Genre
SeeA: Efficient Exploration-Enhanced A Search by Selective Sampling
Three sampling techniques are presented for comparative investigations.
MMD-FUSE: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting
The fundamental problem of non-parametric two-sample testing consists in detecting the difference between any two distributions having access only to samples from these.
Adversarial Training from Mean Field Perspective
We also show that the network width alleviates these issues.
Quantizable Transformers: Removing Outliers by Helping Attention Heads Do Nothing
Due to their size, the capability of these networks has increased tremendously, but this has come at the cost of a significant increase in necessary compute.
Fine-Grained Dynamic Framework for Bias-Variance Joint Optimization on Data Missing Not at Random
Some existing estimators and regularizers attempt to achieve unbiased estimation to improve the predictive performance.
DIFFER: Decomposing Individual Reward for Fair Experience Replay in Multi-Agent Reinforcement Learning
The code is available in https://github.com/cathyhxh/DIFFER.
Improving Visual Prompt Tuning by Gaussian Neighborhood Minimization for Long-Tailed Visual Recognition
Long-tailed visual recognition has received increasing attention recently.
