b'Dong Li'

research

∙ 09/06/2023

Impression-Informed Multi-Behavior Recommender System: A Hierarchical Graph Attention Approach

While recommender systems have significantly benefited from implicit fee...

0 Dong Li, et al. ∙

research

∙ 08/31/2023

Contrastive Representation Learning Based on Multiple Node-centered Subgraphs

As the basic element of graph-structured data, node has been recognized ...

0 Dong Li, et al. ∙

research

∙ 08/30/2023

Breaking the Interference and Fading Gridlock in Backscatter Communications: State-of-the-Art, Design Challenges, and Future Directions

With the rapid advancement of the Internet of Things (IoT) and mobile co...

0 Bowen Gu, et al. ∙

research

∙ 08/27/2023

Towards Generalizable Neural Solvers for Vehicle Routing Problems via Ensemble with Transferrable Local Policy

Machine learning has been adapted to help solve NP-hard combinatorial op...

0 Chengrui Gao, et al. ∙

research

∙ 08/12/2023

Performance Analysis for Resource Constrained Decentralized Federated Learning Over Wireless Networks

Federated learning (FL) can lead to significant communication overhead a...

0 Zhigang Yan, et al. ∙

research

∙ 08/07/2023

Uncertainty-aware Consistency Learning for Cold-Start Item Recommendation

Graph Neural Network (GNN)-based models have become the mainstream appro...

0 Taichi Liu, et al. ∙

research

∙ 07/28/2023

Learning to Collaborate by Grouping: a Consensus-oriented Strategy for Multi-agent Reinforcement Learning

Multi-agent systems require effective coordination between groups and in...

0 Jingqing Ruan, et al. ∙

research

∙ 07/27/2023

Scaling TransNormer to 175 Billion Parameters

We present TransNormerLLM, the first linear attention-based Large Langua...

0 Zhen Qin, et al. ∙

research

∙ 06/30/2023

Performance Analysis for Polar Codes under Successive Cancellation List Decoding with Fixed List Size

In this paper, we first indicate that the block error event of polar cod...

0 Jinnan Piao, et al. ∙

research

∙ 06/28/2023

Event Detection from Social Media Stream: Methods, Datasets and Opportunities

Social media streams contain large and diverse amount of information, ra...

0 Quanzhi Li, et al. ∙

research

∙ 06/24/2023

Enhancing Spectrum Sensing via Reconfigurable Intelligent Surfaces: Passive or Active Sensing and How Many Reflecting Elements are Needed?

Cognitive radio has been proposed to alleviate the scarcity of available...

0 Hao Xie, et al. ∙

research

∙ 06/08/2023

Matrix GARCH Model: Inference and Application

Matrix-variate time series data are largely available in applications. H...

0 Cheng Yu, et al. ∙

research

∙ 06/01/2023

From sparse to dense functional data in high dimensions: Revisiting phase transitions from a non-asymptotic perspective

Nonparametric estimation of the mean and covariance functions is ubiquit...

0 Shaojun Guo, et al. ∙

research

∙ 05/10/2023

Computation-Efficient Backscatter-Blessed MEC with User Reciprocity

This letter proposes a new user cooperative offloading protocol called u...

0 Bowen Gu, et al. ∙

research

∙ 05/08/2023

Toeplitz Neural Network for Sequence Modeling

Sequence modeling has important applications in natural language process...

0 Zhen Qin, et al. ∙

research

∙ 04/20/2023

To Reflect or Not To Reflect: On-Off Control and Number Configuration for Reflecting Elements in RIS-Aided Wireless Systems

Reconfigurable intelligent surface (RIS) has been regarded as a promisin...

0 Hao Xie, et al. ∙

research

∙ 03/27/2023

Fine-grained Audible Video Description

We explore a new task for audio-visual-language modeling called fine-gra...

0 Xuyang Shen, et al. ∙

research

∙ 03/23/2023

Construction Methods Based Minimum Weight Distribution for Polar Codes with Successive Cancellation List Decoding

In this paper, we focus on the construction methods based MWD for polar ...

0 Jinnan Piao, et al. ∙

research

∙ 03/06/2023

DR-Label: Improving GNN Models for Catalysis Systems by Label Deconstruction and Reconstruction

Attaining the equilibrium state of a catalyst-adsorbate system is key to...

0 Bowen Wang, et al. ∙

research

∙ 02/19/2023

Rethinking Memory Profiling and Migration for Multi-Tiered Large Memory Systems

Multi-tiered large memory systems call for rethinking of memory profilin...

0 Jie Ren, et al. ∙

research

∙ 02/14/2023

Accelerated Fuzzy C-Means Clustering Based on New Affinity Filtering and Membership Scaling

Fuzzy C-Means (FCM) is a widely used clustering method. However, FCM and...

0 Dong Li, et al. ∙

research

∙ 02/14/2023

Multi-Prototypes Convex Merging Based K-Means Clustering Algorithm

K-Means algorithm is a popular clustering method. However, it has two li...

0 Dong Li, et al. ∙

research

∙ 01/23/2023

AttMEMO : Accelerating Transformers with Memoization on Big Memory Systems

Transformer models gain popularity because of their superior inference a...

0 Yuan Feng, et al. ∙

research

∙ 12/30/2022

Transformer in Transformer as Backbone for Deep Reinforcement Learning

Designing better deep networks and better reinforcement learning (RL) al...

0 Hangyu Mao, et al. ∙

research

∙ 12/20/2022

Generation-Augmented Query Expansion For Code Retrieval

Pre-trained language models have achieved promising success in code retr...

0 Dong Li, et al. ∙

research

∙ 12/16/2022

Exploring Hybrid Active-Passive RIS-Aided MEC Systems: From the Mode-Switching Perspective

Mobile edge computing (MEC) has been regarded as a promising technique t...

0 Hao Xie, et al. ∙

research

∙ 11/28/2022

Towards Reliable Item Sampling for Recommendation Evaluation

Since Rendle and Krichene argued that commonly used sampling-based evalu...

0 Dong Li, et al. ∙

research

∙ 11/23/2022

Prototypical context-aware dynamics generalization for high-dimensional model-based reinforcement learning

The latent world model provides a promising way to learn policies in a c...

0 Junjie Wang, et al. ∙

research

∙ 10/17/2022

PTDE: Personalized Training with Distillated Execution for Multi-Agent Reinforcement Learning

Centralized Training with Decentralized Execution (CTDE) has been a very...

0 Yiqun Chen, et al. ∙

research

∙ 10/15/2022

Linear Video Transformer with Feature Fixation

Vision Transformers have achieved impressive performance in video classi...

0 Kaiyue Lu, et al. ∙

research

∙ 09/27/2022

Gain without Pain: Recycling Reflected Energy from Wireless Powered RIS-aided Communications

In this paper, we investigate and analyze energy recycling for a reconfi...

0 Hao Xie, et al. ∙

research

∙ 09/09/2022

Multi-Document Scientific Summarization from a Knowledge Graph-Centric View

Multi-Document Scientific Summarization (MDSS) aims to produce coherent ...

0 Pancheng Wang, et al. ∙

research

∙ 08/27/2022

SA: Sliding attack for synthetic speech detection with resistance to clipping and self-splicing

Deep neural networks are vulnerable to adversarial examples that mislead...

0 Deng JiaCheng, et al. ∙

research

∙ 08/16/2022

Three New Arnoldi-Type Methods for the Quadratic Eigenvalue Problem in Rotor Dynamics

Three new Arnoldi-type methods are presented to accelerate the modal ana...

0 Dong Li, et al. ∙

research

∙ 08/03/2022

Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation

Multi-types of behaviors (e.g., clicking, adding to cart, purchasing, et...

0 Chang Meng, et al. ∙

research

∙ 07/28/2022

Neural Architecture Search on Efficient Transformers and Beyond

Recently, numerous efficient Transformers have been proposed to reduce t...

28 Zexiang Liu, et al. ∙

research

∙ 07/21/2022

Auto Machine Learning for Medical Image Analysis by Unifying the Search on Data Augmentation and Neural Architecture

Automated data augmentation, which aims at engineering augmentation poli...

19 Jianwei Zhang, et al. ∙

research

∙ 05/30/2022

SEREN: Knowing When to Explore and When to Exploit

Efficient reinforcement learning (RL) involves a trade-off between "expl...

1 Changmin Yu, et al. ∙

research

∙ 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...

0 Haowei Zhu, et al. ∙

research

∙ 05/04/2022

Dynamic Sparse R-CNN

Sparse R-CNN is a recent strong object detection baseline by set predict...

0 Qinghang Hong, et al. ∙

research

∙ 05/03/2022

Revisiting Communication-Efficient Federated Learning with Balanced Global and Local Updates

In federated learning (FL), a number of devices train their local models...

0 Zhigang Yan, et al. ∙

research

∙ 04/20/2022

Nearly optimal bounds for the global geometric landscape of phase retrieval

The phase retrieval problem is concerned with recovering an unknown sign...

0 Jian-Feng Cai, et al. ∙

research

∙ 03/25/2022

Compare learning: bi-attention network for few-shot learning

Learning with few labeled data is a key challenge for visual recognition...

0 Li Ke, et al. ∙

research

∙ 03/24/2022

LHNN: Lattice Hypergraph Neural Network for VLSI Congestion Prediction

Precise congestion prediction from a placement solution plays a crucial ...

0 Bowen Wang, et al. ∙

research

∙ 01/11/2022

Representing Videos as Discriminative Sub-graphs for Action Recognition

Human actions are typically of combinatorial structures or patterns, i.e...

7 Dong Li, et al. ∙

research

∙ 12/15/2021

The global landscape of phase retrieval II: quotient intensity models

A fundamental problem in phase retrieval is to reconstruct an unknown si...

0 Jian-Feng Cai, et al. ∙

research

∙ 12/15/2021

The global landscape of phase retrieval I: perturbed amplitude models

A fundamental task in phase retrieval is to recover an unknown signal ∈ ...

0 Jian-Feng Cai, et al. ∙

research

∙ 11/24/2021

A global quadratic speed-up for computing the principal eigenvalue of Perron-like operators

We consider a new algorithm in light of the min-max Collatz-Wielandt for...

0 Dong Li, et al. ∙

research

∙ 11/24/2021

Learning State Representations via Retracing in Reinforcement Learning

We propose learning via retracing, a novel self-supervised approach for ...

4 Changmin Yu, et al. ∙

research

∙ 11/17/2021

SEIHAI: A Sample-efficient Hierarchical AI for the MineRL Competition

The MineRL competition is designed for the development of reinforcement ...

12 Hangyu Mao, et al. ∙

Dong Li

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