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A framework for predicting, interpreting, and improving Learning Outcomes
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A framework for predicting, interpreting, and improving Learning Outcomes

Chintan Donda
Sayantani Dasgupta
S. Dhavala
Keyur Faldu
Aditi Avasthi
ArXiv (abs)PDFHTML

Papers citing "A framework for predicting, interpreting, and improving Learning Outcomes"

3 / 3 papers shown
Title
Beyond expectation: Deep joint mean and quantile regression for spatio-temporal problems
Beyond expectation: Deep joint mean and quantile regression for spatio-temporal problems
Filipe Rodrigues
Francisco Câmara Pereira
AI4TS
126
96
0
27 Aug 2018
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
Huifeng Guo
Ruiming Tang
Yunming Ye
Zhenguo Li
Xiuqiang He
124
2,659
0
13 Mar 2017
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Anh Totti Nguyen
J. Yosinski
Jeff Clune
AAML
174
3,275
0
05 Dec 2014

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