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Approximating Single-Source Personalized PageRank with Absolute Error Guarantees
Free accessDataCite | 2024| -
Synthesizing Long-Term Human Motions with Diffusion Models via Coherent Sampling
Free accessArXiv | 2023| -
Approximating Single-Source Personalized PageRank with Absolute Error Guarantees
Free accessArXiv | 2024| -
Counterfactual Cross-modality Reasoning for Weakly Supervised Video Moment Localization
Free accessArXiv | 2023| -
Learning Distributed Representations for Recommender Systems with a Network Embedding Approach
Springer Verlag | 2016| -
Editorial for Special Issue on Large-scale Pre-training: Data, Models, and Fine-tuning
Springer Verlag | 2023| -
CTDA: Contrastive Temporal Domain Adaptation for Action Segmentation
British Library Conference Proceedings | 2023| -
Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited
Free accessArXiv | 2022| -
Document-Level Named Entity Recognition by Incorporating Global and Neighbor Features
Springer Verlag | 2019| -
Document-Level Named Entity Recognition by Incorporating Global and Neighbor Features
British Library Conference Proceedings | 2019| -
Image classification by visual bag-of-words refinement and reduction
British Library Online Contents | 2016| -
Within-Network Classification Using Radius-Constrained Neighborhood Patterns
British Library Conference Proceedings | 2014| -
Direct Semantic Analysis for Social Image Classification
British Library Conference Proceedings | 2014| -
ReBoost: a retrieval-boosted sequence-to-sequence model for neural response generation
Springer Verlag | 2020| -
ReBoost: a retrieval-boosted sequence-to-sequence model for neural response generation
Online Contents | 2019| -
Investigating the Robustness of Counterfactual Learning to Rank Models: A Reproducibility Study
Free accessArXiv | 2024| -
Supervised Contrastive Learning for Few-Shot Action Classification
British Library Conference Proceedings | 2023| -
ReBoost: a retrieval-boosted sequence-to-sequence model for neural response generation
Online Contents | 2019| -
Learning Distributed Representations for Recommender Systems with a Network Embedding Approach
British Library Conference Proceedings | 2016|
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