This dataverse is a collection of the College of Computing and Data Science’s research data.

Featured Dataverses

In order to use this feature you must have at least one published dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

3,771 to 3,780 of 5,121 Results
ternarize.h
May 10, 2022 - Replication Data for: TAB: Unified and Optimized Ternary, Binary and Mixed-Precision Neural Network Inference on the Edge
C++ Source - 16.6 KB - MD5: b52eb464ea52616dacfb1e0363e13855
ternarize.h
May 10, 2022 - Replication Data for: TAB: Unified and Optimized Ternary, Binary and Mixed-Precision Neural Network Inference on the Edge
C++ Source - 16.6 KB - MD5: b52eb464ea52616dacfb1e0363e13855
version.txt
May 10, 2022 - Replication Data for: TAB: Unified and Optimized Ternary, Binary and Mixed-Precision Neural Network Inference on the Edge
Plain Text - 934 B - MD5: deb561656a4c7359189b4a51b3d93dba
Related data for GLIMG: Global and local item graphs for top-N recommender systems
Apr 23, 2022 - Lin Zhuoyi
Lin, Zhuoyi, 2022, "Related data for GLIMG: Global and local item graphs for top-N recommender systems", https://doi.org/10.21979/N9/NRRVDW, DR-NTU (Data), V2
GLIMG: Global and local item graphs for top-N recommender systems
labelml1m.txt
Apr 23, 2022 - Related data for GLIMG: Global and local item graphs for top-N recommender systems
Plain Text - 11.8 KB - MD5: 07701e260ae2c69d9d3c9f226c35cabc
labelyelp.txt
Apr 23, 2022 - Related data for GLIMG: Global and local item graphs for top-N recommender systems
Plain Text - 11.1 KB - MD5: 2bd81066874f84dcf69bf7e646cfad46
main.py
Apr 23, 2022 - Related data for GLIMG: Global and local item graphs for top-N recommender systems
Python Source Code - 8.0 KB - MD5: fef17ebb815014628196c42300145816
Code
Related Data for COMET: Convolutional Dimension Interaction for Collaborative Filtering
Apr 23, 2022 - Lin Zhuoyi
Lin, Zhuoyi, 2022, "Related Data for COMET: Convolutional Dimension Interaction for Collaborative Filtering", https://doi.org/10.21979/N9/TO2HBX, DR-NTU (Data), V2
Latent factor models play a dominant role among recommendation techniques. However, most of the existing latent factor models assume both historical interactions and embedding dimensions are independent of each other, and thus regrettably ignore the high-order interaction informa...
comet.rar
Apr 23, 2022 - Related Data for COMET: Convolutional Dimension Interaction for Collaborative Filtering
RAR Archive - 17.1 KB - MD5: 0fb5991c8bc2b1c5bd3adf8a9a2d5dbc
Code
ml-1m.test.negative
Apr 18, 2022 - Related Data for COMET: Convolutional Dimension Interaction for Collaborative Filtering
Unknown - 2.7 MB - MD5: 4dd3924265e2d0e7b2e6734fd7bebc49
Data
Add Data

Log in to create a dataverse or add a dataset.

Log In
Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.