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**Describe the feature / issue**
Namespace `DissolveFit` will contain basic fitting operations for 1D data. This originally started as a motivation to include a go-to method for a general case of fit…
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This is a meta-issue to discuss and list the simulated and real data setups for the experiments. These just some ideas off the top of my head. Let's discuss it!
# Real Data
## Gaussian
- [ ] …
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Sparse Laplacian Shrinkage combines a L1 based penalty and a quadratic informative penalty, similar to glm-net but with structured L2 penalization matrix
Sparse Laplacian Shrinkage is the first stran…
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In some cases, when there are categorical predictors, imputation fails. I give here a an example, with the stochastic imputer but my guess is that is comes from an improper encoding of categorical var…
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Suggested list of courses would be:
- An introduction to deep learning **
- How to train a neural network
- Regularisation in neural networks
- Deep Bayesian neural networks
- Conv…
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`safe_sparse_dot` has an option `dense_output` which allows to specify that the dot product between two sparse matrices or between a sparse matrix and a numpy array should be output to a numpy array. …
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When I run the following code:
```
#include "taco.h"
using namespace taco;
int main(int argc, char* argv[]){
Format s1{{taco::Sparse, }};
Format s2{{taco::Sparse, taco::Sparse}};
…
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Should a dedicated API/column metadata to efficiently support sparse columns be part of the spec?
## Context
It can be the case than a given column has more more than 99% of its values that are …
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Hi TFLearn Team,
I am new to tensorflow and tflearn and implementing a classifier using LSTM.
In the meanwhileI, encountered the following warning:
/usr/local/lib/python2.7/dist-packages/tenso…
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# GP
- [GP for big data: Hensmen (2013)][2]
- [Stochastic Variational Inference for Fully Bayesian Sparse Gaussian Process Regression Models: Yu (2017)][3]
# SVI
- [Variational Auto-encoder][4]…