In this work, we point out that the major dilemma of image aesthetics assessment (IAA) comes from abstract nature aesthetic labels. That is, a vast variety distinct contents can correspond to same label. On one hand, during inference, IAA model is required relate various other when training, it would be hard for learn distinguish different merely with supervision labels, since labels are not di...

Within the machine learning field, main purpose of lifelong learning, also known as continuous is to enable neural networks learn continuously, humans do. Lifelong accumulates knowledge learned from previous tasks and transfers it support network in future tasks. This technique not only avoids catastrophic forgetting problem with when training new tasks, but makes model more robust temporal evo...

Reducing complex human experiences into a psychiatric diagnosis can be a daunting task. For children with developmental disorders, this process is even more complicated and requires distilling often incomplete and frequently contradictory scientific evidence. Table 1 lists several examples of the problems of developmental psychopathology. Although far from comprehensive, this list does raise 2 ...

Certain fundamental principles are common to all distilling systems. Modern distillation systems are multi-stage, continuous, countercurrent, vapor-liquid contacting systems that operate within the physical laws that state that different materials boil at different temperatures. Represented in Figure 1 is a typical distillation tower that could be employed to separate an ideal mixture. Such a s...

A very simple way to improve the performance of almost any machine learning algorithm is to train many different models on the same data and then to average their predictions [3]. Unfortunately, making predictions using a whole ensemble of models is cumbersome and may be too computationally expensive to allow deployment to a large number of users, especially if the individual models are large n...