Custom combined hinge/kb-divergence loss function in siamese-net fails to generate meaningful speaker-embeddings: https://stackoverflow.com/questions/53581298/custom-combined-hinge-kb-divergence-loss-function-in-siamese-net-fails-to-genera
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Custom combined hinge/kb-divergence loss function in siamese-net fails to generate meaningful speaker-embeddings
I'm currently trying to implement a siamese-net in Keras where I have to implement the following loss function:
loss(p ∥ q) = Is · KL(p ∥ q) + Ids · HL(p ∥ q)
Where KL is the Kullback-Leibler
loss(p ∥ q) = Is · KL(p ∥ q) + Ids · HL(p ∥ q)
Where KL is the Kullback-Leibler
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r/Python - Considerations when creating Databases at the start of a project
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r/Python - Parsing XML out to CSV from SOAP Envelope, a problem with Latin/UTF-8 characters kills script.
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r/Python - PyCM 1.6 released : New machine learning library for confusion matrix statistical analysis
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r/Python - Learning Python API Development - Flask Application Structure
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r/Python - How to Install Jupyter Notebook on AWS EC2 Instance for Machine Learning and Python scripting
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r/Python - Introducing Visual GraphQL Editor - draw your graphql schema
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From the Python community on Reddit: 50 Free Machine Learning Datasets: Natural Language Processing
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Python defensive programming/design-by-contract package. Need...
For the last 1.5 months I've been working on a library for defensive programming/Design-by-Contract in Python, with no dependencies. It all...
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r/Python - At a complete loss of what is going on here...
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python least squares regression modification to objective function: https://stackoverflow.com/questions/45785426/python-least-squares-regression-modification-to-objective-function
Stack Overflow
python least squares regression modification to objective function
Least squares regression is defined as the minimization of the sum of squared residuals e.g.
Minimize(sum_squares(X * beta - y))
However, I'd like to propose a slight modification such that we are
Minimize(sum_squares(X * beta - y))
However, I'd like to propose a slight modification such that we are
Largest possible number of disjoint subsets in a set: https://stackoverflow.com/questions/53076097/largest-possible-number-of-disjoint-subsets-in-a-set
Stack Overflow
Largest possible number of disjoint subsets in a set
I'm given a set of lists, for instance:
[[0, 1, 3], [0, 2, 12], [6, 9, 10], [2, 4, 11], [2, 7, 13], [3, 5, 11], [3, 7, 10], [4, 10, 14], [5, 13, 14]]
I need to find the maximum number of disjoint
[[0, 1, 3], [0, 2, 12], [6, 9, 10], [2, 4, 11], [2, 7, 13], [3, 5, 11], [3, 7, 10], [4, 10, 14], [5, 13, 14]]
I need to find the maximum number of disjoint
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r/Python - Quart (Flask wrapper) is not separating different requests into different contexts
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