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Quantifying Educational Competition: A Game-Theoretic Model with Policy Implications

Autor: He, Siyuan

The competitive pressures in China's primary and secondary education system have persisted despite decades of policy interventions aimed at reducing academic burdens and alleviating parental anxiety. This paper develops a game-theoretic model to anal

Externí odkaz: http://arxiv.org/abs/2412.10974

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XMiner: Efficient Directed Subgraph Matching with Pattern Reduction

Autor: Yuan, Pingpeng, Wang, Yujiang, Ma, Tianyu, He, Siyuan, Liu, Ling

Graph pattern matching, one of the fundamental graph mining problems, aims to extract structural patterns of interest from an input graph. The state-of-the-art graph matching algorithms and systems are mainly designed for undirected graphs. Directed

Externí odkaz: http://arxiv.org/abs/2404.11105

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Escape with Your Self: A Solution to the Avoidance Problem with Decidable Bidirectional Typing for Reachability Types

Autor: Jia, Songlin, Wei, Guannan, He, Siyuan, Bao, Yuyan, Rompf, Tiark

Despite Rust's success in system programming, its ``shared XOR mutable'' principle significantly restricts how mutable values can be used, precluding many useful functional programming idioms. Reachability types are a recent proposal to address the k

Externí odkaz: http://arxiv.org/abs/2404.08217

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Adaptive Low Rank Adaptation of Segment Anything to Salient Object Detection

Autor: Cui, Ruikai, He, Siyuan, Qiu, Shi

Foundation models, such as OpenAI's GPT-3 and GPT-4, Meta's LLaMA, and Google's PaLM2, have revolutionized the field of artificial intelligence. A notable paradigm shift has been the advent of the Segment Anything Model (SAM), which has exhibited a r

Externí odkaz: http://arxiv.org/abs/2308.05426

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A Trustworthy Framework for Medical Image Analysis with Deep Learning

Autor: Ma, Kai, He, Siyuan, Xi, Pengcheng, Ebadi, Ashkan, Tremblay, Stéphane, Wong, Alexander

Computer vision and machine learning are playing an increasingly important role in computer-assisted diagnosis; however, the application of deep learning to medical imaging has challenges in data availability and data imbalance, and it is especially

Externí odkaz: http://arxiv.org/abs/2212.02764

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