11 papers
Generation of Custom Solvers in Rust for Convex Optimization
Hao Zhu, Joschka Boedecker
We introduce cvxgenrust, an open-source tool for generating custom Rust code that solves families of parameterized convex optimization problems modeled in CVXPY. cvxgenrust canonic…
Disciplined Bilevel Programming
Hao Zhu, Joschka Boedecker
Bilevel optimization provides a natural modeling language for hierarchical decision problems. However, applying existing numerical solvers usually requires substantial manual analy…
Probabilistic Recurrent Intention Switching Model
Wenyuan Sheng, Hao Zhu, Joschka Boedecker
Inverse reinforcement learning (IRL) recovers reward functions from observed behavior, yet traditional methods assume a single stationary reward that cannot capture goal switching…
Spectral Alignment in Forward-Backward Representations via Temporal Abstraction
Seyed Mahdi B. Azad, Jasper Hoffmann, Iman Nematollahi +3
Forward-backward (FB) representations provide a powerful framework for learning the successor representation (SR) in continuous spaces by enforcing a low-rank factorization. Howeve…
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…
Fitting Reinforcement Learning Model to Behavioral Data under Bandits
Hao Zhu, Jasper Hoffmann, Baohe Zhang +1
We consider the problem of fitting a reinforcement learning (RL) model to some given behavioral data under a multi-armed bandit environment. These models have received much attenti…
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.…
Constrained Reinforcement Learning with Smoothed Log Barrier Function
Baohe Zhang, Yuan Zhang, Lilli Frison +2
Reinforcement Learning (RL) has been widely applied to many control tasks and substantially improved the performances compared to conventional control methods in many domains where…
Multi-intention Inverse Q-learning for Interpretable Behavior Representation
Hao Zhu, Brice De La Crompe, Gabriel Kalweit +4
In advancing the understanding of natural decision-making processes, inverse reinforcement learning (IRL) methods have proven instrumental in reconstructing animal's intentions und…