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Leveraging Crowdsourcing Data For Deep Active Learning - An Application:
  Learning Intents in Alexa

Leveraging Crowdsourcing Data For Deep Active Learning - An Application: Learning Intents in Alexa

12 March 2018
Jie Yang
Thomas Drake
Andreas C. Damianou
Y. Maarek
    FedML
ArXiv (abs)PDFHTML

Papers citing "Leveraging Crowdsourcing Data For Deep Active Learning - An Application: Learning Intents in Alexa"

11 / 11 papers shown
Title
Multi-annotator Deep Learning: A Probabilistic Framework for
  Classification
Multi-annotator Deep Learning: A Probabilistic Framework for Classification
M. Herde
Denis Huseljic
Bernhard Sick
80
9
0
05 Apr 2023
Towards AI-Empowered Crowdsourcing
Towards AI-Empowered Crowdsourcing
Shipeng Wang
Qingzhong Li
Li-zhen Cui
Zhongmin Yan
Yonghui Xu
Zhuan Shi
Xinping Min
Zhiqi Shen
Han Yu
HAI
34
0
0
28 Dec 2022
Design and Evaluation of Crowd-sourcing Platforms Based on Users
  Confidence Judgments
Design and Evaluation of Crowd-sourcing Platforms Based on Users Confidence Judgments
Samin Nili-Ahmadabadi
Maryam Haghifam
V. Shah-Mansouri
S. Ershadmanesh
13
1
0
12 Dec 2022
FUN-SIS: a Fully UNsupervised approach for Surgical Instrument
  Segmentation
FUN-SIS: a Fully UNsupervised approach for Surgical Instrument Segmentation
Luca Sestini
Benoit Rosa
Elena De Momi
G. Ferrigno
N. Padoy
62
35
0
16 Feb 2022
A Survey on Cost Types, Interaction Schemes, and Annotator Performance
  Models in Selection Algorithms for Active Learning in Classification
A Survey on Cost Types, Interaction Schemes, and Annotator Performance Models in Selection Algorithms for Active Learning in Classification
M. Herde
Denis Huseljic
Bernhard Sick
A. Calma
80
25
0
23 Sep 2021
On Statistical Bias In Active Learning: How and When To Fix It
On Statistical Bias In Active Learning: How and When To Fix It
Sebastian Farquhar
Y. Gal
Tom Rainforth
TDIHAI
60
85
0
27 Jan 2021
Cisco at AAAI-CAD21 shared task: Predicting Emphasis in Presentation
  Slides using Contextualized Embeddings
Cisco at AAAI-CAD21 shared task: Predicting Emphasis in Presentation Slides using Contextualized Embeddings
Sreyan Ghosh
Sonal Kumar
H. Jalan
Hemant Yadav
R. Shah
82
2
0
10 Jan 2021
End-to-End Learning from Noisy Crowd to Supervised Machine Learning
  Models
End-to-End Learning from Noisy Crowd to Supervised Machine Learning Models
Taraneh Younesian
Chi Hong
Amirmasoud Ghiassi
Robert Birke
L. Chen
NoLaFedML
59
3
0
13 Nov 2020
A Survey of Deep Active Learning
A Survey of Deep Active Learning
Pengzhen Ren
Yun Xiao
Xiaojun Chang
Po-Yao (Bernie) Huang
Zhihui Li
Brij B. Gupta
Xiaojiang Chen
Xin Wang
123
1,157
0
30 Aug 2020
A Human-AI Loop Approach for Joint Keyword Discovery and Expectation
  Estimation in Micropost Event Detection
A Human-AI Loop Approach for Joint Keyword Discovery and Expectation Estimation in Micropost Event Detection
Akansha Bhardwaj
Jie Yang
Philippe Cudré-Mauroux
8
9
0
02 Dec 2019
A Technical Survey on Statistical Modelling and Design Methods for
  Crowdsourcing Quality Control
A Technical Survey on Statistical Modelling and Design Methods for Crowdsourcing Quality Control
Yuan Jin
Mark J. Carman
Ye Zhu
Yong Xiang
49
36
0
05 Dec 2018
1