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Oct 26, 2020
Computer Vision

GreedyFool: Distortion-Aware Sparse Adversarial Attack

Modern deep neural networks(DNNs) are vulnerable to adversarial samples. Sparse adversarial samples are a special branch of adversarial samples that …
Oct 26, 2020
Computer Vision

GAN Mask R-CNN:Instance semantic segmentation benefits from generat…

In designing instance segmentation ConvNets that reconstruct masks, segmentation is often taken as its literal definition -- assigning label to every…
Oct 26, 2020
Computer Vision
Artificial Intelligence

Handgun detection using combined human pose and weapon appearance

CCTV surveillance systems are essential nowadays to prevent and mitigate security threats or dangerous situations such as mass shootings or terrorist…
Oct 26, 2020
Cryptography and Security
Machine Learning

Robust and Verifiable Information Embedding Attacks to Deep Neural …

In the era of deep learning, a user often leverages a third-party machine learning tool to train a deep neural network (DNN) classifier and then depl…
Oct 26, 2020
Computer Vision
Machine Learning
Robotics

Demo Abstract: Indoor Positioning System in Visually-Degraded Envir…

Positional estimation is of great importance in the public safety sector. Emergency responders such as fire fighters, medical rescue teams, and the p…
Oct 26, 2020
Machine Learning
Plasma Physics

Meaningful uncertainties from deep neural network surrogates of lar…

Large-scale numerical simulations are used across many scientific disciplines to facilitate experimental development and provide insights into underl…
Oct 26, 2020
Machine Learning
Distributed
Parallel
and Cluster Computing
Networking and Internet Architecture

Real-Time Edge Classification: Optimal Offloading under Token Bucket …

To deploy machine learning-based algorithms for real-time applications with strict latency constraints, we consider an edge-computing setting where a…
Oct 26, 2020
Machine Learning

Reinforcement Learning Enhanced Heterogeneous Graph Neural Network

Heterogeneous Information Networks (HINs), involving a diversity of node types and relation types, are pervasive in many real-world applications. Rec…
Oct 26, 2020
Machine Learning

Random Geometric Graphs on Euclidean Balls

We consider a latent space model for random graphs where a node $i$ is associated to a random latent point $X_i$ on the Euclidean unit ball. The prob…
Oct 26, 2020
Signal Processing
Machine Learning
Neural and Evolutionary Computation

Dyslexia detection from EEG signals using SSA component correlation a…

Objective dyslexia diagnosis is not a straighforward task since it is traditionally performed by means of the intepretation of different behavioural …
Oct 26, 2020
Machine Learning
Distributed
Parallel
and Cluster Computing

Optimal Client Sampling for Federated Learning

It is well understood that client-master communication can be a primary bottleneck in Federated Learning. In this work, we address this issue with a …
Oct 26, 2020
Computer Vision
Human-Computer Interaction

ActiveNet: A computer-vision based approach to determine lethargy

The outbreak of COVID-19 has forced everyone to stay indoors, fabricating a significant drop in physical activeness. Our work is constructed upon the…
Oct 26, 2020
Machine Learning
Artificial Intelligence

Track-Assignment Detailed Routing Using Attention-based Policy Model …

Detailed routing is one of the most critical steps in analog circuit design. Complete routing has become increasingly more challenging in advanced no…
Oct 26, 2020
Computation and Language
Artificial Intelligence

A Survey of Embedding Space Alignment Methods for Language and Knowle…

Neural embedding approaches have become a staple in the fields of computer vision, natural language processing, and more recently, graph analytics. G…
Oct 26, 2020
Chemical Physics
Machine Learning
Computational Physics

Infrared spectra of neutral polycyclic aromatic hydrocarbons by machi…

The Interest in polycyclic aromatic hydrocarbons (PAHs) spans numerous fields and infrared spectroscopy is usually the method of choice to disentangl…
Oct 26, 2020
Machine Learning
Artificial Intelligence

Forethought and Hindsight in Credit Assignment

We address the problem of credit assignment in reinforcement learning and explore fundamental questions regarding the way in which an agent can best …
Oct 26, 2020
Machine Learning
Applications

Data Segmentation via t-SNE, DBSCAN, and Random Forest

This research proposes a data segmentation technique which is easy to interpret and generalizes well. The technique combines t-SNE, DBSCAN, and Rando…
Oct 26, 2020
Machine Learning

In this work, we bound the change in output of spectral graph filters under a specific form of topological perturbation, i.e., edge rewiring, where the bound involves terms which have a structural interpretation. We then demonstrate a practical appl…

On the Stability of Graph Convolutional Neural Networks under Edge …

Graph neural networks are experiencing a surge of popularity within the machine learning community due to their ability to adapt to non-Euclidean dom…
Oct 26, 2020
Machine Learning
Optimization and Control

We thank Yossi Arjevani for a helpful conversation.

Tight last-iterate convergence rates for no-regret learning in mult…

We study the question of obtaining last-iterate convergence rates for no-regret learning algorithms in multi-player games. We show that the optimisti…
Oct 26, 2020
Computer Vision
Multiagent Systems

This paper has presented a new multi-target tracking approach for a distributed camera network, providing a global approach that deals with the distributed fusion of low and high level information. In this work, the challenges of the distributed sys…

Distributed Multi-Target Tracking in Camera Networks

Most recent works on multi-target tracking with multiple cameras focus on centralized systems. In contrast, this paper presents a multi-target tracki…
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