8 citations · 13 across the 6 of their papers we have counts for
7 papers · 1 filter
Reinforcement Learning Paycheck Optimization for Multivariate Financial Goals
Melda Alaluf, Giulia Crippa, Sinong Geng +6
We study paycheck optimization, which examines how to allocate income in order to achieve several competing financial goals. For paycheck optimization, a quantitative methodology i…
Improving Offline RL by Blending Heuristics
Sinong Geng, Aldo Pacchiano, Andrey Kolobov +1
We propose Heuristic Blending (HUBL), a simple performance-improving technique for a broad class of offline RL algorithms based on value bootstrapping. HUBL modifies the Bellman op…
A Data-Driven State Aggregation Approach for Dynamic Discrete Choice Models
Sinong Geng, Houssam Nassif, Carlos A. Manzanares
We study dynamic discrete choice models, where a commonly studied problem involves estimating parameters of agent reward functions (also known as "structural" parameters), using ag…
Deep PQR: Solving Inverse Reinforcement Learning using Anchor Actions
Sinong Geng, Houssam Nassif, Carlos A. Manzanares +2
We propose a reward function estimation framework for inverse reinforcement learning with deep energy-based policies. We name our method PQR, as it sequentially estimates the Polic…
Temporal Poisson Square Root Graphical Models
Sinong Geng, Zhaobin Kuang, Peggy Peissig +1
We propose temporal Poisson square root graphical models (TPSQRs), a generalization of Poisson square root graphical models (PSQRs) specifically designed for modeling longitudinal…
Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error
Sinong Geng, Zhaobin Kuang, Jie Liu +2
We study the -regularized maximum likelihood estimator/estimation (MLE) problem for discrete Markov random fields (MRFs), where efficient and scalable learning requires both s…