Zihao Wang

Tackling Long-Tailed Relations and Uncommon Entities in Knowledge Graph Completion

2019 · arXiv (Cornell University)

For large-scale knowledge graphs (KGs), recent research has been focusing on the large proportion of infrequent relations which have been ignored by previous studies. For example few-shot learning paradigm for relations has been investigated. In …

Sentiment Analysis of Home Appliance Comment Based on Generative Probabilistic Model

2019

Sentiment analysis plays important roles in the field of e-commerce. Not only the customers and end-users but also the suppliers and manufacturers take advantages of sentiment analysis results for product improvement. In this paper, based …

Perception Improvement for Free: Exploring Imperceptible Black-box Adversarial Attacks on Image Classification

2020 · arXiv (Cornell University)

Deep neural networks are vulnerable to adversarial attacks. White-box adversarial attacks can fool neural networks with small adversarial perturbations, especially for large size images. However, keeping successful adversarial perturbations imperceptible is especially challenging for transfer-based …

Benchmarking the Combinatorial Generalizability of Complex Query Answering on Knowledge Graphs

2021 · arXiv (Cornell University)

Complex Query Answering (CQA) is an important reasoning task on knowledge graphs. Current CQA learning models have been shown to be able to generalize from atomic operators to more complex formulas, which can be regarded …

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 …

Runtime verification of self-adaptive multi-agent system using probabilistic timed automata

2023 · Journal of Intelligent & Fuzzy Systems

The self-adaptive multi-agent system requires adaptive adjustments based on the dynamic environment during its runtime. Heterogeneous agent can accomplish different task goals, enhance the efficiency of system operation, but its complex collaboration problem poses new …

Modern synergetic neural network for imbalanced small data classification

2023 · Scientific Reports

Deep learning's performance on the imbalanced small data is substantially degraded by overfitting. Recurrent neural networks retain better performance in such tasks by constructing dynamical systems for robustness. Synergetic neural network (SNN), a synergetic-based recurrent …

EFAW: a new mining attack model combining FAW attacks with the Eclipse attack

2023 · Journal of Surveillance Security and Safety

Aim The Proof-of-Work consensus mechanism is the core mechanism of the blockchain, but the existing Fork After Withholding (FAW) attack can earn more rewards by launching attacks on the mining pools under the Proof-of-Work consensus …

Deep Reinforcement Learning Based Scheduling Strategy in Blockchain Payment Channel Networks

2024 · IEEE Transactions on Networking

With the popularity of blockchains, low transaction throughput has become a significant bottleneck in applications such as cryptocurrencies. Payment channel networks (PCNs) have received attention as a way to improve throughput. However, due to the …

Few-Shot Knowledge Graph Completion via Transfer Knowledge from Similar Tasks

2025

Knowledge graphs (KGs) are essential in many AI applications but often suffer from incompleteness, limiting their utility. Many relations in KGs have only a few examples, making it challenging to train accurate models. Few-shot learning …

Salience Estimation via Variational Auto-Encoders for Multi-Document Summarization

2017 · Proceedings of the AAAI Conference on Artificial Intelligence

We propose a new unsupervised sentence salience framework for Multi-Document Summarization (MDS), which can be divided into two components: latent semantic modeling and salience estimation. For latent semantic modeling, a neural generative model called Variational …

Neural Rating Regression with Abstractive Tips Generation for Recommendation

2017

Recently, some E-commerce sites launch a new interaction box called Tips on their mobile apps. Users can express their experience and feelings or provide suggestions using short texts typically several words or one sentence. In …