3 citations · 5 across the 4 of their papers we have counts for
4 papers
X-MEN: Guaranteed XOR-Maximum Entropy Constrained Inverse Reinforcement Learning
Fan Ding, Yeiang Xue
Inverse Reinforcement Learning (IRL) is a powerful way of learning from demonstrations. In this paper, we address IRL problems with the availability of prior knowledge that optimal…
Provable Constrained Stochastic Convex Optimization with XOR-Projected Gradient Descent
Fan Ding, Yijie Wang, Jianzhu Ma +1
Provably solving stochastic convex optimization problems with constraints is essential for various problems in science, business, and statistics. Recently proposed XOR-Stochastic G…
Stein Variational Inference for Discrete Distributions
Jun Han, Fan Ding, Xianglong Liu +3
Gradient-based approximate inference methods, such as Stein variational gradient descent (SVGD), provide simple and general-purpose inference engines for differentiable continuous…
Towards Efficient Discrete Integration via Adaptive Quantile Queries
Fan Ding, Hanjing Wang, Ashish Sabharwal +1
Discrete integration in a high dimensional space of n variables poses fundamental challenges. The WISH algorithm reduces the intractable discrete integration problem into n optimiz…