151 citations · 780 across the 55 of their papers we have counts for
7 papers · 1 filter
ALSO-X and ALSO-X+: Better Convex Approximations for Chance Constrained Programs
Nan Jiang, Weijun Xie
In a chance constrained program (CCP), the decision-makers aim to seek the best decision whose probability of violating the uncertainty constraints is within the prespecified risk…
A Variant of the Wang-Foster-Kakade Lower Bound for the Discounted Setting
Philip Amortila, Nan Jiang, Tengyang Xie
Recently, Wang et al. (2020) showed a highly intriguing hardness result for batch reinforcement learning (RL) with linearly realizable value function and good feature coverage in t…
Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration
Priyank Agrawal, Jinglin Chen, Nan Jiang
This paper studies regret minimization with randomized value functions in reinforcement learning. In tabular finite-horizon Markov Decision Processes, we introduce a clipping varia…
Batch Value-function Approximation with Only Realizability
Tengyang Xie, Nan Jiang
We make progress in a long-standing problem of batch reinforcement learning (RL): learning from an exploratory and polynomial-sized dataset, using a realizable and otherw…
Q* Approximation Schemes for Batch Reinforcement Learning: A Theoretical Comparison
Tengyang Xie, Nan Jiang
We prove performance guarantees of two algorithms for approximating in batch reinforcement learning. Compared to classical iterative methods such as Fitted Q-Iteration---…
RL-Duet: Online Music Accompaniment Generation Using Deep Reinforcement Learning
Nan Jiang, Sheng Jin, Zhiyao Duan +1
This paper presents a deep reinforcement learning algorithm for online accompaniment generation, with potential for real-time interactive human-machine duet improvisation. Differen…
Minimax Value Interval for Off-Policy Evaluation and Policy Optimization
Nan Jiang, Jiawei Huang
We study minimax methods for off-policy evaluation (OPE) using value functions and marginalized importance weights. Despite that they hold promises of overcoming the exponential va…