
MIMO OFDM DualFunction RadarCommunication Under Error Rate and Beampattern Constraints
In this work we consider a multipleinput multipleoutput (MIMO) dualfu...
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Learning Invariant Representation with Consistency and Diversity for Semisupervised Source Hypothesis Transfer
Semisupervised domain adaptation (SSDA) aims to solve tasks in target d...
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An Encoding Approach for Stable Change Point Detection
Without imposing prior distributional knowledge underlying multivariate ...
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Two stages for visual object tracking
Siamesebased trackers have achived promising performance on visual obje...
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Coarse and finescale geometric information content of Multiclass Classification and implied Datadriven Intelligence
Under any Multiclass Classification (MCC) setting defined by a collectio...
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SoftwareHardware Codesign for Fast and Scalable Training of Deep Learning Recommendation Models
Deep learning recommendation models (DLRMs) are used across many busines...
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Discovering Multiple Phases of Dynamics by Dissecting Multivariate Time Series
We proposed a datadriven approach to dissect multivariate time series i...
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Reconfigurableintelligentsurfaceassisted Downlink Transmission Design via Bayesian Optimization
This paper investigates the transmission design in the reconfigurablein...
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Privacypreserving Channel Estimation in Cellfree Hybrid Massive MIMO Systems
We consider a cellfree hybrid massive multipleinput multipleoutput (M...
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Unraveling S P500 stock volatility and networks – An encoding and decoding approach
We extend the Hierarchical Factor Segmentation(HFS) algorithm for discov...
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Unfolded Deep Neural Network (UDNN) for High Mobility Channel Estimation
High mobility channel estimation is crucial for beyond 5G (B5G) or 6G wi...
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Understanding Training Efficiency of Deep Learning Recommendation Models at Scale
The use of GPUs has proliferated for machine learning workflows and is n...
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GEVO: GPU Code Optimization using EvolutionaryComputation
GPUs are a key enabler of the revolution in machine learning and high pe...
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GEVO: GPU Code Optimization using Evolutionary Computation
GPUs are a key enabler of the revolution in machine learning and high pe...
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Longterm scheduling and power control for wirelessly powered cellfree IoT
We investigate the longterm scheduling and power control scheme for a w...
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Deep Learning Training in Facebook Data Centers: Design of Scaleup and Scaleout Systems
Largescale training is important to ensure high performance and accurac...
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Progressive Local Filter Pruning for Image Retrieval Acceleration
This paper focuses on network pruning for image retrieval acceleration. ...
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DeepRecSys: A System for Optimizing EndToEnd Atscale Neural Recommendation Inference
Neural personalized recommendation is the cornerstone of a wide collect...
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RecNMP: Accelerating Personalized Recommendation with NearMemory Processing
Personalized recommendation systems leverage deep learning models and ac...
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Language ModelDriven Unsupervised Neural Machine Translation
Unsupervised neural machine translation(NMT) is associated with noise an...
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SubCharacter ChineseEnglish Neural Machine Translation with Wubi encoding
Neural machine translation (NMT) is one of the best methods for understa...
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Exploiting Parallelism Opportunities with Deep Learning Frameworks
Stateoftheart machine learning frameworks support a wide variety of d...
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Deep Reinforcement Learning for Unmanned Aerial VehicleAssisted Vehicular Networks
Unmanned aerial vehicles (UAVs) are envisioned to complement the 5G comm...
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Deep Reinforcement Learning for Unmanned Aerial VehicleAssisted Vehicular Networks in Smart Cities
Unmanned aerial vehicles (UAVs) are envisioned to complement the 5G comm...
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The Architectural Implications of Facebook's DNNbased Personalized Recommendation
The widespread application of deep learning has changed the landscape of...
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Multidimensional Spectral SuperResolution with Prior Knowledge via FrequencySelective Vandermonde Decomposition and ADMM
This paper is concerned with estimation of multiple frequencies from inc...
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Deep Learning Recommendation Model for Personalization and Recommendation Systems
With the advent of deep learning, neural networkbased recommendation mo...
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Compressive Multidimensional Harmonic Retrieval with Prior Knowledge
This paper concerns the problem of estimating multidimensional (MD) freq...
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Spectral Method for Phase Retrieval: an Expectation Propagation Perspective
Phase retrieval refers to the problem of recovering a signal x_∈C^n from...
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Secure Distributed Dynamic State Estimation in WideArea Smart Grids
Smart grid is a large complex network with a myriad of vulnerabilities, ...
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Multitarget Position and Velocity Estimation Using OFDM Communication Signals
In this paper, we consider a passive radar system that estimates the pos...
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Decentralized Computation Offloading for MultiUser Mobile Edge Computing: A Deep Reinforcement Learning Approach
Mobile edge computing (MEC) emerges recently as a promising solution to ...
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Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications
The application of deep learning techniques resulted in remarkable impro...
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Quickest Detection of TimeVarying False Data Injection Attacks in Dynamic Linear Regression Models
Motivated by the sequential detection of false data injection attacks (F...
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Online CyberAttack Detection in Smart Grid: A Reinforcement Learning Approach
Early detection of cyberattacks is crucial for a safe and reliable oper...
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RealTime Nonparametric Anomaly Detection in HighDimensional Settings
Timely and reliable detection of abrupt anomalies, e.g., faults, intrusi...
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A Simple and Space Efficient Segment Tree Implementation
The segment tree is an extremely versatile data structure. In this paper...
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Efficient File Delivery for Coded Prefetching in Shared Cache Networks with Multiple Requests Per User
We consider a centralized caching network, where a server serves several...
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RealTime Detection of Hybrid and Stealthy CyberAttacks in Smart Grid
For a safe and reliable operation of the smart grid, timely detection of...
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Consensusbased Distributed Quickest Detection of Attacks with Unknown Parameters
Sequential attack detection in a distributed estimation system is consid...
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SuperResolution mmWave Channel Estimation using Atomic Norm Minimization
We propose superresolution MIMO channel estimators for millimeterwave ...
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An Online RideSharing Path Planning Strategy for Public Vehicle Systems
As efficient trafficmanagement platforms, public vehicle (PV) systems a...
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On Deterministic Sampling Patterns for Robust LowRank Matrix Completion
In this letter, we study the deterministic sampling patterns for the com...
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Scaled Nuclear Norm Minimization for LowRank Tensor Completion
Minimizing the nuclear norm of a matrix has been shown to be very effici...
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Rank Determination for LowRank Data Completion
Recently, fundamental conditions on the sampling patterns have been obta...
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Fourthorder Tensors with Multidimensional Discrete Transforms
The big data era is swamping areas including data analysis, machine/deep...
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Fundamental Conditions for LowCPRank Tensor Completion
We consider the problem of low canonical polyadic (CP) rank tensor compl...
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Characterization of Deterministic and Probabilistic Sampling Patterns for Finite Completability of Low TensorTrain Rank Tensor
In this paper, we analyze the fundamental conditions for lowrank tensor...
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Adaptive Sampling of RF Fingerprints for Finegrained Indoor Localization
Indoor localization is a supporting technology for a broadening range of...
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Xiaodong Wang
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Assistant professor of Department of Electrical Engineering at Columbia University since 2002, Department of Electrical Engineering at Columbia University, 1999 NSF CAREER Award, 2001 IEEE Communications Society and Information Theory Society Joint Paper