97 citations · 312 across the 45 of their papers we have counts for
16 papers · 1 filter
Agent-Aware Training for Agent-Agnostic Action Advising in Deep Reinforcement Learning
Yaoquan Wei, Shunyu Liu, Jie Song +4
Action advising endeavors to leverage supplementary guidance from expert teachers to alleviate the issue of sampling inefficiency in Deep Reinforcement Learning (DRL). Previous age…
ModelGiF: Gradient Fields for Model Functional Distance
Jie Song, Zhengqi Xu, Sai Wu +2
The last decade has witnessed the success of deep learning and the surge of publicly released trained models, which necessitates the quantification of the model functional distance…
Adversarial Erasing with Pruned Elements: Towards Better Graph Lottery Ticket
Yuwen Wang, Shunyu Liu, Kaixuan Chen +5
Graph Lottery Ticket (GLT), a combination of core subgraph and sparse subnetwork, has been proposed to mitigate the computational cost of deep Graph Neural Networks (GNNs) on large…
Curricular Subgoals for Inverse Reinforcement Learning
Shunyu Liu, Yunpeng Qing, Shuqi Xu +6
Inverse Reinforcement Learning (IRL) aims to reconstruct the reward function from expert demonstrations to facilitate policy learning, and has demonstrated its remarkable success i…
Improving Expressivity of GNNs with Subgraph-specific Factor Embedded Normalization
Kaixuan Chen, Shunyu Liu, Tongtian Zhu +5
Graph Neural Networks (GNNs) have emerged as a powerful category of learning architecture for handling graph-structured data. However, existing GNNs typically ignore crucial struct…
Message-passing selection: Towards interpretable GNNs for graph classification
Wenda Li, Kaixuan Chen, Shunyu Liu +5
In this paper, we strive to develop an interpretable GNNs' inference paradigm, termed MSInterpreter, which can serve as a plug-and-play scheme readily applicable to various GNNs' b…
Lookaround Optimizer: steps around, 1 step average
Jiangtao Zhang, Shunyu Liu, Jie Song +3
Weight Average (WA) is an active research topic due to its simplicity in ensembling deep networks and the effectiveness in promoting generalization. Existing weight average approac…
Decentralized SGD and Average-direction SAM are Asymptotically Equivalent
Tongtian Zhu, Fengxiang He, Kaixuan Chen +2
Decentralized stochastic gradient descent (D-SGD) allows collaborative learning on massive devices simultaneously without the control of a central server. However, existing theorie…
Improved Projection-free Online Continuous Submodular Maximization
Yucheng Liao, Yuanyu Wan, Chang Yao +1
We investigate the problem of online learning with monotone and continuous DR-submodular reward functions, which has received great attention recently. To efficiently handle this p…
Is Centralized Training with Decentralized Execution Framework Centralized Enough for MARL?
Yihe Zhou, Shunyu Liu, Yunpeng Qing +4
Centralized Training with Decentralized Execution (CTDE) has recently emerged as a popular framework for cooperative Multi-Agent Reinforcement Learning (MARL), where agents can use…
Temporal Aggregation and Propagation Graph Neural Networks for Dynamic Representation
Tongya Zheng, Xinchao Wang, Zunlei Feng +6
Temporal graphs exhibit dynamic interactions between nodes over continuous time, whose topologies evolve with time elapsing. The whole temporal neighborhood of nodes reveals the va…
Generalization Matters: Loss Minima Flattening via Parameter Hybridization for Efficient Online Knowledge Distillation
Tianli Zhang, Mengqi Xue, Jiangtao Zhang +5
Most existing online knowledge distillation(OKD) techniques typically require sophisticated modules to produce diverse knowledge for improving students' generalization ability. In…
Schema Inference for Interpretable Image Classification
Haofei Zhang, Mengqi Xue, Xiaokang Liu +3
In this paper, we study a novel inference paradigm, termed as schema inference, that learns to deductively infer the explainable predictions by rebuilding the prior deep neural net…
Improved Dynamic Regret for Online Frank-Wolfe
Yuanyu Wan, Lijun Zhang, Mingli Song
To deal with non-stationary online problems with complex constraints, we investigate the dynamic regret of online Frank-Wolfe (OFW), which is an efficient projection-free algorithm…
Recent advances in artificial intelligence for retrosynthesis
Zipeng Zhong, Jie Song, Zunlei Feng +5
Retrosynthesis is the cornerstone of organic chemistry, providing chemists in material and drug manufacturing access to poorly available and brand-new molecules. Conventional rule-…
DepGraph: Towards Any Structural Pruning
Gongfan Fang, Xinyin Ma, Mingli Song +2
Structural pruning enables model acceleration by removing structurally-grouped parameters from neural networks. However, the parameter-grouping patterns vary widely across differen…