Lei Wu
15 papers in the PaperMetrix corpus
Papers by this author
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DRL-Scheduling: An Intelligent QoS-Aware Job Scheduling Framework for Applications in Clouds
2018 · IEEE Access
As an increasing number of traditional applications migrated to the cloud, achieving resource management and performance optimization in such a dynamic and uncertain environment becomes a big challenge for cloud-based application providers. In particular, job …
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Exploring supersymmetry with machine learning
2017 · arXiv (Cornell University)
Investigation of well-motivated parameter space in the theories of Beyond the Standard Model (BSM) plays an important role in new physics discoveries. However, a large-scale exploration of models with multi-parameter or equivalent solutions with a …
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EVulHunter: Detecting Fake Transfer Vulnerabilities for EOSIO's Smart Contracts at Webassembly-level
2019 · arXiv (Cornell University)
As one of the representative Delegated Proof-of-Stake (DPoS) blockchain platforms, EOSIO's ecosystem grows rapidly in recent years. A number of vulnerabilities and corresponding attacks of EOSIO's smart contracts have been discovered and observed in the …
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Global Convergence of Gradient Descent for Deep Linear Residual Networks
2019 · arXiv (Cornell University)
We analyze the global convergence of gradient descent for deep linear residual networks by proposing a new initialization: zero-asymmetric (ZAS) initialization. It is motivated by avoiding stable manifolds of saddle points. We prove that under …
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DEPOSafe: Demystifying the Fake Deposit Vulnerability in Ethereum Smart Contracts
2020 · arXiv (Cornell University)
Cryptocurrency has seen an explosive growth in recent years, thanks to the evolvement of blockchain technology and its economic ecosystem. Besides Bitcoin, thousands of cryptocurrencies have been distributed on blockchains, while hundreds of cryptocurrency exchanges …
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Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data
2021 · arXiv (Cornell University)
Self-supervised learning has enabled significant improvements on natural image benchmarks. However, there is less work in the medical imaging domain in this area. The optimal models have not yet been determined among the various options. …
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Understanding the Evolution of Blockchain Ecosystems: A Longitudinal Measurement Study of Bitcoin, Ethereum, and EOSIO
2021 · arXiv (Cornell University)
The continuing expansion of the blockchain ecosystems has attracted much attention from the research community. However, although a large number of research studies have been proposed to understand the diverse characteristics of individual blockchain systems …
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Conception of Applying Sovereign Blockchain Technology to Improve Tax Credit Management in Guangdong Province, China
2021
Presently, several problems still exist in tax credit management including inadequate collection of credit information, opaque process of credit rating evaluation and adjustment, insufficient pertinence of credit publicity results, and low social application degree of …
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THE HIERARCHICAL MODEL FOR NEWS RECOMMENDATION
2019 · Control and Intelligent Systems
ACTA Press publishes numerous proceedings like technical publications, scientific publications for power and energy systems and research papers for international conferences in the general areas of engineering and computer science.
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Penny Wise and Pound Foolish: Quantifying the Risk of Unlimited Approval of ERC20 Tokens on Ethereum
2022
The prosperity of decentralized finance motivates many investors to profit via trading their crypto assets on decentralized applications (DApps for short) of the Ethereum ecosystem. Apart from Ether (the native cryptocurrency of Ethereum), many ERC20 …
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Blockchain Enabled Secure Authentication for Unmanned Aircraft Systems
2021 · arXiv (Cornell University)
The integration of air and ground smart vehicles is becoming a new paradigm of future transportation. A decent number of smart unmanned vehicles or UAS will be sharing the national airspace for various purposes, such …
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A spectral-based analysis of the separation between two-layer neural networks and linear methods
2021 · arXiv (Cornell University)
We propose a spectral-based approach to analyze how two-layer neural networks separate from linear methods in terms of approximating high-dimensional functions. We show that quantifying this separation can be reduced to estimating the Kolmogorov width …
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An Unsupervised Convolutional Adversarial Anomaly Detection Model for IoT Data Infrastructure
2022
Anomaly detection is critical to ensure the IoT (Internet of Things) data infrastructures' Quality of Service. However, due to the complexity of incon-spicuous(indistinct) anomalies, high dynamicity, and lack of anomaly labels in the operational IoT …
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Theoretical Analysis of Inductive Biases in Deep Convolutional Networks
2023 · arXiv (Cornell University)
In this paper, we provide a theoretical analysis of the inductive biases in convolutional neural networks (CNNs). We start by examining the universality of CNNs, i.e., the ability to approximate any continuous functions. We prove …
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GradPower: Powering Gradients for Faster Language Model Pre-Training
2025 · ArXiv.org
We propose GradPower, a lightweight gradient-transformation technique for accelerating language model pre-training. Given a gradient vector $g=(g_i)_i$, GradPower first applies the elementwise sign-power transformation: $φ_p(g)=({\rm sign}(g_i)|g_i|^p)_{i}$ for a fixed $p>0$, and then feeds the transformed …