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08/13/2023
CDR: Conservative Doubly Robust Learning for Debiased Recommendation
In recommendation systems (RS), user behavior data is observational rath...
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08/10/2023
Homophily-enhanced Structure Learning for Graph Clustering
Graph clustering is a fundamental task in graph analysis, and recent adv...
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08/09/2023
Multi-View Fusion and Distillation for Subgrade Distresses Detection based on 3D-GPR
The application of 3D ground-penetrating radar (3D-GPR) for subgrade dis...
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07/18/2023
QMNet: Importance-Aware Message Exchange for Decentralized Multi-Agent Reinforcement Learning
To improve the performance of multi-agent reinforcement learning under t...
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06/19/2023
Data-Heterogeneous Hierarchical Federated Learning with Mobility
Federated learning enables distributed training of machine learning (ML)...
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06/17/2023
OpenGSL: A Comprehensive Benchmark for Graph Structure Learning
Graph Neural Networks (GNNs) have emerged as the de facto standard for r...
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05/11/2023
Adaptive Privacy-Preserving Coded Computing With Hierarchical Task Partitioning
Distributed computing is known as an emerging and efficient technique to...
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03/08/2023
Enhanced Sliding Window Superposition Coding for Industrial Automation
The introduction of 5G has changed the wireless communication industry. ...
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02/25/2023
MASS: Mobility-Aware Sensor Scheduling of Cooperative Perception for Connected Automated Driving
Timely and reliable environment perception is fundamental to safe and ef...
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02/20/2023
Why is the prediction wrong? Towards underfitting case explanation via meta-classification
In this paper we present a heuristic method to provide individual explan...
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02/09/2023
Adap-Ï„: Adaptively Modulating Embedding Magnitude for Recommendation
Recent years have witnessed the great successes of embedding-based metho...
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01/30/2023
SMDP-Based Dynamic Batching for Efficient Inference on GPU-Based Platforms
In up-to-date machine learning (ML) applications on cloud or edge comput...
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12/28/2022
Robust Sequence Networked Submodular Maximization
In this paper, we study the Robust optimization for sequence Networked s...
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12/07/2022
MOB-FL: Mobility-Aware Federated Learning for Intelligent Connected Vehicles
Federated learning (FL) is a promising approach to enable the future Int...
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11/27/2022
Unbiased Knowledge Distillation for Recommendation
As a promising solution for model compression, knowledge distillation (K...
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11/08/2022
Hilbert Distillation for Cross-Dimensionality Networks
3D convolutional neural networks have revealed superior performance in p...
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10/27/2022
MEET: Mobility-Enhanced Edge inTelligence for Smart and Green 6G Networks
Edge intelligence is an emerging paradigm for real-time training and inf...
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08/29/2022
How to Teach: Learning Data-Free Knowledge Distillation from Curriculum
Data-free knowledge distillation (DFKD) aims at training lightweight stu...
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07/15/2022
DOLPHINS: Dataset for Collaborative Perception enabled Harmonious and Interconnected Self-driving
Vehicle-to-Everything (V2X) network has enabled collaborative perception...
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06/15/2022
A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions
Clustering is a fundamental machine learning task which has been widely ...
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06/03/2022
Multi-user Co-inference with Batch Processing Capable Edge Server
Graphics processing units (GPUs) can improve deep neural network inferen...
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02/17/2022
Time-Correlated Sparsification for Efficient Over-the-Air Model Aggregation in Wireless Federated Learning
Federated edge learning (FEEL) is a promising distributed machine learni...
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02/12/2022
Online V2X Scheduling for Raw-Level Cooperative Perception
Cooperative perception of connected vehicles comes to the rescue when th...
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12/28/2021
Online Adversarial Distillation for Graph Neural Networks
Knowledge distillation has recently become a popular technique to improv...
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09/23/2021
Coded Computation across Shared Heterogeneous Workers with Communication Delay
Distributed computing enables large-scale computation tasks to be proces...
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09/16/2021
Popularity Bias Is Not Always Evil: Disentangling Benign and Harmful Bias for Recommendation
Recommender system usually suffers from severe popularity bias – the col...
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08/23/2021
Efficient Medical Image Segmentation Based on Knowledge Distillation
Recent advances have been made in applying convolutional neural networks...
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08/12/2021
Distilling Holistic Knowledge with Graph Neural Networks
Knowledge Distillation (KD) aims at transferring knowledge from a larger...
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07/14/2021
Semi-Supervised Hypothesis Transfer for Source-Free Domain Adaptation
Domain Adaptation has been widely used to deal with the distribution shi...
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07/14/2021
Uncertainty-Guided Mixup for Semi-Supervised Domain Adaptation without Source Data
Present domain adaptation methods usually perform explicit representatio...
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05/31/2021
Dynamic Scheduling for Over-the-Air Federated Edge Learning with Energy Constraints
Machine learning and wireless communication technologies are jointly fac...
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11/16/2020
CoSam: An Efficient Collaborative Adaptive Sampler for Recommendation
Sampling strategies have been widely applied in many recommendation syst...
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11/16/2020
SamWalker++: recommendation with informative sampling strategy
Recommendation from implicit feedback is a highly challenging task due t...
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09/23/2020
Edge Learning with Timeliness Constraints: Challenges and Solutions
Future machine learning (ML) powered applications, such as autonomous dr...
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08/03/2020
Cluster-Based Cooperative Digital Over-the-Air Aggregation for Wireless Federated Edge Learning
In this paper, we study a federated learning system at the wireless edge...
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07/14/2020
Joint Device Scheduling and Resource Allocation for Latency Constrained Wireless Federated Learning
In federated learning (FL), devices contribute to the global training by...
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05/25/2020
Dynamic Compression Ratio Selection for Edge Inference Systems with Hard Deadlines
Implementing machine learning algorithms on Internet of things (IoT) dev...
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03/04/2020
Fast Adaptively Weighted Matrix Factorization for Recommendation with Implicit Feedback
Recommendation from implicit feedback is a highly challenging task due t...
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02/20/2020
Distributed Task Replication for Vehicular Edge Computing: Performance Analysis and Learning-based Algorithm
In a vehicular edge computing (VEC) system, vehicles can share their sur...
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02/19/2020
Urgency of Information for Context-Aware Timely Status Updates in Remote Control Systems
As 5G and Internet-of-Things (IoT) are deeply integrated into vertical i...
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02/14/2020
AoI-Delay Tradeoff in Mobile Edge Caching with Freshness-Aware Content Refreshing
Mobile edge caching can effectively reduce service delay but may introdu...
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01/30/2020
How Does BN Increase Collapsed Neural Network Filters?
Improving sparsity of deep neural networks (DNNs) is essential for netwo...
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01/28/2020
Beyond Age: Urgency of Information for Timeliness Guarantee in Status Update Systems
Timely status updating is crucial for future applications that involve r...
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12/25/2019
Channel Fingerprint Based Beam Tracking for Millimeter Wave Communications
Beamforming structures with fixed beam codebooks provide economical solu...
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12/25/2019
On the Coverage and Capacity of Ultra-Dense Networks with Directional Transmissions
We investigate the performance of a downlink ultra-dense network (UDN) w...
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12/03/2019
AI-Assisted Low Information Latency Wireless Networking
The 5G Phase-2 and beyond wireless systems will focus more on vertical a...
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11/15/2019
Flexible Functional Split and Power Control for Energy Harvesting Cloud Radio Access Networks
Functional split is a promising technique to flexibly balance the proces...
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11/03/2019
Device Scheduling with Fast Convergence for Wireless Federated Learning
Owing to the increasing need for massive data analysis and model trainin...
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11/01/2019
Energy-Aware Analog Aggregation for Federated Learning with Redundant Data
Federated learning (FL) enables workers to learn a model collaboratively...
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10/29/2019
