Row 6746

Row ID: 6746 | Dataset Entry | Axioma AXP Content Repository

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i need to understand

1. how are these loss landscape formed from cost/loss function?

2. do these change as the network is training or is it fixed per dataset

3. what are those tiny balls rolling down hill? why is it two three balls rolling down hill ? i belive random seed init will init them anywhere but they roll down to reduce cost

4. if we already know the loss landscape can we not just calculate the bottom point where cost is lowest instead of figuring out step by step sgd

5. do activation funtion have any effect on this landscape like parabolic depth vs sharp depth?

sorry im just confused , anyone help!

FieldValue
text i need to understand 1. how are these loss landscape formed from cost/loss function? 2. do these change as the network is training or is it fixed per dataset 3. what are those tiny balls rolling down hill? why is it two three balls rolling down hill ? i belive random seed init will init them anywhere but they roll down to reduce cost 4. if we already know the loss landscape can we not just calculate the bottom point where cost is lowest instead of figuring out step by step sgd 5. do act…
label r/deeplearning
dataType post
communityName r/deeplearning
datetime 2024-05-13
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Raw Record

{
  "text": "i need to understand \n\n1. how are these loss landscape formed from cost/loss function? \n\n2. do these change as the network is training or is it fixed per dataset \n\n3. what are those tiny balls rolling down hill? why is it two three balls rolling down hill ? i belive random seed init will init them anywhere but they roll down to reduce cost \n\n4. if we already know the loss landscape can we not just calculate the bottom point where cost is lowest instead of figuring out step by step sgd\n\n5. do activation funtion have any effect on this landscape like parabolic depth vs sharp depth?\n\nsorry im just confused , anyone help!",
  "label": "r/deeplearning",
  "dataType": "post",
  "communityName": "r/deeplearning",
  "datetime": "2024-05-13",
  "username_encoded": "Z0FBQUFBQm5LakwzVk8xUVhwNnRyV0ZaeXI2LUJoZTZZSl94ejhKVlZLaUU0UHNITTI2TWlBUy1Ccm9BZnpNRDNaVEVfbk93SUJCcndnbDZXMHFxX1BzQzZVd0VDS1Zlb1E9PQ==",
  "url_encoded": "Z0FBQUFBQm5Lak9HV1dRZnhnS0Nyd2w5T1c4SGVVd0luXzBDQkFsZkpBSmVsaUxRNlVidmhiTFZRZXBobC1qbDNuRzlSa1RzN1JpTlR6VHJuTHJ0VWFUWURON25jY0hPUDlBX3FDSTRxX2V5eFM3d3V6S0FnbkpDWVhPQzdyTTJSV0Jhd0RFdHFLT0ZZYXJSUllsN3FtM1pqLXpfQlBFVm13M2hoLXNWTUNjX2pSQ2JPTVI0VkJsWHpTb1ZwWFBfcVB2bVM0QnpDNE9GQjVQMXJYbHlYcFdQMzFleU9iazlxZz09"
}
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