Flow boiling in mini/micro-channel heatsinks is often utilized to meet the high heat
dissipation requirements of thermal management systems. However, accurate prediction of …

Behavioral cloning reduces policy learning to supervised learning by training a
discriminative model to predict expert actions given observations. Such discriminative …

Variational approaches based on neural networks are showing promise for estimating
mutual information (MI) between high dimensional variables. However, they can be difficult …

Mutual information is a general statistical dependency measure which has found
applications in representation learning, causality, domain generalization and computational …

Internet search affects people's cognition of the world, so mitigating biases in search results
and learning fair models is imperative for social good. We study a unique gender bias in …

Proactive failure detection of instances is vitally essential to microservice systems because
an instance failure can propagate to the whole system and degrade the system's …

Mutual information has been successfully adopted in filter feature-selection methods to
assess both the relevancy of a subset of features in predicting the target variable and the …

Automatic Modulation Classification (AMC) is crucial for monitoring the legitimacy of user
frequency behavior and identifying potential sources of interference in spectrum monitoring …

Conditional generative models enjoy significant progress over the past few years. One of the
popular conditional models is Auxiliary Classifier GAN (AC-GAN) that generates highly …

Multimodal learning aims to learn from data of different modalities by fusing information from
heterogeneous sources. Although it is beneficial to learn from more modalities, it is often …