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09/16/2023
Accelerating In-Browser Deep Learning Inference on Diverse Edge Clients through Just-in-Time Kernel Optimizations
Web applications are increasingly becoming the primary platform for AI s...
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07/11/2023
Reinforcement Learning with Non-Cumulative Objective
In reinforcement learning, the objective is almost always defined as a c...
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02/23/2023
Uncertainty Injection: A Deep Learning Method for Robust Optimization
This paper proposes a paradigm of uncertainty injection for training dee...
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02/23/2023
Amos-SLAM: An Anti-Dynamics Two-stage SLAM Approach
The traditional Simultaneous Localization And Mapping (SLAM) systems rel...
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09/21/2022
AirFi: Empowering WiFi-based Passive Human Gesture Recognition to Unseen Environment via Domain Generalization
WiFi-based smart human sensing technology enabled by Channel State Infor...
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09/21/2022
Machine Learning on generalized Complete Intersection Calabi-Yau Manifolds
Generalized Complete Intersection Calabi-Yau Manifold (gCICY) is a new c...
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01/04/2022
Efficient Quantum Feature Extraction for CNN-based Learning
Recent work has begun to explore the potential of parametrized quantum c...
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12/08/2021
Active Sensing for Communications by Learning
This paper proposes a deep learning approach to a class of active sensin...
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08/03/2021
Bayesian spectral density approach for identification and uncertainty quantification of bridge section's flutter derivatives operated in turbulent flow
This study presents a Bayesian spectral density approach for identificat...
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06/20/2021
Life-cycle assessment for flutter probability of a long-span suspension bridge based on field monitoring data
Assessment of structural safety status is of paramount importance for ex...
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05/10/2021
A Sharp Analysis of Covariate Adjusted Precision Matrix Estimation via Alternating Gradient Descent with Hard Thresholding
In this paper, we present a sharp analysis for an alternating gradient d...
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04/07/2021
Time-Data Tradeoffs in Structured Signals Recovery via Proximal-Gradient Homotopy Method
In this paper, we characterize data-time tradeoffs of the proximal-gradi...
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03/24/2021
Quantized Corrupted Sensing with Random Dithering
Corrupted sensing concerns the problem of recovering a high-dimensional ...
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01/03/2021
Phase Transitions in Recovery of Structured Signals from Corrupted Measurements
This paper is concerned with the problem of recovering a structured sign...
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12/22/2020
Scalable Deep Reinforcement Learning for Routing and Spectrum Access in Physical Layer
This paper proposes a novel and scalable reinforcement learning approach...
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11/06/2020
Threats and Opportunities: Blockchain Meets Quantum Computation
This article considered deficiencies of the flourishing blockchain techn...
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09/05/2020
A Simple and General Graph Neural Network with Stochastic Message Passing
Graph neural networks (GNNs) are emerging machine learning models on gra...
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08/05/2020
Spectrally Sparse Signal Recovery via Hankel Matrix Completion with Prior Information
This paper studies the problem of reconstructing spectrally sparse signa...
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06/18/2020
Algorithmic Decision Making with Conditional Fairness
Nowadays fairness issues have raised great concerns in decision-making s...
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01/05/2020
Matrix Completion with Prior Subspace Information via Maximizing Correlation
This paper studies the problem of completing a low-rank matrix from a fe...
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10/16/2019
Covariance Matrix Estimation from Correlated Sub-Gaussian Samples
This paper studies the problem of estimating a covariance matrix from co...
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08/29/2019
Data-based wind disaster climate identification algorithm and extreme wind speed prediction
An extreme wind speed estimation method that considers wind hazard clima...
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05/11/2019
ECG Identification under Exercise and Rest Situations via Various Learning Methods
As the advancement of information security, human recognition as its cor...
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01/29/2019
Performance comparison of an AI-based Adaptive Learning System in China
Adaptive learning systems stand apart from traditional learning systems ...
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01/24/2019
Recovery of Structured Signals From Corrupted Non-Linear Measurements
This paper studies the problem of recovering a structured signal from a ...
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08/04/2018
Spatial Deep Learning for Wireless Scheduling
The optimal scheduling of interfering links in a dense wireless network ...
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08/03/2018
Covariance Matrix Estimation from Correlated Samples
Covariance matrix estimation concerns the problem of estimating the cova...
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12/11/2017
Identifying the Mislabeled Training Samples of ECG Signals using Machine Learning
The classification accuracy of electrocardiogram signal is often affecte...
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05/24/2017