Topic: joint-learning Goto Github
Some thing interesting about joint-learning
Some thing interesting about joint-learning
joint-learning,Implementation of PAKDD'20 paper: "Jointly Modelling Attribute Interactions and Relationships for Cross-lingual Knowledge Alignment".
User: allanchen95
joint-learning,Python project planing organizer for python formation Adep Roubaix
User: brunoharlein
joint-learning,A part-of-speech/morphological tagger and a dependency parser that can be trained separately or jointly, with special methods for Ancient Greek.
User: clemeth
joint-learning,This repository provides an insight into ventures of framing an intelligent Command line interface (CLI) for UNIX Based Systems.
User: divyansha1115
joint-learning,This project allows users to add, delete and views information of all their employees.
User: ductran963
joint-learning,Code-Switching Language Modeling using Syntax-Aware Multi-Task Learning (CALCS 2018, ACL)
User: gentaiscool
Home Page: https://www.aclweb.org/anthology/W18-3207
joint-learning,Opinion recommendation is a task, recently introduced, for consistently generating a text review and a rating score that a certain user would give to a certain product, which has never seen before. Input information driving recommendation is text reviews and ratings for this product contributed by other users and text reviews submitted by the user under consideration for other products. The aforementioned task faces the same problems emerging in text generation using neural networks, namely repetition and specificity. In this paper, it is experi- mentally demonstrated that by employing coverage loss during training, repetition is reduced without adding extra parameters. Furthermore, the amount of repetition in the generated text review is defined as a measure of the captured information. Such measure is used to improve rating score prediction significantly during testing.
User: gionanide
joint-learning,Implementation of joint construction of Mask/BBox heads in QDTrack-mots for joint training research
User: jkd2021
joint-learning,PyTorch code for JEREX: Joint Entity-Level Relation Extractor
Organization: lavis-nlp
joint-learning,PyTorch code for SpERT: Span-based Entity and Relation Transformer
Organization: lavis-nlp
joint-learning,Joint text classification on multiple levels with multiple labels, using a multi-head attention mechanism to wire two prediction tasks together.
User: mirunapislar
joint-learning,COVID-19 forecasting model for East Java cities using Joint Learning. My undergrad thesis.
User: r-n
joint-learning,Streamlit web app of covid-forecasting-joint-learning
User: r-n
joint-learning,2021 CCF BDCI 全国信息检索挑战杯(CCIR-Cup)智能人机交互自然语言理解赛道第二名参赛解决方案
User: scu-jjkinging
joint-learning,Source code and datasets for EMNLP 2019 paper: Jointly Learning Entity and Relation Representations for Entity Alignment.
User: stephaniewyt
joint-learning,Our source code for the paper "Transformer-based Joint Learning Approach for Text Normalization in Vietnamese ASR"
User: vietbtx
joint-learning,BERT-based joint intent detection and slot filling with intent-slot attention mechanism (INTERSPEECH 2021)
Organization: vinairesearch
joint-learning,Crack Segmentation for Low-Resolution Images using Joint Learning with Super-Resolution (CSSR) was accepted to international conference on MVA2021 (oral), and selected for the Best Practical Paper Award.
User: yuki-11
A declarative, efficient, and flexible JavaScript library for building user interfaces.
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TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
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JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
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A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
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We are working to build community through open source technology. NB: members must have two-factor auth.
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Data-Driven Documents codes.
China tencent open source team.