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08/25/2023
TriGait: Aligning and Fusing Skeleton and Silhouette Gait Data via a Tri-Branch Network
Gait recognition is a promising biometric technology for identification ...
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08/14/2023
Temporal Sentence Grounding in Streaming Videos
This paper aims to tackle a novel task - Temporal Sentence Grounding in ...
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07/30/2023
Efficient Federated Learning via Local Adaptive Amended Optimizer with Linear Speedup
Adaptive optimization has achieved notable success for distributed learn...
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07/29/2023
GaitASMS: Gait Recognition by Adaptive Structured Spatial Representation and Multi-Scale Temporal Aggregation
Gait recognition is one of the most promising video-based biometric tech...
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06/09/2023
Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed Initialization
Federated learning (FL) is a distributed paradigm that coordinates massi...
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05/24/2023
Towards More Suitable Personalization in Federated Learning via Decentralized Partial Model Training
Personalized federated learning (PFL) aims to produce the greatest perso...
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05/19/2023
Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape
In federated learning (FL), a cluster of local clients are chaired under...
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04/07/2023
On Efficient Training of Large-Scale Deep Learning Models: A Literature Review
The field of deep learning has witnessed significant progress, particula...
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03/27/2023
Demystifying CXL Memory with Genuine CXL-Ready Systems and Devices
The high demand for memory capacity in modern datacenters has led to mul...
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03/15/2023
Visual Prompt Based Personalized Federated Learning
As a popular paradigm of distributed learning, personalized federated le...
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02/24/2023
Subspace based Federated Unlearning
Federated learning (FL) enables multiple clients to train a machine lear...
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02/21/2023
Fusion of Global and Local Knowledge for Personalized Federated Learning
Personalized federated learning, as a variant of federated learning, tra...
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02/21/2023
FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy
Federated learning is an emerging distributed machine learning framework...
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02/13/2023
Deep Graph-Level Orthogonal Hypersphere Compression for Anomaly Detection
Graph-level anomaly detection aims to identify anomalous graphs from a c...
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02/08/2023
Improving the Model Consistency of Decentralized Federated Learning
To mitigate the privacy leakages and communication burdens of Federated ...
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10/09/2022
Nonlinear Sufficient Dimension Reduction with a Stochastic Neural Network
Sufficient dimension reduction is a powerful tool to extract core inform...
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07/25/2022
Laplacian-based Cluster-Contractive t-SNE for High Dimensional Data Visualization
Dimensionality reduction techniques aim at representing high-dimensional...
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03/16/2022
ORCA: A Network and Architecture Co-design for Offloading us-scale Datacenter Applications
Responding to the "datacenter tax" and "killer microseconds" problems fo...
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01/14/2022
A Kernel-Expanded Stochastic Neural Network
The deep neural network suffers from many fundamental issues in machine ...
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01/09/2022
Tree-based Regression for Interval-valued Data
Regression methods for interval-valued data have been increasingly studi...
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10/01/2021
Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration
Deep learning has powered recent successes of artificial intelligence (A...
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05/27/2021
Manifold-constrained Gaussian process inference for time-varying parameters in dynamic systems
Identification of parameters in ordinary differential equations (ODEs) i...
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02/25/2021
Consistent Sparse Deep Learning: Theory and Computation
Deep learning has been the engine powering many successes of data scienc...
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07/23/2020
Deep Learning Based Equalizer for MIMO-OFDM Systems with Insufficient Cyclic Prefix
In this paper, we study the equalization design for multiple-input multi...
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03/16/2020
Resource Allocation for IRS-assisted Full-Duplex Cognitive Radio Systems
In this paper, we investigate the resource allocation design for intelli...
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02/07/2020
Extended Stochastic Gradient MCMC for Large-Scale Bayesian Variable Selection
Stochastic gradient Markov chain Monte Carlo (MCMC) algorithms have rece...
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11/21/2019
Interval-Valued Kriging Models for Geostatistical Mapping with Imprecise Inputs
Many geosciences data are imprecise due to various limitations and uncer...
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10/20/2019
Learning-based real-time method to looking through scattering medium oriented to practical application
Strong scattering media brings great difficulties to optical imaging, wh...
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10/14/2019
Resource Allocation for Multi-User Downlink MISO OFDMA-URLLC Systems
This paper considers the resource allocation algorithm design for downli...
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07/06/2019
Resource Allocation for Secure IRS-assisted Multiuser MISO Systems
In this paper, we study resource allocation design for secure communicat...
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05/26/2019
Multiuser MISO UAV Communications in Uncertain Environments with No-fly Zones: Robust Trajectory and Resource Allocation Design
In this paper, we investigate robust resource allocation algorithm desig...
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01/17/2019
Resource Allocation for Multi-User Downlink URLLC-OFDMA Systems
In this paper, we study resource allocation for downlink orthogonal freq...
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01/09/2019
An interval-valued GARCH model for range-measured return processes
Range-measured return contains more information than the traditional sca...
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09/11/2018
Robust Resource Allocation for UAV Systems with UAV Jittering and User Location Uncertainty
In this paper, we investigate resource allocation algorithm design for m...
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07/31/2018
Optimal 3D-Trajectory Design and Resource Allocation for Solar-Powered UAV Communication Systems
In this paper, we investigate the resource allocation algorithm design f...
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01/22/2018