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09/03/2023
VGDiffZero: Text-to-image Diffusion Models Can Be Zero-shot Visual Grounders
Large-scale text-to-image diffusion models have shown impressive capabil...
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08/13/2023
Learning on Graphs with Out-of-Distribution Nodes
Graph Neural Networks (GNNs) are state-of-the-art models for performing ...
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07/26/2023
Investigating the Impact of Variables on Handover Performance in 5G Ultra-Dense Networks
The advent of 5G New Radio (NR) technology has revolutionized the landsc...
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07/19/2023
STRAPPER: Preference-based Reinforcement Learning via Self-training Augmentation and Peer Regularization
Preference-based reinforcement learning (PbRL) promises to learn a compl...
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06/26/2023
CEIL: Generalized Contextual Imitation Learning
In this paper, we present ContExtual Imitation Learning (CEIL), a genera...
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06/23/2023
CLUE: Calibrated Latent Guidance for Offline Reinforcement Learning
Offline reinforcement learning (RL) aims to learn an optimal policy from...
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05/25/2023
Beyond Reward: Offline Preference-guided Policy Optimization
This study focuses on the topic of offline preference-based reinforcemen...
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05/23/2023
Offline Experience Replay for Continual Offline Reinforcement Learning
The capability of continuously learning new skills via a sequence of pre...
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04/15/2023
BVIP Guiding System with Adaptability to Individual Differences
Guiding robots can not only detect close-range obstacles like other guid...
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03/27/2023
Troika: Multi-Path Cross-Modal Traction for Compositional Zero-Shot Learning
Recent compositional zero-shot learning (CZSL) methods adapt pre-trained...
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03/17/2023
Effect of Variable Physical Numerologies on Link-Level Performance of 5G NR V2X
With technology and societal development, the 5th generation wireless co...
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03/12/2023
RotoGBML: Towards Out-of-Distribution Generalization for Gradient-Based Meta-Learning
Gradient-based meta-learning (GBML) algorithms are able to fast adapt to...
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02/23/2023
Mitigating Unnecessary Handovers in Ultra-Dense Networks through Machine Learning-based Mobility Prediction
In 5G wireless communication, Intelligent Transportation Systems (ITS) a...
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02/22/2023
Behavior Proximal Policy Optimization
Offline reinforcement learning (RL) is a challenging setting where exist...
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01/19/2023
The Effect of Variable Factors on the Handover Performance for Ultra Dense Network
With wireless communication technology development, the 5G New Radio (NR...
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01/11/2023
Graph based Environment Representation for Vision-and-Language Navigation in Continuous Environments
Vision-and-Language Navigation in Continuous Environments (VLN-CE) is a ...
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11/23/2022
VoP: Text-Video Co-operative Prompt Tuning for Cross-Modal Retrieval
Many recent studies leverage the pre-trained CLIP for text-video cross-m...
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08/22/2022
Reference-Limited Compositional Zero-Shot Learning
Compositional zero-shot learning (CZSL) refers to recognizing unseen com...
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07/14/2022
Tree Structure-Aware Few-Shot Image Classification via Hierarchical Aggregation
In this paper, we mainly focus on the problem of how to learn additional...
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03/13/2022
DARA: Dynamics-Aware Reward Augmentation in Offline Reinforcement Learning
Offline reinforcement learning algorithms promise to be applicable in se...
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03/02/2022
Imitation and Adaptation Based on Consistency: A Quadruped Robot Imitates Animals from Videos Using Deep Reinforcement Learning
The essence of quadrupeds' movements is the movement of the center of gr...
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03/02/2022
A Transferable Legged Mobile Manipulation Framework Based on Disturbance Predictive Control
Due to their ability to adapt to different terrains, quadruped robots ha...
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01/05/2022
Few-shot Domain Adaptation for IMU Denoising
Different application scenarios will cause IMU to exhibit different erro...
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11/13/2021
Learning to Evolve on Dynamic Graphs
Representation learning in dynamic graphs is a challenging problem becau...
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11/12/2021
Mobility prediction Based on Machine Learning Algorithms
Nowadays mobile communication is growing fast in the 5G communication in...
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10/25/2021
Unsupervised Domain Adaptation with Dynamics-Aware Rewards in Reinforcement Learning
Unsupervised reinforcement learning aims to acquire skills without prior...
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10/21/2021
Off-Dynamics Inverse Reinforcement Learning from Hetero-Domain
We propose an approach for inverse reinforcement learning from hetero-do...
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10/15/2021
Performance, Successes and Limitations of Deep Learning Semantic Segmentation of Multiple Defects in Transmission Electron Micrographs
In this work, we perform semantic segmentation of multiple defect types ...
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04/27/2021
Adaptive Adversarial Training for Meta Reinforcement Learning
Meta Reinforcement Learning (MRL) enables an agent to learn from a limit...
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04/16/2021
Pareto Self-Supervised Training for Few-Shot Learning
While few-shot learning (FSL) aims for rapid generalization to new conce...
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04/11/2021
Learn Goal-Conditioned Policy with Intrinsic Motivation for Deep Reinforcement Learning
It is of significance for an agent to learn a widely applicable and gene...
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12/10/2020
DA-HGT: Domain Adaptive Heterogeneous Graph Transformer
Domain adaptation using graph networks is to learn label-discriminative ...
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12/10/2020
Visual Perception Generalization for Vision-and-Language Navigation via Meta-Learning
Vision-and-language navigation (VLN) is a challenging task that requires...
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09/10/2020
Attributes-Guided and Pure-Visual Attention Alignment for Few-Shot Recognition
The purpose of few-shot recognition is to recognize novel categories wit...
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07/17/2020
Effect of Retransmissions on the Performance of C-V2X Communication for 5G
In recent years, the next generation of wireless communication (5G) play...
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04/10/2019
System-Level Simulator of LTE Sidelink C-V2X Communication for 5G
In recent years, Cellular-Vehicle-to-Everything (CV2X) has been an emerg...
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04/10/2019
