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Transfer Learning

393 papers with code · Methodology

Transfer learning is a methodology where weights from a model trained on one task are taken and either used (a) to construct a fixed feature extractor, (b) as weight initialization and/or fine-tuning.

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Latest papers with code

Hyperspectral Classification Based on 3D Asymmetric Inception Network with Data Fusion Transfer Learning

11 Feb 2020UniLauX/AINet

Hyperspectral image(HSI) classification has been improved with convolutional neural network(CNN) in very recent years.

TRANSFER LEARNING

0
11 Feb 2020

MS-Net: Multi-Site Network for Improving Prostate Segmentation with Heterogeneous MRI Data

9 Feb 2020liuquande/MS-Net

However, the prostate MRIs from different sites present heterogeneity due to the differences in scanners and imaging protocols, raising challenges for effective ways of aggregating multi-site data for network training.

TRANSFER LEARNING

5
09 Feb 2020

Understanding the Automated Parameter Optimization on Transfer Learning for CPDP: An Empirical Study

8 Feb 2020COLA-Laboratory/icse2020

Given a tight computational budget, it is more cost-effective to focus on optimizing the parameter configuration of transfer learning algorithms (3) The research on CPDP is far from mature where it is "not difficult" to find a better alternative by making a combination of existing transfer learning and classification techniques.

TRANSFER LEARNING

1
08 Feb 2020

Data Mining in Clinical Trial Text: Transformers for Classification and Question Answering Tasks

30 Jan 2020L-ENA/HealthINF2020

This paper contributes to solving problems related to ambiguity in PICO sentence prediction tasks, as well as highlighting how annotations for training named entity recognition systems are used to train a high-performing, but nevertheless flexible architecture for question answering in systematic review automation.

ENTITY EXTRACTION NAMED ENTITY RECOGNITION QUESTION ANSWERING READING COMPREHENSION TRANSFER LEARNING WORD EMBEDDINGS

1
30 Jan 2020

ABSent: Cross-Lingual Sentence Representation Mapping with Bidirectional GANs

29 Jan 2020zuohuif/ABSent

A number of cross-lingual transfer learning approaches based on neural networks have been proposed for the case when large amounts of parallel text are at our disposal.

CROSS-LINGUAL TRANSFER SENTENCE EMBEDDING TRANSFER LEARNING

5
29 Jan 2020

ManyModalQA: Modality Disambiguation and QA over Diverse Inputs

22 Jan 2020hannandarryl/ManyModalQA

To demonstrate this ambiguity, we construct a modality selector (or disambiguator) network, and this model gets substantially lower accuracy on our challenge set, compared to existing datasets, indicating that our questions are more ambiguous.

QUESTION ANSWERING TRANSFER LEARNING

4
22 Jan 2020

A Common Semantic Space for Monolingual and Cross-Lingual Meta-Embeddings

17 Jan 2020ikergarcia1996/MVM-Embeddings

This paper presents a new technique for creating monolingual and cross-lingual meta-embeddings.

CROSS-LINGUAL TRANSFER SEMANTIC TEXTUAL SIMILARITY TRANSFER LEARNING WORD EMBEDDINGS

1
17 Jan 2020

Schema2QA: Answering Complex Queries on the Structured Web with a Neural Model

16 Jan 2020stanford-oval/genienlp

With transfer learning, we show that a new domain can achieve a 59% accuracy without manual effort.

TRANSFER LEARNING

1
16 Jan 2020

Lipschitz Lifelong Reinforcement Learning

15 Jan 2020SuReLI/llrl

We consider the problem of knowledge transfer when an agent is facing a series of Reinforcement Learning (RL) tasks.

TRANSFER LEARNING

1
15 Jan 2020