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Found 7 papers, 1 papers with code
Predicting Machine Translation Performance on Low-Resource Languages: The Role of Domain Similarity
Fine-tuning and testing a multilingual large language model is expensive and challenging for low-resource languages (LRLs).
High-dimensional Bid Learning for Energy Storage Bidding in Energy Markets
To address this challenge, we modify the common reinforcement learning(RL) process by proposing a new bid representation method called Neural Network Embedded Bids (NNEBs).
Modality-Aware Contrastive Instance Learning with Self-Distillation for Weakly-Supervised Audio-Visual Violence Detection
In this paper, we analyze the modality asynchrony and undifferentiated instances phenomena of the multiple instance learning (MIL) procedure, and further investigate its negative impact on weakly-supervised audio-visual learning.
Anomaly Detection In Surveillance Videos
audio-visual learning
+1
Self-Supervised Video Representation Learning with Motion-Contrastive Perception
Visual-only self-supervised learning has achieved significant improvement in video representation learning.
Acoustic-to-articulatory Inversion based on Speech Decomposition and Auxiliary Feature
Acoustic-to-articulatory inversion (AAI) is to obtain the movement of articulators from speech signals.
Bid Optimization using Maximum Entropy Reinforcement Learning
In this paper, we first utilize a widely accepted linear bidding function to compute every impression's base price and optimize it by a mutable adjustment factor derived from the RTB auction environment, to avoid optimizing every impression's bidding price directly.
Accurate Frequency Estimator of Sinusoid Based on Interpolation of FFT and DTFT
The correlation coef cients between the Fourier Transform of the noises on two arbitrarily spaced spectrum lines are derived, and the MSE calculation formula is derived in additive white noise background based on the correlation coef cients.
