Search Results for author: Junwei Zhang

Found 10 papers, 3 papers with code

Accelerated Cloud for Artificial Intelligence (ACAI)

no code implementations30 Jan 2024 Dachi Chen, Weitian Ding, Chen Liang, Chang Xu, Junwei Zhang, Majd Sakr

Training an effective Machine learning (ML) model is an iterative process that requires effort in multiple dimensions.

Scheduling

PointCA: Evaluating the Robustness of 3D Point Cloud Completion Models Against Adversarial Examples

no code implementations22 Nov 2022 Shengshan Hu, Junwei Zhang, Wei Liu, Junhui Hou, Minghui Li, Leo Yu Zhang, Hai Jin, Lichao Sun

In addition, existing attack approaches towards point cloud classifiers cannot be applied to the completion models due to different output forms and attack purposes.

Adversarial Attack Point Cloud Classification +2

Double-Scale Self-Supervised Hypergraph Learning for Group Recommendation

1 code implementation9 Sep 2021 Junwei Zhang, Min Gao, Junliang Yu, Lei Guo, Jundong Li, Hongzhi Yin

Technically, for (1), a hierarchical hypergraph convolutional network based on the user- and group-level hypergraphs is developed to model the complex tuplewise correlations among users within and beyond groups.

Evolutionary Generative Adversarial Networks with Crossover Based Knowledge Distillation

1 code implementation27 Jan 2021 Junjie Li, Junwei Zhang, Xiaoyu Gong, Shuai Lü

Generative Adversarial Networks (GAN) is an adversarial model, and it has been demonstrated to be effective for various generative tasks.

Knowledge Distillation

Proximal Policy Optimization via Enhanced Exploration Efficiency

no code implementations11 Nov 2020 Junwei Zhang, Zhenghao Zhang, Shuai Han, Shuai Lü

Based on continuous control tasks with dense reward, this paper analyzes the assumption of the original Gaussian action exploration mechanism in PPO algorithm, and clarifies the influence of exploration ability on performance.

Continuous Control reinforcement-learning +1

Path-Based Reasoning over Heterogeneous Networks for Recommendation via Bidirectional Modeling

1 code implementation10 Aug 2020 Junwei Zhang, Min Gao, Junliang Yu, Linda Yang, Zongwei Wang, Qingyu Xiong

Despite their effectiveness, these models are often confronted with the following limitations: (1) Most prior path-based reasoning models only consider the influence of the predecessors on the subsequent nodes when modeling the sequences, and ignore the reciprocity between the nodes in a path; (2) The weights of nodes in the same path instance are usually assumed to be constant, whereas varied weights of nodes can bring more flexibility and lead to expressive modeling; (3) User-item interactions are noisy, but they are often indiscriminately exploited.

Explainable Recommendation Recommendation Systems

Recommender Systems Based on Generative Adversarial Networks: A Problem-Driven Perspective

no code implementations5 Mar 2020 Min Gao, Junwei Zhang, Junliang Yu, Jundong Li, Junhao Wen, Qingyu Xiong

In general, two lines of research have been conducted, and their common ideas can be summarized as follows: (1) for the data noise issue, adversarial perturbations and adversarial sampling-based training often serve as a solution; (2) for the data sparsity issue, data augmentation--implemented by capturing the distribution of real data under the minimax framework--is the primary coping strategy.

Data Augmentation Recommendation Systems

Recruitment-imitation Mechanism for Evolutionary Reinforcement Learning

no code implementations13 Dec 2019 Shuai Lü, Shuai Han, Wenbo Zhou, Junwei Zhang

In this paper, we propose Recruitment-imitation Mechanism (RIM) for evolutionary reinforcement learning, a scalable framework that combines advantages of the three methods mentioned above.

Continuous Control Efficient Exploration +4

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