Meng Li

Blockchain-Enabled Secure Energy Trading With Verifiable Fairness in Industrial Internet of Things

2020 · IEEE Transactions on Industrial Informatics

Energy trading in Industrial Internet of Things (IIoT), a fundamental approach to realize Industry 4.0, plays a vital role in satisfying energy demands and optimizing system efficiency. Existing research works utilize a utility company to …

Short-term photovoltaic power prediction based on FVS-KELM method

2020 · Journal of Applied Science and Engineering

ABSTRACT For the highly nonlinear short-term photovoltaic power problems affected by a variety of factors, a novel modeling method FVS-KELM based on feature vectors selection (FVS) algorithm and kernel extreme learning machine (KELM) is proposed. …

CPT: Efficient Deep Neural Network Training via Cyclic Precision

2021 · arXiv (Cornell University)

Low-precision deep neural network (DNN) training has gained tremendous attention as reducing precision is one of the most effective knobs for boosting DNNs' training time/energy efficiency. In this paper, we attempt to explore low-precision training …

SID: Incremental Learning for Anchor-Free Object Detection via Selective and Inter-Related Distillation

2020 · arXiv (Cornell University)

Incremental learning requires a model to continually learn new tasks from streaming data. However, traditional fine-tuning of a well-trained deep neural network on a new task will dramatically degrade performance on the old task -- …

Sharded Blockchain for Collaborative Computing in the Internet of Things: Combined of Dynamic Clustering and Deep Reinforcement Learning Approach

2022 · IEEE Internet of Things Journal

Immutability, decentralization, and linear promoted scalability make the sharded blockchain a promising solution, which can effectively address the trust issue in the large-scale Internet of Things (IoT). However, currently, the throughput of sharded blockchains is …

Blockchain Sharding Strategy for Collaborative Computing Internet of Things Combining Dynamic Clustering and Deep Reinforcement Learning

2022

Immutability, decentralization, and linear promoted scalability make sharded blockchain a promising solution, which can effectively address the trust issue in the large-scale Internet of Things (IoT). However, currently, the throughput of sharded blockchains is still …

CoPriv: Network/Protocol Co-Optimization for Communication-Efficient Private Inference

2023 · arXiv (Cornell University)

Deep neural network (DNN) inference based on secure 2-party computation (2PC) can offer cryptographically-secure privacy protection but suffers from orders of magnitude latency overhead due to enormous communication. Previous works heavily rely on a proxy …

Ironman: Accelerating Oblivious Transfer Extension for Privacy-Preserving AI with Near-Memory Processing

2025 · arXiv (Cornell University)

With the wide application of machine learning (ML), privacy concerns arise with user data as they may contain sensitive information. Privacy-preserving ML (PPML) based on cryptographic primitives has emerged as a promising solution in which …