
A Deep ActorCritic Reinforcement Learning Framework for Dynamic Multichannel Access
To make efficient use of limited spectral resources, we in this work pro...
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Embedding Compression with Isotropic Iterative Quantization
Continuous representation of words is a standard component in deep learn...
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Enhancing Crosstask BlackBox Transferability of Adversarial Examples with Dispersion Reduction
Neural networks are known to be vulnerable to carefully crafted adversar...
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Interpretable Deep Graph Generation with NodeEdge CoDisentanglement
Disentangled representation learning has recently attracted a significan...
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Progressive Weight Pruning of Deep Neural Networks using ADMM
Deep neural networks (DNNs) although achieving humanlevel performance i...
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PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Realtime Execution on Mobile Devices
Model compression techniques on Deep Neural Network (DNN) have been wide...
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A Unified Framework of DNN Weight Pruning and Weight Clustering/Quantization Using ADMM
Many model compression techniques of Deep Neural Networks (DNNs) have be...
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A Lagrangian Dual Framework for Deep Neural Networks with Constraints
A variety of computationally challenging constrained optimization proble...
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An UltraEfficient MemristorBased DNN Framework with Structured Weight Pruning and Quantization Using ADMM
The high computation and memory storage of large deep neural networks (D...
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Anomalous Instance Detection in Deep Learning: A Survey
Deep Learning (DL) is vulnerable to outofdistribution and adversarial ...
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AutoSlim: An Automatic DNN Structured Pruning Framework for UltraHigh Compression Rates
Structured weight pruning is a representative model compression techniqu...
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MissionAware SpatioTemporal Deep Learning Model for UAS Instantaneous Density Prediction
The number of daily sUAS operations in uncontrolled low altitude airspac...
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Minor Privacy Protection Through Realtime Video Processing at the Edge
The collection of a lot of personal information about individuals, inclu...
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Domain Conditioned Adaptation Network
Tremendous research efforts have been made to thrive deep domain adaptat...
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Interference Channels With Arbitrarily Correlated Sources
Communicating arbitrarily correlated sources over interference channels ...
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The Common Information of N Dependent Random Variables
This paper generalizes Wyner's definition of common information of a pai...
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Wyner's Common Information: Generalizations and A New Lossy Source Coding Interpretation
Wyner's common information was originally defined for a pair of dependen...
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FFTBased Deep Learning Deployment in Embedded Systems
Deep learning has delivered its powerfulness in many application domains...
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Thoracic Disease Identification and Localization with Limited Supervision
Accurate identification and localization of abnormalities from radiology...
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Deep Reinforcement Learning: Framework, Applications, and Embedded Implementations
The recent breakthroughs of deep reinforcement learning (DRL) technique ...
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CirCNN: Accelerating and Compressing Deep Neural Networks Using BlockCirculantWeight Matrices
Largescale deep neural networks (DNNs) are both compute and memory inte...
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Continuous Authentication Using Oneclass Classifiers and their Fusion
While developing continuous authentication systems (CAS), we generally a...
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Robust Federated Learning Using ADMM in the Presence of Data Falsifying Byzantines
In this paper, we consider the problem of federated (or decentralized) l...
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Nonconvex LowRank Matrix Recovery with Arbitrary Outliers via MedianTruncated Gradient Descent
Recent work has demonstrated the effectiveness of gradient descent for d...
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Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank
Recently low displacement rank (LDR) matrices, or socalled structured m...
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Hidden Community Detection in Social Networks
We introduce a new paradigm that is important for community detection in...
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HardwareDriven Nonlinear Activation for Stochastic Computing Based Deep Convolutional Neural Networks
Recently, Deep Convolutional Neural Networks (DCNNs) have made unprecede...
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Blockdiagonal Hessianfree Optimization for Training Neural Networks
Secondorder methods for neural network optimization have several advant...
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A Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms
This paper proposes a new approach to construct high quality spacefilli...
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Reshaped Wirtinger Flow and Incremental Algorithm for Solving Quadratic System of Equations
We study the phase retrieval problem, which solves quadratic system of e...
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Nonparametric Detection of Geometric Structures over Networks
Nonparametric detection of existence of an anomalous structure over a ne...
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Universal Collaboration Strategies for Signal Detection: A Sparse Learning Approach
This paper considers the problem of high dimensional signal detection in...
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Consensus based Detection in the Presence of Data Falsification Attacks
This paper considers the problem of detection in distributed networks in...
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Separation of undersampled composite signals using the Dantzig selector with overcomplete dictionaries
In many applications one may acquire a composition of several signals th...
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Nonparametric Detection of Anomalous Data Streams
A nonparametric anomalous hypothesis testing problem is investigated, in...
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A KernelBased Nonparametric Test for Anomaly Detection over Line Networks
The nonparametric problem of detecting existence of an anomalous interva...
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Sharp Threshold for Multivariate MultiResponse Linear Regression via Block Regularized Lasso
In this paper, we investigate a multivariate multiresponse (MVMR) linea...
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Hybrid Maximum Likelihood Modulation Classification Using Multiple Radios
The performance of a modulation classifier is highly sensitive to channe...
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Solving Support Vector Machines in Reproducing Kernel Banach Spaces with Positive Definite Functions
In this paper we solve support vector machines in reproducing kernel Ban...
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A Deep Reinforcement LearningBased Framework for Content Caching
Content caching at the edge nodes is a promising technique to reduce the...
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Optimal Crowdsourced Classification with a Reject Option in the Presence of Spammers
We explore the design of an effective crowdsourcing system for an Mary ...
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Nonparametric Composite Hypothesis Testing in an Asymptotic Regime
We investigate the nonparametric, composite hypothesis testing problem f...
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Continuous User Authentication via Unlabeled Phone Movement Patterns
In this paper, we propose a novel continuous authentication system for s...
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Strongly Secure and Efficient Data Shuffle On Hardware Enclaves
Mitigating memoryaccess attacks on the Intel SGX architecture is an imp...
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SpecWatch: A Framework for Adversarial Spectrum Monitoring with Unknown Statistics
In cognitive radio networks (CRNs), dynamic spectrum access has been pro...
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An Area and Energy Efficient Design of DomainWall MemoryBased Deep Convolutional Neural Networks using Stochastic Computing
With recent trend of wearable devices and Internet of Things (IoTs), it ...
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VIBNN: Hardware Acceleration of Bayesian Neural Networks
Bayesian Neural Networks (BNNs) have been proposed to address the proble...
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Assessing the Utility of Weather Data for Photovoltaic Power Prediction
Photovoltaic systems have been widely deployed in recent times to meet t...
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Security Analysis and Enhancement of Model Compressed Deep Learning Systems under Adversarial Attacks
DNN is presenting humanlevel performance for many complex intelligent t...
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Power Control and Mode Selection for VBR Video Streaming in D2D Networks
In this paper, we investigate the problem of power control for streaming...
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Syracuse University
Syracuse University, founded in 1870 and comprised of thirteen schools and colleges, is a private research university in the heart of New York State.