewed by others. It means that you will know who is actually writing the most part of … Continue reading

Posted in Uncategorized | 2 Comments