1 citations · 3 across the 4 of their papers we have counts for
7 papers
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…
Language Generation via Combinatorial Constraint Satisfaction: A Tree Search Enhanced Monte-Carlo Approach
Maosen Zhang, Nan Jiang, Lei Li +1
Generating natural language under complex constraints is a principled formulation towards controllable text generation. We present a framework to allow specification of combinatori…
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…
End-to-End Refinement Guided by Pre-trained Prototypical Classifier
Junwen Bai, Zihang Lai, Runzhe Yang +3
Many real-world tasks involve identifying patterns from data satisfying background or prior knowledge. In domains like materials discovery, due to the flaws and biases in raw exper…
End-to-End Learning for the Deep Multivariate Probit Model
Di Chen, Yexiang Xue, Carla P. Gomes
The multivariate probit model (MVP) is a popular classic model for studying binary responses of multiple entities. Nevertheless, the computational challenge of learning the MVP mod…
Multi-Entity Dependence Learning with Rich Context via Conditional Variational Auto-encoder
Luming Tang, Yexiang Xue, Di Chen +1
Multi-Entity Dependence Learning (MEDL) explores conditional correlations among multiple entities. The availability of rich contextual information requires a nimble learning scheme…