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Found 6 papers, 1 papers with code
Reinforcement Learning Approach for Integrating Compressed Contexts into Knowledge Graphs
The widespread use of knowledge graphs in various fields has brought about a challenge in effectively integrating and updating information within them.
Gradient-based Parameter Selection for Efficient Fine-Tuning
With the growing size of pre-trained models, full fine-tuning and storing all the parameters for various downstream tasks is costly and infeasible.
Data Augmentation for Time-Series Classification: An Extensive Empirical Study and Comprehensive Survey
Data Augmentation (DA) has emerged as an indispensable strategy in Time Series Classification (TSC), primarily due to its capacity to amplify training samples, thereby bolstering model robustness, diversifying datasets, and curtailing overfitting.
Long-tail Cross Modal Hashing
LtCMH firstly adopts auto-encoders to mine the individuality and commonality of different modalities by minimizing the dependency between the individuality of respective modalities and by enhancing the commonality of these modalities.
Motion-based Camera Localization System in Colonoscopy Videos
In this study, we propose a camera localization system to estimate the relative location of the camera and classify the colon into anatomical segments.
Batched Multi-armed Bandits Problem
While the minimax regret for the two-armed stochastic bandits has been completely characterized in \cite{perchet2016batched}, the effect of the number of arms on the regret for the multi-armed case is still open.
