Search Results for author:
Found 22 papers, 2 papers with code
Identifying Tension in Holocaust Survivors’ Interview: Code-switching/Code-mixing as Cues
Our CS/CM annotated interview corpus is openly accessible.
DMSA: Dynamic Multi-scale Unsupervised Semantic Segmentation Based on Adaptive Affinity
The proposed method in this paper proposes an end-to-end unsupervised semantic segmentation architecture DMSA based on four loss functions.
A novel efficient Multi-view traffic-related object detection framework
With the rapid development of intelligent transportation system applications, a tremendous amount of multi-view video data has emerged to enhance vehicle perception.
Orthogonal-Time-Frequency-Space Signal Design for Integrated Data and Energy Transfer: Benefits from Doppler Offsets
Integrated data and energy transfer (IDET) is an advanced technology for enabling energy sustainability for massively deployed low-power electronic consumption components.
SISO-OFDM and MISO-OFDM Counterparts for "Wideband Waveforming for Integrated Data and Energy Transfer: Creating Extra Gain Beyond Multiple Antennas and Multiple Carriers"
In this article, we proposethe SISO-OFDM and MISO-OFDM based IDET systems, which are the counterparts of our optimal wideband waveforming strategy in [1].
QuatDE: Dynamic Quaternion Embedding for Knowledge Graph Completion
Knowledge graph embedding has been an active research topic for knowledge base completion (KGC), with progressive improvement from the initial TransE, TransH, RotatE et al to the current state-of-the-art QuatE.
Ranked #2 on
Link Prediction
on WN18
Connecting AI Learning and Blockchain Mining in 6G Systems
The sixth generation (6G) systems are generally recognized to be established on ubiquitous Artificial Intelligence (AI) and distributed ledger such as blockchain.
An Efficient One-Class SVM for Anomaly Detection in the Internet of Things
Insecure Internet of things (IoT) devices pose significant threats to critical infrastructure and the Internet at large; detecting anomalous behavior from these devices remains of critical importance, but fast, efficient, accurate anomaly detection (also called "novelty detection") for these classes of devices remains elusive.
End-to-End Jet Classification of Boosted Top Quarks with the CMS Open Data
We describe a novel application of the end-to-end deep learning technique to the task of discriminating top quark-initiated jets from those originating from the hadronization of a light quark or a gluon.
Exactly solvable model of Fermi arcs and pseudogap
We introduce a very simple and exactly solvable model that supports Fermi arcs in its ground state and excitation spectrum.
Strongly Correlated Electrons Superconductivity
6G Cellular Networks and Connected Autonomous Vehicles
With 5G mobile communication systems been commercially rolled out, research discussions on next generation mobile systems, i. e., 6G, have started.
Feature Extraction for Novelty Detection in Network Traffic
To facilitate such exploration, we develop a systematic framework, open-source toolkit, and public Python library that makes it both possible and easy to extract and generate features from network traffic and perform and end-to-end evaluation of these representations across most prevalent modern novelty detection models.
Distributed Resource Scheduling for Large-Scale MEC Systems: A Multi-Agent Ensemble Deep Reinforcement Learning with Imitation Acceleration
We consider the optimization of distributed resource scheduling to minimize the sum of task latency and energy consumption for all the Internet of things devices (IoTDs) in a large-scale mobile edge computing (MEC) system.
Reinforcement learning enabled cooperative spectrum sensing in cognitive radio networks
In cognitive radio (CR) networks, fast and accurate spectrum sensing plays a fundamental role in achieving high spectral efficiency.
AI Driven Heterogeneous MEC System with UAV Assistance for Dynamic Environment -- Challenges and Solutions
By taking full advantage of Computing, Communication and Caching (3C) resources at the network edge, Mobile Edge Computing (MEC) is envisioned as one of the key enablers for the next generation networks.
Stacked Auto Encoder Based Deep Reinforcement Learning for Online Resource Scheduling in Large-Scale MEC Networks
An online resource scheduling framework is proposed for minimizing the sum of weighted task latency for all the Internet of things (IoT) users, by optimizing offloading decision, transmission power and resource allocation in the large-scale mobile edge computing (MEC) system.
RL-Based User Association and Resource Allocation for Multi-UAV enabled MEC
In this paper, multi-unmanned aerial vehicle (UAV) enabled mobile edge computing (MEC), i. e., UAVE is studied, where several UAVs are deployed as flying MEC platform to provide computing resource to ground user equipments (UEs).
Machine Learning in High Energy Physics Community White Paper
In this document we discuss promising future research and development areas for machine learning in particle physics.
Point Set Registration With Global-Local Correspondence and Transformation Estimation
We present a new point set registration method with global-local correspondence and transformation estimation (GL-CATE).
Density Estimation via Discrepancy
Given i. i. d samples from some unknown continuous density on hyper-rectangle $[0, 1]^d$, we attempt to learn a piecewise constant function that approximates this underlying density non-parametrically.
Density Estimation via Discrepancy Based Adaptive Sequential Partition
Given $iid$ observations from an unknown absolute continuous distribution defined on some domain $\Omega$, we propose a nonparametric method to learn a piecewise constant function to approximate the underlying probability density function.
Simple one-pass algorithm for penalized linear regression with cross-validation on MapReduce
Key words: penalized linear regression, lasso, elastic-net, ridge, MapReduce
