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08/21/2023
Pixel Adaptive Deep Unfolding Transformer for Hyperspectral Image Reconstruction
Hyperspectral Image (HSI) reconstruction has made gratifying progress wi...
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08/04/2023
Adaptive Preferential Attached kNN Graph with Distribution-Awareness
Graph-based kNN algorithms have garnered widespread popularity for machi...
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07/04/2023
Separated RoadTopoFormer
Understanding driving scenarios is crucial to realizing autonomous drivi...
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06/29/2023
Entanglement Routing over Quantum Networks Using Greenberger-Horne-Zeilinger Measurements
Generating a long-distance quantum entanglement is one of the most essen...
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06/15/2023
Multi-Temporal Relationship Inference in Urban Areas
Finding multiple temporal relationships among locations can benefit a bu...
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04/12/2023
AutoShot: A Short Video Dataset and State-of-the-Art Shot Boundary Detection
The short-form videos have explosive popularity and have dominated the n...
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04/03/2023
Spectral Enhanced Rectangle Transformer for Hyperspectral Image Denoising
Denoising is a crucial step for hyperspectral image (HSI) applications. ...
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04/02/2023
LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World Denoising
Despite the significant results on synthetic noise under simplified assu...
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03/08/2023
Distributed and Deep Vertical Federated Learning with Big Data
In recent years, data are typically distributed in multiple organization...
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11/24/2022
Multi-Job Intelligent Scheduling with Cross-Device Federated Learning
Recent years have witnessed a large amount of decentralized data in vari...
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11/05/2022
Modeling Multi-Dimensional Datasets via a Fast Scale-Free Network Model
Compared with network datasets, multi-dimensional data are much more com...
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08/05/2022
A Hybrid Observer for Estimating the State of a Distributed Linear System
A hybrid observer is described for estimating the state of a system of t...
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07/25/2022
Cooperative Actor-Critic via TD Error Aggregation
In decentralized cooperative multi-agent reinforcement learning, agents ...
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07/14/2022
Accelerated Federated Learning with Decoupled Adaptive Optimization
The federated learning (FL) framework enables edge clients to collaborat...
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07/14/2022
Large-scale Knowledge Distillation with Elastic Heterogeneous Computing Resources
Although more layers and more parameters generally improve the accuracy ...
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06/21/2022
FedHiSyn: A Hierarchical Synchronous Federated Learning Framework for Resource and Data Heterogeneity
Federated Learning (FL) enables training a global model without sharing ...
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06/12/2022
Stochastic Gradient Descent without Full Data Shuffle
Stochastic gradient descent (SGD) is the cornerstone of modern machine l...
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06/05/2022
E^2VTS: Energy-Efficient Video Text Spotting from Unmanned Aerial Vehicles
Unmanned Aerial Vehicles (UAVs) based video text spotting has been exten...
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05/31/2022
Multi-Entanglement Routing Design over Quantum Networks
Quantum networks are considered as a promising future platform for quant...
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05/21/2022
Not All SWAPs Have the Same Cost: A Case for Optimization-Aware Qubit Routing
Despite rapid advances in quantum computing technologies, the qubit conn...
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05/04/2022
Dual Cross-Attention Learning for Fine-Grained Visual Categorization and Object Re-Identification
Recently, self-attention mechanisms have shown impressive performance in...
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05/04/2022
Dynamic Sparse R-CNN
Sparse R-CNN is a recent strong object detection baseline by set predict...
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04/25/2022
FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server
Despite achieving remarkable performance, Federated Learning (FL) suffer...
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01/21/2022
Occupancy Information Ratio: Infinite-Horizon, Information-Directed, Parameterized Policy Search
We develop a new measure of the exploration/exploitation trade-off in in...
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12/24/2021
Dual Hierarchical Attention Networks for Bi-typed Heterogeneous Graph Learning
Bi-typed heterogeneous graphs are applied in many real-world scenarios. ...
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12/15/2021
Data Placement for Multi-Tenant Data Federation on the Cloud
Due to privacy concerns of users and law enforcement in data security an...
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12/11/2021
Efficient Device Scheduling with Multi-Job Federated Learning
Recent years have witnessed a large amount of decentralized data in mult...
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11/24/2021
Finite-Time Error Bounds for Distributed Linear Stochastic Approximation
This paper considers a novel multi-agent linear stochastic approximation...
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11/22/2021
Decentralized Multi-Armed Bandit Can Outperform Classic Upper Confidence Bound
This paper studies a decentralized multi-armed bandit problem in a multi...
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11/20/2021
HeterPS: Distributed Deep Learning With Reinforcement Learning Based Scheduling in Heterogeneous Environments
Deep neural networks (DNNs) exploit many layers and a large number of pa...
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11/12/2021
Resilient Consensus-based Multi-agent Reinforcement Learning
Adversarial attacks during training can strongly influence the performan...
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10/29/2021
Deep Keyphrase Completion
Keyphrase provides accurate information of document content that is high...
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10/15/2021
Joint Channel and Weight Pruning for Model Acceleration on Moblie Devices
For practical deep neural network design on mobile devices, it is essent...
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10/07/2021
AgFlow: Fast Model Selection of Penalized PCA via Implicit Regularization Effects of Gradient Flow
Principal component analysis (PCA) has been widely used as an effective ...
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08/09/2021
ChemiRise: a data-driven retrosynthesis engine
We have developed an end-to-end, retrosynthesis system, named ChemiRise,...
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08/04/2021
ErrorCompensatedX: error compensation for variance reduced algorithms
Communication cost is one major bottleneck for the scalability for distr...
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07/12/2021
MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal
Real estate appraisal refers to the process of developing an unbiased op...
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06/11/2021
DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning
Games are abstractions of the real world, where artificial agents learn ...
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04/29/2021
From Distributed Machine Learning to Federated Learning: A Survey
In recent years, data and computing resources are typically distributed ...
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04/12/2021
Distributed Learning Systems with First-order Methods
Scalable and efficient distributed learning is one of the main driving f...
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03/30/2021
Reputation and Pricing Dynamics in Online Markets
We study the economic interactions among sellers and buyers in online ma...
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03/19/2021
Interpretable Deep Learning: Interpretations, Interpretability, Trustworthiness, and Beyond
Deep neural networks have been well-known for their superb performance i...
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02/04/2021
1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed
Scalable training of large models (like BERT and GPT-3) requires careful...
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01/20/2021
Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments
Exploration under sparse reward is a long-standing challenge of model-fr...
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12/22/2020
C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods Ahead of COVID-19 Outbreak
The novel coronavirus disease (COVID-19) has crushed daily routines and ...
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12/14/2020
Relaxed Peephole Optimization: A Novel Compiler Optimization for Quantum Circuits
In this paper, we propose a novel quantum compiler optimization, named r...
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10/24/2020
Federated Bandit: A Gossiping Approach
In this paper, we study Federated Bandit, a decentralized Multi-Armed Ba...
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10/23/2020
Short Video-based Advertisements Evaluation System: Self-Organizing Learning Approach
With the rising of short video apps, such as TikTok, Snapchat and Kwai, ...
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10/22/2020
Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free
Adversarial training and its many variants substantially improve deep ne...
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09/28/2020
