Search Results for author: Xiaoyang Wang

Found 18 papers, 4 papers with code

RLOps: Development Life-cycle of Reinforcement Learning Aided Open RAN

no code implementations12 Nov 2021 Peizheng Li, Jonathan Thomas, Xiaoyang Wang, Ahmed Khalil, Abdelrahim Ahmad, Rui Inacio, Shipra Kapoor, Arjun Parekh, Angela Doufexi, Arman Shojaeifard, Robert Piechocki

We provide a taxonomy of the challenges faced by ML/RL models throughout the development life-cycle: from the system specification to production deployment (data acquisition, model design, testing and management, etc.).


Robust and Personalized Federated Learning with Spurious Features: an Adversarial Approach

no code implementations29 Sep 2021 Xiaoyang Wang, Han Zhao, Klara Nahrstedt, Oluwasanmi O Koyejo

To this end, we propose a strategy to mitigate the effect of spurious features based on our observation that the global model in the federated learning step has a low accuracy disparity due to statistical heterogeneity.

Personalized Federated Learning

AppQ: Warm-starting App Recommendation Based on View Graphs

no code implementations8 Sep 2021 Dan Su, Jiqiang Liu, Sencun Zhu, Xiaoyang Wang, Wei Wang, Xiangliang Zhang

In this work, we propose AppQ, a novel app quality grading and recommendation system that extracts inborn features of apps based on app source code.

Recommendation Systems

Combining Graph Neural Networks with Expert Knowledge for Smart Contract Vulnerability Detection

1 code implementation24 Jul 2021 Zhenguang Liu, Peng Qian, Xiaoyang Wang, Yuan Zhuang, Lin Qiu, Xun Wang

Then, we propose a novel temporal message propagation network to extract the graph feature from the normalized graph, and combine the graph feature with designed expert patterns to yield a final detection system.

Vulnerability Detection

Self-play Learning Strategies for Resource Assignment in Open-RAN Networks

no code implementations3 Mar 2021 Xiaoyang Wang, Jonathan D Thomas, Robert J Piechocki, Shipra Kapoor, Raul Santos-Rodriguez, Arjun Parekh

Open Radio Access Network (ORAN) is being developed with an aim to democratise access and lower the cost of future mobile data networks, supporting network services with various QoS requirements, such as massive IoT and URLLC.


NaturalConv: A Chinese Dialogue Dataset Towards Multi-turn Topic-driven Conversation

no code implementations3 Mar 2021 Xiaoyang Wang, Chen Li, Jianqiao Zhao, Dong Yu

To facilitate the research on this corpus, we provide results of several benchmark models.

Robusta: Robust AutoML for Feature Selection via Reinforcement Learning

no code implementations15 Jan 2021 Xiaoyang Wang, Bo Li, Yibo Zhang, Bhavya Kailkhura, Klara Nahrstedt

However, these AutoML pipelines only focus on improving the learning accuracy of benign samples while ignoring the ML model robustness under adversarial attacks.

AutoML Feature Importance +1

Identifying Coarse-grained Independent Causal Mechanisms with Self-supervision

1 code implementation 1st Conference on Causal Learning and Reasoning 2022 Xiaoyang Wang, Klara Nahrstedt, Oluwasanmi O Koyejo

Current approaches for learning disentangled representations assume that independent latent variables generate the data through a single data generation process.

Automatic Summarization of Open-Domain Podcast Episodes

no code implementations9 Nov 2020 Kaiqiang Song, Chen Li, Xiaoyang Wang, Dong Yu, Fei Liu

Instead, we investigate several less-studied aspects of neural abstractive summarization, including (i) the importance of selecting important segments from transcripts to serve as input to the summarizer; (ii) striking a balance between the amount and quality of training instances; (iii) the appropriate summary length and start/end points.

Abstractive Text Summarization

Lipschitz Learning for Signal Recovery

no code implementations4 Oct 2019 Hong Jiang, Jong-Hoon Ahn, Xiaoyang Wang

We will develop a theoretical framework to characterize the signals that can be robustly recovered from their observations by an ML algorithm, and establish a Lipschitz condition on signals and observations that is both necessary and sufficient for the existence of a robust recovery.

Compressive Sensing

STA: Spatial-Temporal Attention for Large-Scale Video-based Person Re-Identification

no code implementations9 Nov 2018 Yang Fu, Xiaoyang Wang, Yunchao Wei, Thomas Huang

Thus, a more robust clip-level feature representation can be generated according to a weighted sum operation guided by the mined 2-D attention score matrix.

Frame Large-Scale Person Re-Identification +1

Request-and-Reverify: Hierarchical Hypothesis Testing for Concept Drift Detection with Expensive Labels

no code implementations25 Jun 2018 Shujian Yu, Xiaoyang Wang, Jose C. Principe

In this paper, a novel Hierarchical Hypothesis Testing framework with Request-and-Reverify strategy is developed to detect concept drifts by requesting labels only when necessary.

General Classification Two-sample testing

Video Event Recognition With Deep Hierarchical Context Model

no code implementations CVPR 2015 Xiaoyang Wang, Qiang Ji

Video event recognition still faces great challenges due to large intra-class variation and low image resolution, in particular for surveillance videos.

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