84 citations · 518 across the 35 of their papers we have counts for
7 papers · 1 filter
The Effectiveness of Memory Replay in Large Scale Continual Learning
Yogesh Balaji, Mehrdad Farajtabar, Dong Yin +2
We study continual learning in the large scale setting where tasks in the input sequence are not limited to classification, and the outputs can be of high dimension. Among multiple…
Optimization and Generalization of Regularization-Based Continual Learning: a Loss Approximation Viewpoint
Dong Yin, Mehrdad Farajtabar, Ang Li +2
Neural networks have achieved remarkable success in many cognitive tasks. However, when they are trained sequentially on multiple tasks without access to old data, their performanc…
Learning to Incentivize Other Learning Agents
Jiachen Yang, Ang Li, Mehrdad Farajtabar +3
The challenge of developing powerful and general Reinforcement Learning (RL) agents has received increasing attention in recent years. Much of this effort has focused on the single…
The AVA-Kinetics Localized Human Actions Video Dataset
Ang Li, Meghana Thotakuri, David A. Ross +3
This paper describes the AVA-Kinetics localized human actions video dataset. The dataset is collected by annotating videos from the Kinetics-700 dataset using the AVA annotation pr…
MARS: Malleable Actor-Critic Reinforcement Learning Scheduler
Betis Baheri, Jacob Tronge, Bo Fang +3
In this paper, we introduce MARS, a new scheduling system for HPC-cloud infrastructures based on a cost-aware, flexible reinforcement learning approach, which serves as an intermed…
Hybrid Models for Open Set Recognition
Hongjie Zhang, Ang Li, Jie Guo +1
Open set recognition requires a classifier to detect samples not belonging to any of the classes in its training set. Existing methods fit a probability distribution to the trainin…
Data Efficient Training for Reinforcement Learning with Adaptive Behavior Policy Sharing
Ge Liu, Rui Wu, Heng-Tze Cheng +7
Deep Reinforcement Learning (RL) is proven powerful for decision making in simulated environments. However, training deep RL model is challenging in real world applications such as…