Ping Luo

On Batch Adaptive Training for Deep Learning: Lower Loss and Larger Step Size

2018

Mini-batch gradient descent and its variants are commonly used in deep learning. The principle of mini-batch gradient descent is to use noisy gradient calculated on a batch to estimate the real gradient, thus balancing the …

AdaptDiffuser: Diffusion Models as Adaptive Self-evolving Planners

2023 · arXiv (Cornell University)

Diffusion models have demonstrated their powerful generative capability in many tasks, with great potential to serve as a paradigm for offline reinforcement learning. However, the quality of the diffusion model is limited by the insufficient …

Semantic Path based Personalized Recommendation on Weighted Heterogeneous Information Networks

2015

Recently heterogeneous information network (HIN) analysis has attracted a lot of attention, and many data mining tasks have been exploited on HIN. As an important data mining task, recommender system includes a lot of object …

Mechanism-Aware Neural Machine for Dialogue Response Generation

2017 · Proceedings of the AAAI Conference on Artificial Intelligence

To the same utterance, people's responses in everyday dialogue may be diverse largely in terms of content semantics, speaking styles, communication intentions and so on. Previous generative conversational models ignore these 1-to-n relationships between a …