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Alex Smola

Personal blog · blog.smola.orgdataai

Alex Smola's personal blog at blog.smola.org covers data and ai. Since 2010, 6 different Hacker News readers have linked it 7 times. It is still writing: the last post was on 2026-08-09, and you can follow it by feed.

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7mentions?
6HN people?
2010–2021first – last linked?
Links on Hacker News per year · peak 3 in 2011

Too few sampled comments (2) to say how often HN recommends it.?

Why HN links it

HN readers link Alex Smola's blog for machine learning and statistics material, such as numerical stability with probabilities and experimental design for data science projects. The comments cite posts as sources rather than praising them.

Summarised by Claude from a sample of 2 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.

What Hacker News says?

  1. A similar trick is used for a different reason in statistical and probabilistic calculations -- for numerical stability rather than performance. Suppose you have n probabilities p_1, ..., p_n. Each p_i is a real number in the interval [0, 1] . Often you want to multiply probabilities to compute prod_i p_i . Probabilities p_i can be tiny floating point values (very close to zero) and if n, the number of factors, is l…

    Comment linking /post/987977550/log-probabilities-semirings-and-floating-point

    on “Reverse-engineering the Yamaha DX7 synthesizer's sound chip from die photos”
  2. Submitted Leaving CMU as a story · 75 points

    HN discussion
  3. Maybe one problem is that some projects naively try to start at "fit a model to whatever data we've got" when perhaps they would be better off starting with a statistical experimental design perspective, and thinking about how exactly the data would need to be collected https://en.wikipedia.org/wiki/Design_of_experiments Here's one detailed anecdote of how projects can fail: > Imagine you want to design some algorit…

    Comment linking /post/4110255196/real-simple-covariate-shift-correction

    on “Ask HN: Why AI and Data Science projects have a high risk of failure?”
  4. Submitted Yahoo's hadoop-based Latent Dirichlet Allocation On Github as a story · 55 points

    HN discussion
  5. Submitted Log-probabilities, semirings and floating point numbers as a story · 35 points

    HN discussion
  6. Submitted Adventures in Data Land as a story · 2 points

    HN discussion
  7. Submitted Hashing for Collaborative Filtering as a story · 2 points

    HN discussion

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