5 ms·

Slightly off topic, but I hate how publications are written. It seems like authors are purposely using big words and sentences that are often 5-6 lines long in

• amelius 10y ago
  Then here's a challenge: could you write the abstract of the article in "simple English", without changing the meaning?
  • unfamiliar 10y ago
    Here's my attempt; not a huge number of changes because it was not too bad to begin with, but with slightly less self-indulgent language, and a lot of the jargon has to stay (partly because I don't know the field): Neural machine learning methods, such as deep neural networks (DNN), have achieved remarkable success in a number of complex data processing tasks. These methods have arguably had their strongest impact on tasks such as image and audio processing - areas where humans have always performed better than conventional algorithms. In contrast to biological neural systems, which are capable of learning continuously, deep artificial networks have a limited ability for incorporating new information after a network has been trained. As a result, continuous learning methods could be very helpful in allowing deep networks to handle data sets which change over time. Here, inspired by the process of adult neurogenesis in the hippocampus, we investigate how adding new neurons to artificial neural networks can allow them to acquire new information, while preserving what they have already learned. Our results on the MNIST handwritten digit dataset and the NIST SD 19 dataset, which includes lower and upper case letters and digits, show that neurogenesis looks like a good approach for tackling the "stability-plasticity dilemma" that has been a problem for adaptive machine learning algorithms for some time. As an academic, I tend to agree that we frequently feel compelled to apply more verbosity than is strictly required in order to communicate the intended semantic constructs.
    • SubiculumCode 10y ago
      Academic writing avoids using periods. Unfortunately.
  • hmate9 10y ago
    Problem: current methods for training neural networks cannot learn continuously. Once they have been trained, they cannot easily learn new information. We propose a method to fix this problem. Our algorithm adds new neurons to the neural network which allows it to learn new information, while maintaining everything it already "knows". I showed this to my father, a surgeon, and he said he understood it. But not the original abstract.
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• bicubic 10y ago
  A lot of the time the verbosity isn't so much to sound more clever as it is to be very specific and explicit about what the author is trying to convey. There's a lot of changing assumed knowledge and jargon in various fields and our use of language changes over time. The publication writing style is an attempt to factor that out.
  • rdlecler1 10y ago
    That's what an appendix is for. Letters to Nature are 1500 words. You'd be surprised how effective that forcing function is. Not only do you preserve meaning, but you can convey it better because it respects the readers cache size limitations.
    • bicubic 10y ago
      By that analogy, an appendix is even worse; requiring a jump and a complete cache flush for the reader :p
• shmageggy 10y ago
  Although I just glanced at a few parts of this, I did not find it to be poorly written. Can you give an example where you thought it was too verbose or unnecessarily complex?
  • hmate9 10y ago
    For example in the abstract: "adding new neurons to deep layers of artificial neural networks in order to facilitate their acquisition of novel information while preserving previously trained data representations" Nobody talks like this. In my head I read this sentence and I have to translate it to "we add extra neurons to existing networks so they can learn new information while remembering everything it already knows".
    • bmh100 10y ago
      However, your statement is actually vague and ambiguous. "Extra neurons"? Input layer? Output layer? Just before a final, fully-connected layer? Somewhere in between? "Everything it already knows"? What does it know? Character probabilities, like a charnn? Image categories like in a CNN? Input distributions, like a GAN? From the abstract, I can immediately tell that this paper is about modifying deep auto-encoders in the hidden layers. From that, I can immediately understand that the paper is not about adapting to new input formats or output formats, but instead about inputs from a new distribution but in the same format. The author's intended audience, researchers and academics, do talk like this. They do so because it is quickly understandable and actually information dense, as indicated in my above paragraph.
      • bjterry 10y ago
        Anytime someone uses the phrase "in order to facilitate" they are being more verbose than is necessary in order to signify their greater erudition. There is no meaningful semantic or technical distinction between "in order to facilitate" and "to help."
        • bmh100 10y ago