137 citations · 412 across the 61 of their papers we have counts for
11 papers · 1 filter
Learning Robust Policy against Disturbance in Transition Dynamics via State-Conservative Policy Optimization
Yufei Kuang, Miao Lu, Jie Wang +3
Deep reinforcement learning algorithms can perform poorly in real-world tasks due to the discrepancy between source and target environments. This discrepancy is commonly viewed as…
Sample-Efficient Reinforcement Learning via Conservative Model-Based Actor-Critic
Zhihai Wang, Jie Wang, Qi Zhou +2
Model-based reinforcement learning algorithms, which aim to learn a model of the environment to make decisions, are more sample efficient than their model-free counterparts. The sa…
Dual Progressive Prototype Network for Generalized Zero-Shot Learning
Chaoqun Wang, Shaobo Min, Xuejin Chen +2
Generalized Zero-Shot Learning (GZSL) aims to recognize new categories with auxiliary semantic information,e.g., category attributes. In this paper, we handle the critical issue of…
Discovering Representation Sprachbund For Multilingual Pre-Training
Yimin Fan, Yaobo Liang, Alexandre Muzio +4
Multilingual pre-trained models have demonstrated their effectiveness in many multilingual NLP tasks and enabled zero-shot or few-shot transfer from high-resource languages to low…
Conditional DETR for Fast Training Convergence
Depu Meng, Xiaokang Chen, Zejia Fan +5
The recently-developed DETR approach applies the transformer encoder and decoder architecture to object detection and achieves promising performance. In this paper, we handle the c…
Supervised Off-Policy Ranking
Yue Jin, Yue Zhang, Tao Qin +4
Off-policy evaluation (OPE) is to evaluate a target policy with data generated by other policies. Most previous OPE methods focus on precisely estimating the true performance of a…
Dual-view Molecule Pre-training
Jinhua Zhu, Yingce Xia, Tao Qin +3
Inspired by its success in natural language processing and computer vision, pre-training has attracted substantial attention in cheminformatics and bioinformatics, especially for m…
Task-Independent Knowledge Makes for Transferable Representations for Generalized Zero-Shot Learning
Chaoqun Wang, Xuejin Chen, Shaobo Min +2
Generalized Zero-Shot Learning (GZSL) targets recognizing new categories by learning transferable image representations. Existing methods find that, by aligning image representatio…
ProphetNet-X: Large-Scale Pre-training Models for English, Chinese, Multi-lingual, Dialog, and Code Generation
Weizhen Qi, Yeyun Gong, Yu Yan +9
Now, the pre-training technique is ubiquitous in natural language processing field. ProphetNet is a pre-training based natural language generation method which shows powerful perfo…
Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking
Ning Wang, Wengang Zhou, Jie Wang +1
In video object tracking, there exist rich temporal contexts among successive frames, which have been largely overlooked in existing trackers. In this work, we bridge the individua…
IOT: Instance-wise Layer Reordering for Transformer Structures
Jinhua Zhu, Lijun Wu, Yingce Xia +5
With sequentially stacked self-attention, (optional) encoder-decoder attention, and feed-forward layers, Transformer achieves big success in natural language processing (NLP), and…