3 citations · 4 across the 4 of their papers we have counts for
4 papers
Cross Domain LifeLong Sequential Modeling for Online Click-Through Rate Prediction
Ruijie Hou, Zhaoyang Yang, Yu Ming +5
Deep neural networks (DNNs) that incorporated lifelong sequential modeling (LSM) have brought great success to recommendation systems in various social media platforms. While conti…
Temporal Calibrated Regularization for Robust Noisy Label Learning
Dongxian Wu, Yisen Wang, Zhuobin Zheng +1
Deep neural networks (DNNs) exhibit great success on many tasks with the help of large-scale well annotated datasets. However, labeling large-scale data can be very costly and erro…
Arena: a toolkit for Multi-Agent Reinforcement Learning
Qing Wang, Jiechao Xiong, Lei Han +5
We introduce Arena, a toolkit for multi-agent reinforcement learning (MARL) research. In MARL, it usually requires customizing observations, rewards and actions for each agent, cha…
Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments
Łukasz Kidziński, Sharada Prasanna Mohanty, Carmichael Ong +26
In the NIPS 2017 Learning to Run challenge, participants were tasked with building a controller for a musculoskeletal model to make it run as fast as possible through an obstacle c…