Moreover, the standard CMAB usually assumes the workers always stay in the system, whereas the workers may join in or depart from the system over time, such that what we have learnt for an individual worker cannot be applied after the worker leaves.
Three different structures based on attention-guided feature gathering (AFG) are designed for deep feature fusion.
Therefore, directly learning a mapping function from speech to the entire head image is prone to ambiguity, particularly when using a short video for training.
This poses a challenge when dealing with an unseen misspelled character, as the decoder may generate an IDS sequence that matches a seen character instead.
Moreover, we proposed an encoder-decoder-based hierarchical document structure parsing system (DSPS) to tackle this problem.
Table structure recognition is an indispensable element for enabling machines to comprehend tables.
Next, to parse the hierarchical relationship between the heading entities, a tree-structured decoder is designed.
In this paper, we propose FedTune, an automatic FL hyper-parameter tuning algorithm tailored to applications' diverse system requirements in FL training.
It has already been observed that audio-visual embedding is more robust than uni-modality embedding for person verification.
By designing a series of signal processing algorithms bespoke for dynamic vision sensing on mobile devices, EV-Tach is able to extract the rotational speed accurately from the event stream produced by dynamic vision sensing on rotary targets.
For the generalization against diverse noises, we inject class-specific identifiable patterns into a confined local patch prior, so that defensive patches could preserve more recognizable features towards specific classes, leading models for better recognition under noises.
To boost the performance of PMT, we propose multi-modeling unit training (MMUT) architecture fusion with PMT (PM-MMUT).
In this paper, we make the first attempt on quantifying the privacy leakage of recommender systems through the lens of membership inference.
Based on dual synchronous idea, a dual synchronous generator (DSG) control is applied in VSC to form inertial current source.
Collaborative learning allows multiple clients to train a joint model without sharing their data with each other.