3 citations · 6 across the 5 of their papers we have counts for
5 papers
Adjustable Robust Reinforcement Learning for Online 3D Bin Packing
Yuxin Pan, Yize Chen, Fangzhen Lin
Designing effective policies for the online 3D bin packing problem (3D-BPP) has been a long-standing challenge, primarily due to the unpredictable nature of incoming box sequences…
Using Language Models For Knowledge Acquisition in Natural Language Reasoning Problems
Fangzhen Lin, Ziyi Shou, Chengcai Chen
For a natural language problem that requires some non-trivial reasoning to solve, there are at least two ways to do it using a large language model (LLM). One is to ask it to solve…
Backward Imitation and Forward Reinforcement Learning via Bi-directional Model Rollouts
Yuxin Pan, Fangzhen Lin
Traditional model-based reinforcement learning (RL) methods generate forward rollout traces using the learnt dynamics model to reduce interactions with the real environment. The re…
PocketNN: Integer-only Training and Inference of Neural Networks via Direct Feedback Alignment and Pocket Activations in Pure C++
Jaewoo Song, Fangzhen Lin
Standard deep learning algorithms are implemented using floating-point real numbers. This presents an obstacle for implementing them on low-end devices which may not have dedicated…
Computing Class Hierarchies from Classifiers
Kai Kang, Fangzhen Lin
A class or taxonomic hierarchy is often manually constructed, and part of our knowledge about the world. In this paper, we propose a novel algorithm for automatically acquiring a c…