Newest 'transfer-learning' Questions

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What is the difference between transfer learning and reinforcement learning?

...Seems so similar to me... I am new in advanced ML techniques, please give me some example.

reinforcement-learning transfer-learning

asked Nov 27 at 16:01

pikachu

896 bronze badges

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7 views

How to apply transfer learning using a survival model?

I have a parametric survival model assuming a certain distribution pattern for dataset A. I now wish to use the same model for dataset B. What criteria is needed to ensure that the model built on ...

asked Nov 17 at 14:48

Py_Mel

354 bronze badges

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votes

2answers

55 views

Directly using Inaccurate Labels vs. Transfer Learning

I have a two ML models model_a and model_b that optimize on an event, label_a. I have a small volume of labels for model_a and a large volume of labels for model_b. The features used in these models ...

machine-learning transfer-learning labeling

asked Nov 3 at 17:10

Ethereal

513 bronze badges

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0answers

20 views

Transfer Learning for non-NN models

I have built an non-NN Ensemble Classifier for labeling the content of scanned invoices, for which I used a training set of template invoices. I would like to use that model to predict labels of ...

supervised-learning transfer-learning

asked Oct 31 at 12:19

Oxymoron

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Testing machine learning models using a different set of labels

I have a dataset with 119 features and 228 samples. I have trained my classifier using a particular set of labels (0 and 1). Now I want to test how the model is performing to external data. There is ...

classification feature-selection transfer-learning

asked Oct 30 at 13:18

bandit_king28

777 bronze badges

1

vote

1answer

29 views

Object detection with just one image? [duplicate]

Deep neural networks require lots of examples to learn tasks like image classification, and object recognition. On the other hand, we humans can learn and identify object just by looking at it once. ...

neural-networks conv-neural-network computer-vision object-detection transfer-learning

asked Oct 30 at 1:35

tired and bored dev

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19 views

MSE loss going Infinite [duplicate]

I am using DeepLabv3+ model to perform regression and predict the value of one of the channels. Details of the model used OS = 8, Backbone = None, loss='mean_squared_error', optimizer = adam(0.001, ...

regression neural-networks transfer-learning image-segmentation

asked Oct 28 at 9:48

akzhere

11 bronze badge

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0answers

6 views

how to choose a transfer learning approach for regression model

I am new to the concept of transfer learning and from what I have seen so far, there are many ways in which transfer learning can be applied. I have two datasets where the distribution of failures ...

regression machine-learning mathematical-statistics transfer-learning

asked Oct 23 at 17:54

Py_Mel

354 bronze badges

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0answers

34 views

Why we need the Gram matrix in style transfer learning?

I read this paper by Gatys and cannot comprehend why the Gram matrix for the style feature maps is necessary? In the paper it reads that: On top of the CNN responses in each layer of the network ...

neural-networks transfer-learning

asked Oct 3 at 1:53

Lerner Zhang

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2

votes

1answer

37 views

Combining data with differing dependent variables

Suppose we have two feature matrices, $X_1$ and $X_2$, with response variables $Y_1$ and $Y_2.$ Where $X_1$ and $X_2$ have the same feature columns, but distinct observations. Furthermore, $Y_1$ and $...

regression machine-learning data-transformation transfer-learning

asked Aug 28 at 3:05

Peter DeWeirdt

212 bronze badges

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votes

1answer

36 views

Understanding the process of transfer learning for NLP

Full Disclosure: I am a machine learning newbie. I have been learning about natural language processing for the past few weeks. To my understanding, the process of creating a supervised text model ...

machine-learning natural-language transfer-learning

asked Aug 20 at 20:45

thedeg123

11 bronze badge

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22 views

What type of Normalisation technique is best for image data before applying any CNN deep learning model on type of it? [duplicate]

How to decide upon the normalisation that need to be used for image classification or cv problems , Is there any standard on what to choose when in particularly with Image data ?

neural-networks conv-neural-network normalization standardization transfer-learning

asked Aug 15 at 13:52

ylnhari

16 bronze badges

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vote

0answers

7 views

Needing 4th dimension for shape [closed]

I was working on a transfer learning solution to categorize between diseases in the eye. I was using the Xception model built into Keras and it uses a data set that I was able to accumulate. However ...

tensorflow keras transfer-learning data-augmentation

asked Aug 15 at 8:13

Aditya Mangalampalli

111 bronze badge

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vote

0answers

15 views

Supervised learning in non-stationary environments?

For real applications, concept drifts often exist, i.e., the relationship between the input and output changes overtime. I'm wondering what are the most common methods to enable neural networks to ...

machine-learning neural-networks stationarity transfer-learning

asked Aug 5 at 14:57

Hammer. Wang

735 bronze badges

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0answers

38 views

How to do transfer learning with limited data

This is my first question here, please be gentle with me. I'm working on point cloud classification problem. I'm building a NN to classify point cloud. I found a really nice architecture that I want ...

classification transfer-learning

asked Aug 5 at 5:44

TripleS

1011 bronze badge

2

votes

1answer

28 views

Using a separate but related dataset for feature extraction (transfer learning)

I have two datasets of MRI images: a larger one of Altzheimer's paitents (AD), which is about 3 times the size of a smaller dataset of brain tumor paitents (BT). My aim is to make use of the AD data ...

feature-selection conv-neural-network autoencoders transfer-learning

asked Jul 16 at 15:09

thegrasshopperliesheavy

233 bronze badges

2

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0answers

23 views

Transfer Learning in domains other than Image processing and NLP

Can Transfer Learning be applied in domains other than Image processing or NLP? I am trying to apply it on clickstream data (for propensity modeling). Any reference would be greatly appreciated.

machine-learning propensity-scores artificial-intelligence transfer-learning

asked Jun 16 at 6:17

avinax

233 bronze badges

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vote

1answer

14 views

Same input size for Source and Target Model?

For the transfer learning do we need to have same input image size of target model as source model? for example my source model is trained on 100x100 input images and target model is low resolution ...

machine-learning neural-networks conv-neural-network computer-vision transfer-learning

asked Jun 15 at 4:39

Addee

1514 bronze badges

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1answer

136 views

Transfer learning for regression problems?

How does transfer learning work for regression tasks? Can someone point to an application where transfer learning has been successfully applied for regression tasks.

regression transfer-learning

asked Jun 10 at 23:35

GSH

735 bronze badges

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18 views

What do I call the model that I have “transferred” from in transfer learning?

I am trying to document some machine learning artefacts, we have two models a and b. a and b are trained using the same data, they are trained with the same embedding and with the same algorithm and ...

neural-networks terminology transfer-learning

asked Jun 3 at 15:14

Simon Thompson

112 bronze badges

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0answers

32 views

How to add new features to already trained model without training again on whole dataset?

Suppose, we have following features on which a classification model (Neural Network) is trained to predict whether a customer will buy Milk or not (0 :Will not buy, 1:Will buy) each week(n): ...

machine-learning neural-networks feature-selection transfer-learning

asked May 15 at 9:38

CYAN CEVI

1213 bronze badges

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0answers

11 views

Bias and variance decomposition to estimate prediction

There are various ways that statisticians have come up for bias vs. variance decomposition in terms of prediction estimation. My question is this, how can one leverage or create a loss function based ...

classification variance bias hyperparameter transfer-learning

asked May 2 at 23:38

MichaelMMeskhi

7510 bronze badges

5

votes

3answers

147 views

Extending a neural network to classify new objects

Suppose a model M classifies apples and oranges. Can M be extended to classify a third class of objects, e.g., pears, such that ...

neural-networks deep-learning conv-neural-network transfer-learning

asked Apr 4 at 16:24

John M.

1511 bronze badge

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1answer

949 views

How to Fine Tune a pre-trained network

I'm looking into using Transfer Learning to take the ResNet50 model trained on ImageNet and fine tune it to my own dataset using Keras. However, I feel I have some misconception about what exactly ...

machine-learning deep-learning transfer-learning

asked Feb 7 at 12:37

TwoRice

553 bronze badges

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293 views

compute the KL divergence between two datasets

I have two datasets $D1$ and $D2$ in two different feature spaces $\mathcal{X}_{1} \in \Re^{m}$ and $\mathcal{X}_{2} \in \Re^{n}$. Further assume that the datasets have different number of data points....

machine-learning deep-learning multivariate-analysis kullback-leibler transfer-learning

asked Feb 7 at 10:50

Upendra Pratap Singh

1,14610 silver badges20 bronze badges

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9 views

Will merging class labels in pre-trained model hurt transfer learning?

I'm using a large image dataset labeled with 15 classes to train a ConvNet model. The resulting model will then be used to enable transfer learning in a tiny dataset labeled with only 3 classes. The 3 ...

machine-learning neural-networks deep-learning conv-neural-network transfer-learning

asked Feb 6 at 1:57

Edna

11 bronze badge

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51 views

Would training 1024x1024 images with pretrained resnet (224x224) be appropriate?

I want to use Resnet50 (or 101, or 152..) backbone for a segmentation task. My problem requires a lot of context, hence tiling the large image into 224x224 defeats the purpose. I was wondering if I ...

transfer-learning pre-training

asked Jan 31 at 10:46

user1696420

12 bronze badges

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vote

0answers

81 views

Using PCA in domain adaptation

In literature, I see people using (Kernelized) Principle Component Analysis, not for feature extraction, but for domain adaptation. In other words, I have data from a source domain and I would like to ...

machine-learning pca transfer-learning domain-adaptation

asked Jan 17 at 19:14

Armannas

113 bronze badges

0

votes

1answer

63 views

What does a “similar” dataset mean in the context of fine tuning a CNN?

In https://arxiv.org/pdf/1809.09529.pdf it is said If the new dataset is similar to original dataset, we expect higher-level features in the CNN to be relevant to this dataset. Thus, it is ...

neural-networks conv-neural-network transfer-learning

asked Jan 15 at 2:50

fabiomaia

3291 silver badge10 bronze badges

6

votes

1answer

1k views

How should I standardize input when fine-tuning a CNN?

I am working on a model for binary classification of skin samples from https://www.isic-archive.com as either benign or malignant. I want to use the VGG16 model pre-trained on ImageNet and fine-tune ...

neural-networks conv-neural-network transfer-learning

asked Dec 26 '18 at 3:22

fabiomaia

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1answer

17 views

Should I be stepping down high a dimensional embedding when predicting low dimensional output

I'm using a ResNet-50 pretrained on ImageNet as a starting point for various image classifiers. Because the pretrained model has 1001 outputs, I have added a single dense layer with output size 500 ...

deep-learning transfer-learning

asked Dec 18 '18 at 18:09

Joey Carson

1035 bronze badges

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votes

1answer

119 views

using (deep) neural networks for a severely imbalanced image dataset when some classes have <10 images

Taking a long shot here. So I have a a small dataset of ~500 images with discrete labels from 1 to 9. My task is to detect the per-class and overall accuracy of this classification method using a (...

machine-learning neural-networks deep-learning unbalanced-classes transfer-learning

asked Nov 11 '18 at 19:26

Mona Jalal

3844 silver badges16 bronze badges

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1answer

278 views

Is Gradient Boosting Regression Tree able to learn linear models

Assume $Y$ is a linear function of a vector of variables $X$ (plus a noise term). The train data consists of ($X,Y$) such that $X \in ［0,1］$. Assume one use gbdt to learn this linear model. And if ...

linear-model boosting xgboost transfer-learning

asked Aug 26 '18 at 4:28

Hao Yu

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0answers

26 views

FineTuned VGG16 achieving great results on epoch 1, is this normal?

I'm training a model to classify whether a person is smiling (showing teeth) or not. I'm using Keras and I trained a VGG16 model loaded with the ImageNet weights, froze the first 4 layers and added a ...

classification deep-learning overfitting transfer-learning

asked Aug 24 '18 at 22:03

JDev

112 bronze badges

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votes

1answer

21 views

How do we call when one model is trained by another?

Suppose I have one model (say, for image classification) as black box. I don't posess it and don't know it's parameters. Suppose it is web API. Then I take bunch of images, classify them by this ...

terminology transfer-learning

asked Jul 18 '18 at 20:57

Dims

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-1

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2answers

45 views

Transfer learning scenario [closed]

I have an interesting question and I need some help. Consider the following problem. Let's suppose that I am doing regression with neural networks. As input I have a set of measurements, arrays of $N$ ...

machine-learning neural-networks transfer-learning

asked Jun 7 '18 at 6:10

Umberto

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vote

0answers

121 views

Transfer Learning for Multivariate Regression

As I understand it, transfer learning is termed as using the parameters of a pre-trained model, which was initially trained on a particular 'source' task, and have it train on another related 'target' ...

machine-learning neural-networks transfer-learning

asked Jun 5 '18 at 12:39

Ashwin Nair

114 bronze badges

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1answer

345 views

Transfer learning for audio

I know that when working with images, what people normally do is download a big model trained with huge data and freeze most of the layers except the lasts ones to train them with their own data. I'm ...

lstm transfer-learning speech-recognition gru

asked Jun 1 '18 at 12:04

Isaac

1032 bronze badges

5

votes

1answer

1k views

Transfer learning: How and why retrain only final layers of a network?

In this video, Prof. Andrew Ng says regarding transfer learning: Depending on how much data you have, you might just retrain the new layers of the network, or maybe you could retrain even more ...

machine-learning neural-networks backpropagation transfer-learning

asked May 31 '18 at 8:26

Tom Hale

1,1812 gold badges8 silver badges23 bronze badges

2

votes

1answer

4k views

Fine Tuning vs. Transferlearning vs. Learning from scratch

In my master thesis, I am researching on transfer learning on a specific use Case, a traffic sign detector implemented as a Single Shot Detector with a VGG16 base network for classification. The ...

deep-learning computer-vision object-detection transfer-learning

asked May 1 '18 at 9:12

Jürgen Zornig

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1

vote

0answers

32 views

Transfer learning for image classification

When working with transfer learning for image classification, I would like to freeze only a part of the convolutional base of a pretrained model while adding a classifier (some shallow network) on top ...

deep-learning computer-vision transfer-learning

asked Apr 14 '18 at 12:55

chsafouane

571 silver badge5 bronze badges

0

votes

1answer

87 views

Adapt speech recognition for Shakespeare english

We need to be able to search the works of Shakespeare by voice. The way I see it, the goal is if I quote into the microphone: "Yet but three come one more. Two of both kinds make up four. Ere ...

transfer-learning speech-recognition machine-translation

asked Mar 27 '18 at 18:20

AwokeKnowing

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6

votes

0answers

3k views

Transfer Learning on generative adversarial networks (GANs)

Is it possible to apply transfer learning to GANs and if so, what are some examples of someone having tried this?

gan transfer-learning

asked Mar 26 '18 at 5:14

Alberto Miller

611 silver badge4 bronze badges

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0answers

2k views

How to Train LSTM across Multiple Time Series datasets

I believe there are generalizable mapping rules that can be extracted from multiple time series data-sets I have. Each data-set represents a specific company, and while I am able to train on each ...

time-series neural-networks lstm transfer-learning

asked Feb 20 '18 at 22:21

David Yang

1715 bronze badges

1

vote

1answer

302 views

Comparing distribution of training and test dataset

When we fit a model to a training dataset, our basic assumption is that the test dataset will also come from the same (or similar) distribution. How to check if the distribution of the training and ...

distributions t-test analysis transfer-learning two-sample

asked Feb 8 '18 at 21:15

The Wanderer

4652 silver badges14 bronze badges

9

votes

2answers

4k views

Where to find pre-trained models for transfer learning [closed]

I am new to the machine learning field, but I wanted to try and implement a simple classification algorithm with Keras. Unfortunately, I have a very small set of data, so I thought to try to apply ...

machine-learning classification neural-networks transfer-learning

asked Feb 6 '18 at 7:33

Eggman

931 silver badge7 bronze badges

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1answer

145 views

Can object detection be done by passing parts of images to an image classification network? [closed]

I am using a pre-trained image classification network. How is the object detection performace by passing the parts of the image individually to detect various objects. is there any other way to ...

conv-neural-network computer-vision object-detection transfer-learning

asked Feb 5 '18 at 7:25

userlatebloomer

698 bronze badges

27

votes

6answers

9k views

Why study convex optimization for theoretical machine learning?

I am working on theoretical machine learning — on transfer learning, to be specific — for my Ph.D. Out of curiosity, why should I take a course on convex optimization? What take-aways from convex ...

machine-learning optimization convex transfer-learning

asked Jan 25 '18 at 8:23

Upendra Pratap Singh

1,14610 silver badges20 bronze badges

4

votes

1answer

886 views

how is covariate shift associated with domain adaptation?

This question is in context to transfer learning. During my presentation on transfer learning, I was asked the difference between covariate shift and domain adaptation. All I know is that covariate ...

machine-learning transfer-learning

asked Jan 18 '18 at 13:49

Upendra Pratap Singh

1,14610 silver badges20 bronze badges

0

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0answers

485 views

Keyword Spotting: How to train a model with general speech corpus?

I am trying to find a correct way to train a DNN based keyword spotting (Deep KWS) with general speech corpus (VS data) described in this paper (Chen, Guoguo, Carolina Parada, and Georg Heigold. "...

machine-learning neural-networks transfer-learning speech-recognition

asked Jan 15 '18 at 3:05

Lion Lai

1154 bronze badges

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