Jinjiarui/HEROES Jinjiarui/HEROES

  • Stars
    star
    3
  • Rank 3,963,521 (Top 79 %)
  • Language
    Python
  • License
    Apache License 2.0
  • Created almost 4 years ago
  • Updated over 1 year ago
Twitter logo Share LinkedIn logo Share Facebook logo Share
Jinjiarui/HEROES
github

Jinjiarui

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

Code for CIKM'22 "Multi-Scale User Behavior Network for Entire Space Multi-Task Learning"

More Repositories

1

GraphHINGE

Code for KDD'20 "An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph"
Python
70
star
2

rl4rs-papers

A collection of research and survey papers of reforcement learning (RL) based recommender system techniques.
68
star
3

CoRide

Code for CIKM'19 "CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platforms"
Python
64
star
4

STARec

Code for WWW'22 "Learn over Past, Evolve for Future: Search-based Time-aware Recommendation with Sequential Behavior Data"
Python
60
star
5

DRSR

Code for SIGIR'20 β€œA Deep Recurrent Survival Model for Unbiased Ranking”
Python
51
star
6

TWINS

Code for WWW'22 "Who to Watch Next: Two-side Interactive Networks for Live Broadcast Recommendation"
Python
41
star
7

hrl-papers

A collection of research and survey papers of hierarchical reinforcement learning (HRL).
34
star
8

GraphANGEL

Code for ICLR'22 "Inductive Relation Prediction Using Analogy Subgraph Embeddings"
Python
28
star
9

AsAp

A Toolkit for Mining Data in a Structural Fashion
Python
15
star
10

ex2rs-papers

A collection of research and survey papers of explaination techniques and their applications.
5
star
11

LabelTrick

Code for ICLR'22 "Why Propagate Alone? Parallel Use of Labels and Features on Graphs"
Python
3
star
12

STARank

Code for CIKM'23 "Replace Scoring with Arrangment: A Contextual Set-to-Arrangement Framework for Learning-to-Rank"
Python
3
star
13

SGORLON

Code for "Goal-oriented Reinforcement Learning for Navigation in Safety-Critical Environments"
Python
1
star