Row 49971

Row ID: 49971 | Dataset Entry | Axioma AXP Content Repository

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I know linear neural networks are reverse engineerable but are non linear neural networks reverse engineerable as well?

So far I've only found answers that say that it is very, very complex.

This is what I'm trying to do:

I want to get the correct values of the neural network(weights, biases etc) by reverse engineering. So that the learning time drops heavily.

Right now, I have an neural network with 2 inputs, 1 output and 2 hidden layers each 8 neurons which I'm trying to learn to perform addition.

So far after 100k epoch's \~85 minutes it is very, very, very, very, very, very close. But it's still \~0,000100000 away from it.

For this run I had an very, very, very small data set with only 15 addition problems.

So if anyone knows how to get the correct values of the neural network within a few epochs please help me!

FieldValue
text I know linear neural networks are reverse engineerable but are non linear neural networks reverse engineerable as well? So far I've only found answers that say that it is very, very complex. This is what I'm trying to do: I want to get the correct values of the neural network(weights, biases etc) by reverse engineering. So that the learning time drops heavily. Right now, I have an neural network with 2 inputs, 1 output and 2 hidden layers each 8 neurons which I'm trying to learn to perform a…
label r/chatgpt
dataType post
communityName r/ChatGPT
datetime 2024-05-22
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url_encoded Z0FBQUFBQm5Lak9oRFRxY0cxS0ZYVDJkU0JySXhhOTRLcERLZEpBSzhCaHMyYXFqMFJ0TUJFemNIS2Z5ZW5wR2hpRFJ0Ql9zM3k0MEw4Q044YmxzVTdxNTFWeVFYWTBFM0ttaml0Z1Y0Y05BZnE2MF8tNDRVYWM1aHJtcTNXNEMya0w0cWxMTmRaVFJnZE9hSTVFUWFBVENid3ZVMGN1UVNWV0E0TFVjRDRVU0R2QTNrVVBiV3UzTEpjSW1QU0FoLWphWnlzYXloc0dN

Raw Record

{
  "text": "I know linear neural networks are reverse engineerable but are non linear neural networks reverse engineerable as well?\n\nSo far I've only found answers that say that it is very, very complex.\n\nThis is what I'm trying to do:\n\nI want to get the correct values of the neural network(weights, biases etc) by reverse engineering. So that the learning time drops heavily.\n\nRight now, I have an neural network with 2 inputs, 1 output and 2 hidden layers each 8 neurons which I'm trying to learn to perform addition.\n\nSo far after 100k epoch's \\~85 minutes it is very, very, very, very, very, very close. But it's still \\~0,000100000 away from it. \n\nFor this run I had an very, very, very small data set with only 15 addition problems.\n\nSo if anyone knows how to get the correct values of the neural network within a few epochs please help me!\n\n",
  "label": "r/chatgpt",
  "dataType": "post",
  "communityName": "r/ChatGPT",
  "datetime": "2024-05-22",
  "username_encoded": "Z0FBQUFBQm5Lak1TR0V2OEhtck42NGh2MmFZdjFEbXJNS1NwX3UyVnVxLWsxMEEzSDE2S0NwdUVKc1Z0alExX0d6YWdWLXhMVXN0Q2FPdEN4a0pmd0VFTXFhZVFDVmlKdFE9PQ==",
  "url_encoded": "Z0FBQUFBQm5Lak9oRFRxY0cxS0ZYVDJkU0JySXhhOTRLcERLZEpBSzhCaHMyYXFqMFJ0TUJFemNIS2Z5ZW5wR2hpRFJ0Ql9zM3k0MEw4Q044YmxzVTdxNTFWeVFYWTBFM0ttaml0Z1Y0Y05BZnE2MF8tNDRVYWM1aHJtcTNXNEMya0w0cWxMTmRaVFJnZE9hSTVFUWFBVENid3ZVMGN1UVNWV0E0TFVjRDRVU0R2QTNrVVBiV3UzTEpjSW1QU0FoLWphWnlzYXloc0dN"
}
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