1 citations · 1 across the 6 of their papers we have counts for
6 papers
Calibrating conditional risk
Andrey Vasilyev, Yikai Wang, Xiaocheng Li +1
We introduce and study the problem of calibrating conditional risk, which involves estimating the expected loss of a prediction model conditional on input features. We analyze this…
Risk Profiling and Modulation for LLMs
Yikai Wang, Xiaocheng Li, Guanting Chen
Large language models (LLMs) are increasingly used for decision-making tasks under uncertainty; however, their risk profiles and how they are influenced by prompting and alignment…
OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making
Hanzhao Wang, Guanting Chen, Kalyan Talluri +1
We build a Generative Pre-trained Transformer (GPT) model from scratch to solve sequential decision making tasks arising in contexts of operations research and management science w…
Reward Modeling with Ordinal Feedback: Wisdom of the Crowd
Shang Liu, Yu Pan, Guanting Chen +1
Learning a reward model (RM) from human preferences has been an important component in aligning large language models (LLMs). The canonical setup of learning RMs from pairwise pref…
Unbiased Simulation Estimators for Multivariate Jump-Diffusions
Guanting Chen, Alex Shkolnik, Kay Giesecke
We develop and analyze a class of unbiased Monte Carlo estimators for multivariate jump-diffusion processes with state-dependent drift, volatility, jump intensity and jump size. A…
An Adaptive State Aggregation Algorithm for Markov Decision Processes
Guanting Chen, Johann Demetrio Gaebler, Matt Peng +2
Value iteration is a well-known method of solving Markov Decision Processes (MDPs) that is simple to implement and boasts strong theoretical convergence guarantees. However, the co…