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Found 42 papers, 13 papers with code
Ricci Curvature of the Internet Topology
Analysis of Internet topologies has shown that the Internet topology has negative curvature, measured by Gromov's "thin triangle condition", which is tightly related to core congestion and route reliability.
Social and Information Networks Computational Geometry Networking and Internet Architecture Physics and Society
JATE 2.0: Java Automatic Term Extraction with Apache Solr
Automatic Term Extraction (ATE) or Recognition (ATR) is a fundamental processing step preceding many complex knowledge engineering tasks.
Learning Translations via Matrix Completion
Bilingual Lexicon Induction is the task of learning word translations without bilingual parallel corpora.
SemRe-Rank: Improving Automatic Term Extraction By Incorporating Semantic Relatedness With Personalised PageRank
Extensively evaluated with 13 state-of-the-art base ATE methods on four datasets of diverse nature, it is shown to have achieved widespread improvement over all base methods and across all datasets, with up to 15 percentage points when measured by the Precision in the top ranked K candidate terms (the average for a set of K's), or up to 28 percentage points in F1 measured at a K that equals to the expected real terms in the candidates (F1 in short).
Performing Co-Membership Attacks Against Deep Generative Models
We conduct extensive experiments on a variety of datasets and generative models showing that: our attacker network outperforms prior membership attacks; co-membership attacks can be substantially more powerful than single attacks; and VAEs are more susceptible to membership attacks compared to GANs.
Network Alignment by Discrete Ollivier-Ricci Flow
In this work, we propose to use `Ricci flow metric', to define the distance between two nodes in a network.
Social and Information Networks Computational Geometry
Application-driven Privacy-preserving Data Publishing with Correlated Attributes
To address the privacy concerns of users in this environment, we propose a novel framework called PR-GAN that offers privacy-preserving mechanism using generative adversarial networks.
Data Augmentation for Rumor Detection Using Context-Sensitive Neural Language Model With Large-Scale Credibility Corpus
We present an offline data augmentation method based on semantic relatedness for rumor detection.
Community Detection on Networks with Ricci Flow
Many complex networks in the real world have community structures -- groups of well-connected nodes with important functional roles.
Social and Information Networks Physics and Society
Topology Based Scalable Graph Kernels
We propose a new graph kernel for graph classification and comparison using Ollivier Ricci curvature.
Neural Language Model Based Training Data Augmentation for Weakly Supervised Early Rumor Detection
Preliminary experiments with a state-of-the-art deep learning-based rumor detection model show that augmented data can alleviate over-fitting and class imbalance caused by limited train data and can help to train complex neural networks (NNs).
RP-DNN: A Tweet level propagation context based deep neural networks for early rumor detection in Social Media
Early rumor detection (ERD) on social media platform is very challenging when limited, incomplete and noisy information is available.
Approximation Algorithms for Multi-Robot Patrol-Scheduling with Min-Max Latency
The problem is NP-hard, as it has the traveling salesman problem as a special case (when $k=1$ and all sites have the same weight).
Visual Perception Model for Rapid and Adaptive Low-light Image Enhancement
The core of VP model is to decompose the light source into light intensity and light spatial distribution to describe the perception process of HVS, offering refinement estimation of illumination and reflectance.
Streaming Chunk-Aware Multihead Attention for Online End-to-End Speech Recognition
Recently, streaming end-to-end automatic speech recognition (E2E-ASR) has gained more and more attention.
Sound Audio and Speech Processing
Heterogeneous Interventions Reduce the Spread of COVID-19 in Simulations on Real Mobility Data
Major interventions have been introduced worldwide to slow down the spread of the SARS-CoV-2 virus.
Social and Information Networks Physics and Society
Deep Reinforcement Learning for Collaborative Edge Computing in Vehicular Networks
Mobile edge computing (MEC) is a promising technology to support mission-critical vehicular applications, such as intelligent path planning and safety applications.
Influencers and the Giant Component: the Fundamental Hardness in Privacy Protection for Socially Contagious Attributes
Experiments demonstrate that a giant connected component of infected nodes can and does appear in real-world networks and that a simple inference attack can reveal the status of a good fraction of nodes.
Inference Attack
Social and Information Networks
Ricci-GNN: Defending Against Structural Attacks Through a Geometric Approach
We propose a novel GNN defense algorithm against structural attacks that maliciously modify graph topology.
Physics-informed generative neural network: an application to troposphere temperature prediction
The generative neural network takes the mask as prior for the second-stage refined predictions.
Enhancing Knowledge Tracing via Adversarial Training
The original and adversarial examples are further used to jointly train the KT model, forcing it is not only to be robust to the adversarial examples, but also to enhance the generalization over the original ones.
Logically at Factify 2022: Multimodal Fact Verification
This paper describes our participant system for the multi-modal fact verification (Factify) challenge at AAAI 2022.
On Cyclic Solutions to the Min-Max Latency Multi-Robot Patrolling Problem
For the Euclidean version of the problem, for instance, combining our results with known results on Euclidean TSP, yields a PTAS for approximating an optimal cyclic solution, and it yields a $(2(1-1/k)+\varepsilon)$-approximation of the optimal unrestricted solution.
TCR: A Transformer Based Deep Network for Predicting Cancer Drugs Response
Our study highlights the prediction power of TCR and its potential value for cancer drug repurpose and precision oncology treatment.
Digital Twin-Empowered Network Planning for Multi-Tier Computing
Using a multi-tier computing paradigm with servers deployed at the core network, gateways, and base stations to support stateful applications, we aim to optimize long-term resource reservation by jointly minimizing the usage of computing, storage, and communication resources and the cost from reconfiguring resource reservation.
IDPL: Intra-subdomain adaptation adversarial learning segmentation method based on Dynamic Pseudo Labels
Secondly, the subdomain classifier module based on instance confidence is constructed, which can dynamically divide the target domain into easy and difficult subdomains according to the relative proportion of easy and difficult instances.
Holistic Network Virtualization and Pervasive Network Intelligence for 6G
The pervasive network intelligence integrates AI into future networks from the perspectives of networking for AI and AI for networking, respectively.
Logically at Factify 2: A Multi-Modal Fact Checking System Based on Evidence Retrieval techniques and Transformer Encoder Architecture
In this paper, we present the Logically submissions to De-Factify 2 challenge (DE-FACTIFY 2023) on the task 1 of Multi-Modal Fact Checking.
Understanding the Complexity and Its Impact on Testing in ML-Enabled Systems
Machine learning (ML) enabled systems are emerging with recent breakthroughs in ML.
VISAR: A Human-AI Argumentative Writing Assistant with Visual Programming and Rapid Draft Prototyping
In argumentative writing, writers must brainstorm hierarchical writing goals, ensure the persuasiveness of their arguments, and revise and organize their plans through drafting.
PhysBench: A Benchmark Framework for Remote Physiological Sensing with New Dataset and Baseline
In recent years, due to the widespread use of internet videos, physiological remote sensing has gained more and more attention in the fields of affective computing and telemedicine.
Digital Twin-Based 3D Map Management for Edge-Assisted Mobile Augmented Reality
In this paper, we design a 3D map management scheme for edge-assisted mobile augmented reality (MAR) to support the pose estimation of individual MAR device, which uploads camera frames to an edge server.
Efficient Partitioning Method of Large-Scale Public Safety Spatio-Temporal Data based on Information Loss Constraints
It can also ensure the load balancing of distributed storage while maintaining spatio-temporal proximity of the data partitioning results.
Ultrasound Image Segmentation of Thyroid Nodule via Latent Semantic Feature Co-Registration
Segmentation of nodules in thyroid ultrasound imaging plays a crucial role in the detection and treatment of thyroid cancer.
User Dynamics-Aware Edge Caching and Computing for Mobile Virtual Reality
The proposed approach aims to maximize VR video streaming performance, i. e., minimizing video frame missing rate, by proactively caching popular VR video chunks and adaptively scheduling computing resources at an edge server based on user and network dynamics.
Digital Twin-Based User-Centric Edge Continual Learning in Integrated Sensing and Communication
A DT of the ISAC device is constructed to predict the impact of potential decisions on the long-term computation cost of the server, based on which the decisions are made with closed-form formulas.
PAC Privacy Preserving Diffusion Models
Data privacy protection is garnering increased attention among researchers.
Composite Active Learning: Towards Multi-Domain Active Learning with Theoretical Guarantees
In this paper, we propose the first general method, dubbed composite active learning (CAL), for multi-domain AL. Our approach explicitly considers the domain-level and instance-level information in the problem; CAL first assigns domain-level budgets according to domain-level importance, which is estimated by optimizing an upper error bound that we develop; with the domain-level budgets, CAL then leverages a certain instance-level query strategy to select samples to label from each domain.
Differentially Private Range Queries with Correlated Input Perturbation
This work proposes a class of locally differentially private mechanisms for linear queries, in particular range queries, that leverages correlated input perturbation to simultaneously achieve unbiasedness, consistency, statistical transparency, and control over utility requirements in terms of accuracy targets expressed either in certain query margins or as implied by the hierarchical database structure.
HelixFold-Multimer: Elevating Protein Complex Structure Prediction to New Heights
While monomer protein structure prediction tools boast impressive accuracy, the prediction of protein complex structures remains a daunting challenge in the field.
EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple Extraction
Multi-triple extraction is a challenging task due to the existence of informative inter-triple correlations, and consequently rich interactions across the constituent entities and relations. While existing works only explore entity representations, we propose to explicitly introduce relation representation, jointly represent it with entities, and novelly align them to identify valid triples. We perform comprehensive experiments on document-level relation extraction and joint entity and relation extraction along with ablations to demonstrate the advantage of the proposed method.
Document-level Relation Extraction
Joint Entity and Relation Extraction
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