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Found 7 papers, 1 papers with code
Market Crowds' Trading Behaviors, Agreement Prices, and the Implications of Trading Volume
It has been long that literature in financial academics focuses mainly on price and return but much less on trading volume.
Machine unlearning via GAN
Machine learning models, especially deep models, may unintentionally remember information about their training data.
Subject Enveloped Deep Sample Fuzzy Ensemble Learning Algorithm of Parkinson's Speech Data
Therefore, it is necessary to reconstruct the existing large segments within one subject into few segments even one segment within one subject, which can facilitate the extraction of relevant speech features to characterize diagnostic markers for the whole subject.
Lightweight machine unlearning in neural network
Our method only needs to make a small perturbation of the weight of the target model and make it iterate in the direction of the model trained with the remaining data subset until the contribution of the unlearning data to the model is completely eliminated.
Controlled Evaluation of Grammatical Knowledge in Mandarin Chinese Language Models
We find suggestive evidence that structural supervision helps with representing syntactic state across intervening content and improves performance in low-data settings, suggesting that the benefits of hierarchical inductive biases in acquiring dependency relationships may extend beyond English.
Tracking Fast Neural Adaptation by Globally Adaptive Point Process Estimation for Brain-Machine Interface
In order to identify the active neurons in brain control and track their tuning property changes, we propose a globally adaptive point process method (GaPP) to estimate the neural modulation state from spike trains, decompose the states into the hyper preferred direction and reconstruct the kinematics in a dual-model framework.
