Row 24931

Row ID: 24931 | Dataset Entry | Axioma AXP Content Repository

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I was reading through [https://arxiv.org/abs/1703.04730](https://arxiv.org/abs/1703.04730) and was looking into the derivation of equation (1) given in the Appendix A. I understand how we get equations (6)-(10), but the jump from equation (10) to (11) is confusing me.

I also don't really get how you'd 2nd order Taylor expand the RHS of equation (10), as it's a vector-to-vector function. Do they mean 2nd order Taylor expanding the perturbed loss function R(theta) + epsilon L(theta)? If this is the case, shouldn't the hessian should be part of a quadratic form? In equation (11) they're only right multiplying by delta\_epsilon (not left multiplying), so it's not in this form.

FieldValue
text I was reading through [https://arxiv.org/abs/1703.04730](https://arxiv.org/abs/1703.04730) and was looking into the derivation of equation (1) given in the Appendix A. I understand how we get equations (6)-(10), but the jump from equation (10) to (11) is confusing me. I also don't really get how you'd 2nd order Taylor expand the RHS of equation (10), as it's a vector-to-vector function. Do they mean 2nd order Taylor expanding the perturbed loss function R(theta) + epsilon L(theta)? If this is t…
label r/machinelearning
dataType post
communityName r/MachineLearning
datetime 2024-05-21
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url_encoded Z0FBQUFBQm5Lak9SeHlfYVYxcDV1aWNucW9IV1ljaWN3ZkZSYThTVnJZZ29tR1hhNHZReXlURjFxbmF0RHVJQVQwWGg2MDhJTmpWWmdSUXJpQnlqMUxjVngxUFE3RF9FNER0SmlRdWNqTkt5NFRnVUhIYTlmUFlHMVY4UV9oWFFTcWROZ3IxaG45d3hmSXlkS1Y2SmEtN3ZnQlJvcmZzRldleEVkYWJlWWxYeVZRcVd4bVZmZzFyRTlvT1Q2WHhGQUhsY0xYZkZUTG5ncjBDeXRfS0dhMHVUZ0czOWJmX0ctdz09

Raw Record

{
  "text": "I was reading through [https://arxiv.org/abs/1703.04730](https://arxiv.org/abs/1703.04730) and was looking into the derivation of equation (1) given in the Appendix A. I understand how we get equations (6)-(10), but the jump from equation (10) to (11) is confusing me.\n\nI also don't really get how you'd 2nd order Taylor expand the RHS of equation (10), as it's a vector-to-vector function. Do they mean 2nd order Taylor expanding the perturbed loss function R(theta) + epsilon L(theta)? If this is the case, shouldn't the hessian should be part of a quadratic form? In equation (11) they're only right multiplying by delta\\_epsilon (not left multiplying), so it's not in this form. ",
  "label": "r/machinelearning",
  "dataType": "post",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-21",
  "username_encoded": "Z0FBQUFBQm5Lak1DSWJPWmJidldZYjAwSzdqU0lYR2ZKcHdTYjlfZDZVR1ZicVh2QlEtRC1iN0RSbThwQk5BWUJIU0dPaDVuLXgxXzRKQ3BKSFlTdlBpcTdMemVmNlVfUHc9PQ==",
  "url_encoded": "Z0FBQUFBQm5Lak9SeHlfYVYxcDV1aWNucW9IV1ljaWN3ZkZSYThTVnJZZ29tR1hhNHZReXlURjFxbmF0RHVJQVQwWGg2MDhJTmpWWmdSUXJpQnlqMUxjVngxUFE3RF9FNER0SmlRdWNqTkt5NFRnVUhIYTlmUFlHMVY4UV9oWFFTcWROZ3IxaG45d3hmSXlkS1Y2SmEtN3ZnQlJvcmZzRldleEVkYWJlWWxYeVZRcVd4bVZmZzFyRTlvT1Q2WHhGQUhsY0xYZkZUTG5ncjBDeXRfS0dhMHVUZ0czOWJmX0ctdz09"
}
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