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07/18/2023
Pixel-wise Graph Attention Networks for Person Re-identification
Graph convolutional networks (GCN) is widely used to handle irregular da...
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12/30/2022
Multisensor Multiobject Tracking With High-Dimensional Object States
Passive monitoring of acoustic or radio sources has important applicatio...
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12/30/2022
Active Planning for Cooperative Localization: A Fisher Information Approach
Location-aware networks will introduce new services and applications for...
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12/15/2022
Co-Learning with Pre-Trained Networks Improves Source-Free Domain Adaptation
Source-free domain adaptation aims to adapt a source model trained on fu...
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06/16/2022
Domain Generalization via Selective Consistency Regularization for Time Series Classification
Domain generalization methods aim to learn models robust to domain shift...
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05/30/2022
Few-Shot Adaptation of Pre-Trained Networks for Domain Shift
Deep networks are prone to performance degradation when there is a domai...
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09/23/2021
An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series
Several techniques for multivariate time series anomaly detection have b...
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03/16/2021
Graph-Based Multiobject Tracking with Embedded Particle Flow
Seamless situational awareness provided by modern radar systems relies o...
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02/17/2021
POLA: Online Time Series Prediction by Adaptive Learning Rates
Online prediction for streaming time series data has practical use for m...
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02/17/2021
Robust Domain-Free Domain Generalization with Class-aware Alignment
While deep neural networks demonstrate state-of-the-art performance on a...
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10/21/2020
Conformance Checking for a Medical Training Process Using Petri net Simulation and Sequence Alignment
Process Mining has recently gained popularity in healthcare due to its p...
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08/24/2020
Hierarchical Adaptive Lasso: Learning Sparse Neural Networks with Shrinkage via Single Stage Training
Deep neural networks achieve state-of-the-art performance in a variety o...
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07/18/2020
Modeling Nonlinear Growth Followed by Long-Memory Equilibrium with Unknown Change Point
Measurements of many biological processes are characterized by an initia...
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03/26/2020
CAZSL: Zero-Shot Regression for Pushing Models by Generalizing Through Context
Learning accurate models of the physical world is required for a lot of ...
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01/27/2020
Multi-label Prediction in Time Series Data using Deep Neural Networks
This paper addresses a multi-label predictive fault classification probl...
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12/19/2018
Toward Intelligent Network Optimization in Wireless Networking: An Auto-learning Framework
In wireless communication systems (WCSs), the network optimization probl...
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10/15/2018
ABACUS: Unsupervised Multivariate Change Detection via Bayesian Source Separation
Change detection involves segmenting sequential data such that observati...
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06/14/2018
Financial Forecasting and Analysis for Low-Wage Workers
Despite the plethora of financial services and products on the market no...
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12/21/2015