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### Find missing object(s) in image with a priori knowledge about the missing object(s) (w.r.t base image)

Problem Statement: I am working on developing a method, or borrow/modify/combine existing ones, where given an golden image (reference or base with all expected objects to be present), it is able to ...
• 4,108
2k views

### Why is my Keras model not learning image segmentation?

Edit: as is turns out, not even the model's initial creator could successfully fine-tune it. This is most likely a problem of implementation, or possibly related to the non-intuitive way in which the ...
• 199
2k views

### AdaBoost implementation and tuning for high dimensional feature space in R

I am trying to implement the AdaBoost.M1 algorithm (trees as base-learners) to a data set with a large feature space (~ 20.000 features) and ~ 100 samples in R. ...
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115 views

### Training value neural network AlphaGo style

I have been trying to replicate the results obtained by AlphaGo following their supervise learning protocol. The papers specify that they use a network that has two heads: a value head that predicts ...
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198 views

### How to predict advantage value in deep reinforcement learning

I'm currently working on a collection of reinforcement algorithms: https://github.com/lhk/rl_gym For deep q-learning, you need to calculate the q-values that should be predicted by your network. There ...
• 181
2k views

### Python : Feature Matching + Homography to find Multiple Objects

I'm trying to use OpenCV via Python to find multiple objects in a train image and match it with the key points detected from a query image. For my case, I'm trying to detect the tennis courts in the ...
• 81
9k views

### How is WordPiece tokenization helpful to effectively deal with rare words problem in NLP?

I have seen that NLP models such as BERT utilize WordPiece for tokenization. In WordPiece, we split the tokens like playing to play and ##ing. It is mentioned that it covers a wider spectrum of Out-Of-...
• 696
3k views

### Tensorflow v1 Dataset API AttributeError with ndim

I'd like to make pipeline for optimizing Gpu and Cpu. Dataset It's about 10000 datapoint and 4 description variables for the regression problem. ...
1k views

### Multivariate, multistep forecasting with LSTM

I want to use an RNN with LSTM to forecast multiple steps into the future, based on multiple inputs. I have some ideas for different ways to approach this, but I'm afraid I'm missing the "right way" ...
• 171
2k views

### Fine tuning accuracy lower than Raw Transfer Learning Accuracy

I've used transfer learning on Inception V3 with ImageNet weights on Keras with Tensorflow backend on python 2.7 to create an image classifier. I first extracted and saved the bottleneck features from ...
• 71
897 views

### ALS in Spark: what loss function is it minimizing?

I’ve playing with the MovieLens ratings dataset under Spark’s ALS and a manual implementation of ALS and comparing results with the same hyperparameters. I’d like to know this exactly in order to make ...
507 views

### differences between LSQR and FTRL when working with very sparse data

I have a 2M instances dataset with millions of very very sparse dummy variables created using the hashing trick = ...
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124 views

### Unable to transform (greatly performing) Autoencoder into Variational Autoencoder

Following the procedure described in this SO question, I am trying to transform my (greatly performing) convolutional Autoencoder into a Variational version of the same Autoencoder. As explained in ...
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### Is it Scientifically Rigorous to create a multimodal ML Model with data from multiple sources

I'm attempting to create a multimodal machine learning model for disease diagnosis. However, I'm having quite a bit of difficulty finding public data sets with all the data I need. For example, I need ...
18 views

### Homework/class help: Backward propagation of max pooling if each element in an array determines more than one value?

(This isn't actually my homework, and in fact wasn't addressed in my homework, but I was confused about this because my homework hadn't addressed this) For example if I have an array: And I do max ...
180 views

### ResNet50 + Transformer

In many papers people extract features from image using ResNet and than pass them through transformer. I want to implement the same. I want to get features and than classify them using transformer. ...
152 views

### Why margin loss is used in Capsule Network instead of Cross Entropy loss?

I'm reading the Capsule Network paper proposed by Hinton. I'm not sure why the margin loss is used instead of the cross entropy loss. Any intuitive explaination for this?
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107 views

### Non-greedy decision tree / random forest implementation(s) in Python

The standard random forest is trained using a greedy approach for computational feasibility. However, there are a number of alternative methods such as "lookahead" or using bilevel ...
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730 views

### Forecast Model to Estimate Customer Service Call Volume and Appropriate Staff

I am working on a project to predict the proper staffing needed for a customer service team using historical data. I am new to machine learning, and I am not sure if my approach to this problem is the ...
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26 views

### What are descriptors

I am very new to data science, and r programming specifically. Could some explain what a descriptor in data science is? In particular, what are the differences between a 2d and 3d descriptor? Thank ...
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