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09/06/2023
Impression-Informed Multi-Behavior Recommender System: A Hierarchical Graph Attention Approach
While recommender systems have significantly benefited from implicit fee...
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08/31/2023
Contrastive Representation Learning Based on Multiple Node-centered Subgraphs
As the basic element of graph-structured data, node has been recognized ...
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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...
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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...
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08/12/2023
Performance Analysis for Resource Constrained Decentralized Federated Learning Over Wireless Networks
Federated learning (FL) can lead to significant communication overhead a...
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08/07/2023
Uncertainty-aware Consistency Learning for Cold-Start Item Recommendation
Graph Neural Network (GNN)-based models have become the mainstream appro...
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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...
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07/27/2023
Scaling TransNormer to 175 Billion Parameters
We present TransNormerLLM, the first linear attention-based Large Langua...
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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...
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06/28/2023
Event Detection from Social Media Stream: Methods, Datasets and Opportunities
Social media streams contain large and diverse amount of information, ra...
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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...
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06/08/2023
Matrix GARCH Model: Inference and Application
Matrix-variate time series data are largely available in applications. H...
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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...
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05/10/2023
Computation-Efficient Backscatter-Blessed MEC with User Reciprocity
This letter proposes a new user cooperative offloading protocol called u...
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05/08/2023
Toeplitz Neural Network for Sequence Modeling
Sequence modeling has important applications in natural language process...
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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...
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03/27/2023
Fine-grained Audible Video Description
We explore a new task for audio-visual-language modeling called fine-gra...
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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 ...
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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...
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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...
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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...
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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...
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01/23/2023
AttMEMO : Accelerating Transformers with Memoization on Big Memory Systems
Transformer models gain popularity because of their superior inference a...
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12/30/2022
Transformer in Transformer as Backbone for Deep Reinforcement Learning
Designing better deep networks and better reinforcement learning (RL) al...
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12/20/2022
Generation-Augmented Query Expansion For Code Retrieval
Pre-trained language models have achieved promising success in code retr...
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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...
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11/28/2022
Towards Reliable Item Sampling for Recommendation Evaluation
Since Rendle and Krichene argued that commonly used sampling-based evalu...
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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...
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10/17/2022
PTDE: Personalized Training with Distillated Execution for Multi-Agent Reinforcement Learning
Centralized Training with Decentralized Execution (CTDE) has been a very...
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10/15/2022
Linear Video Transformer with Feature Fixation
Vision Transformers have achieved impressive performance in video classi...
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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...
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09/09/2022
Multi-Document Scientific Summarization from a Knowledge Graph-Centric View
Multi-Document Scientific Summarization (MDSS) aims to produce coherent ...
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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...
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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...
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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...
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07/28/2022
Neural Architecture Search on Efficient Transformers and Beyond
Recently, numerous efficient Transformers have been proposed to reduce t...
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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...
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05/30/2022
SEREN: Knowing When to Explore and When to Exploit
Efficient reinforcement learning (RL) involves a trade-off between "expl...
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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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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...
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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...
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03/25/2022
Compare learning: bi-attention network for few-shot learning
Learning with few labeled data is a key challenge for visual recognition...
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03/24/2022
LHNN: Lattice Hypergraph Neural Network for VLSI Congestion Prediction
Precise congestion prediction from a placement solution plays a crucial ...
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01/11/2022
Representing Videos as Discriminative Sub-graphs for Action Recognition
Human actions are typically of combinatorial structures or patterns, i.e...
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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...
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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 ∈ ...
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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...
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11/24/2021
Learning State Representations via Retracing in Reinforcement Learning
We propose learning via retracing, a novel self-supervised approach for ...
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11/17/2021