jimfleming

9 ms·

31.
by jimfleming 8y ago
To draw too many parallels here would be like comparing stick figures to still life paintings and proclaiming "They're both flowers!" While it might be true you won't learn much about still life paintings from stick figu
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Evolving Alient Corals(joelsimon.net)
2 points by jimfleming 9y ago|0 comments
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by jimfleming 9y ago
SHAP[0] is another model-agnostic method for interpreting predictions. It's a bit newer and builds on LIME, Shapely, and a few other works. There's also an associated tool[1]. [0] https://arxiv.org/abs/1705.07
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by jimfleming 9y ago
If I'm understanding correctly (I haven't read it in depth yet): Points are processed as local clusters. Each cluster of points is ordered according to a transformation matrix X. This produces a "canonical" ordering so t
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by jimfleming 9y ago
If you're interested in this, RVO (reciprocal velocity obstacles) is another multi-agent system for collision avoidance with some good reading[0][1][2]. I've been porting the RVO2 library to Python3 over break and it's incred
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by jimfleming 9y ago
Adversarial examples don't really support the claim that deep models are just memorizing examples. If they were, they wouldn't generalize to unseen examples at all. However, the human brain is also susceptible to adversarial examp
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by jimfleming 9y ago
It's more like giving you a bag of random house numbers and instructing you to place the numbers on the correct houses in an area you've never been to before. An instructor teaches you where some of the numbers go, and you can mem
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by jimfleming 9y ago
That is not a conclusion that can be drawn from the findings in the paper. While the models they evaluate can achieve zero training error on random labels, the test error is obviously not zero: it doesn't generalize at all. However, tr
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Show HN: TFStage: TensorFlow Project Scaffolding(github.com)
4 points by jimfleming 9y ago|0 comments
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TFStage: TensorFlow Project Scaffolding(github.com)
2 points by jimfleming 9y ago|0 comments
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by jimfleming 9y ago
Regarding your edit, the authors of the paper in question focus on FNNs and note the reason in the paper: > Both RNNs and CNNs can stabilize learning via weight sharing, therefore they are less prone to these perturbations. In contrast,
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How I Built a Reverse Image Search with Machine Learning and TensorFlow: Part 1(codementor.io)
3 points by jimfleming 9y ago|0 comments
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by jimfleming 9y ago
Here imperative style means you can use language constructs in e.g. Python, such as if-statements and while-loops, to directly construct models. TensorFlow, Theano, and other graph-based frameworks typically require creating branches and lo
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Running TensorFlow with GPU Support on Kubernetes(medium.com)
2 points by jimfleming 10y ago|0 comments
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by jimfleming 10y ago
The sparsity encouraged by ReLUs is one reason they are used but not to the exclusion of all other activations. ReLU variants can indeed outperform standard ReLU[0] but sometimes sparsity is a desired property. For example, in generative mo
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by jimfleming 10y ago
Nature uses something like STDP (spike timing dependent plasticity), where the change in a synapse strength is proportional to the sign and delta time of the last spike at each end of the synapse. You can approximate something like backprop
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by jimfleming 10y ago
The reasons to use ReLUs are sparsity and improved gradient flow. ReLUs encourage sparsity because when the input to the ReLU is less than 0 as the activation becomes 0. This means some fraction of activations in a given layer will be omitt
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by jimfleming 10y ago
Titan X is the product line which has multiple generations, with the Pascal architecture being the latest.
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Show HN: Recurrent Entity Networks with TensorFlow(github.com)
37 points by jimfleming 10y ago|0 comments
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by jimfleming 10y ago
This looks like a great summary, thank you. My reading of [2] is that the model only needs to be retrained if the environmental boundary changes. For example, to handle objects that do not fit within the current boundary. Since I imagine sc
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by jimfleming 10y ago
A GRU is more like a simplification of the ideas in LSTM, rather than a building block. At a high level, it uses the hidden state as the memory of the cell (rather than a separate cell state) and it uses a single "update" gate, me
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Show HN: Walkthrough of Symbolic Differentiation(jimfleming.me)
1 points by jimfleming 10y ago|0 comments
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Show HN: Implementing (parts of) TensorFlow (almost) from Scratch(jimfleming.me)
1 points by jimfleming 10y ago|0 comments
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by jimfleming 10y ago
Spent some time experimenting with Numerai. Really fun competition, clean (encrypted) dataset, and Bitcoin payouts. I wrote about my experience and open-sourced all of the models here[0] if you're looking to get started. [0] https:&#x
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by jimfleming 10y ago
Interesting, I read this as encouragement for founders rather than complaining. The point is that there will always be haters, so being discouraged by them or complaining isn't fruitful.
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by jimfleming 10y ago
I'm honestly not sure. I think it's serious (they seem pretty cautious in their statements which you wouldn't do in satire). But I did find it interesting regardless of it's seriousness.
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People for the Ethical Treatment of Reinforcement Learners(petrl.org)
1 points by jimfleming 10y ago|2 comments
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by jimfleming 10y ago
You should have a look a PETRL[0]: People for the Ethical Treatment of Reinforcement Learners :) [0] http://petrl.org/
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by jimfleming 10y ago
It was an off-hand remark. I'm aware of the landscape, though perhaps slightly more optimistic. The first goal is simple enough and largely underway with the Gym. Significant progress has been made on #3 and #4 just in the last year bu
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by jimfleming 10y ago
This is great! The goals seem reasonably ambitious and mostly doable over a few years. I am surprised by #2: "Build a household robot". It's my understanding that efficient actuation and power are largely unsolved problems ou

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