4 papers
Disciplined Biconvex Programming
Hao Zhu, Joschka Boedecker
We introduce disciplined biconvex programming (DBCP), a modeling framework for specifying and solving biconvex optimization problems. Biconvex optimization problems arise in variou…
Multi-convex Programming for Discrete Latent Factor Models Prototyping
Hao Zhu, Shengchao Yan, Jasper Hoffmann +1
Discrete latent factor models (DLFMs) are widely used in various domains such as machine learning, economics, neuroscience, psychology, etc. Currently, fitting a DLFM to some datas…
Solving Inverse Problem for Multi-armed Bandits via Convex Optimization
Hao Zhu, Joschka Boedecker
We consider the inverse problem of multi-armed bandits (IMAB) that are widely used in neuroscience and psychology research for behavior modelling. We first show that the IMAB probl…
Inverse Reinforcement Learning via Convex Optimization
Hao Zhu, Yuan Zhang, Joschka Boedecker
We consider the inverse reinforcement learning (IRL) problem, where an unknown reward function of some Markov decision process is estimated based on observed expert demonstrations.…