17 citations · 28 across the 13 of their papers we have counts for
7 papers · 1 filter
Enhancing Counterfactual Classification via Self-Training
Ruijiang Gao, Max Biggs, Wei Sun +1
Unlike traditional supervised learning, in many settings only partial feedback is available. We may only observe outcomes for the chosen actions, but not the counterfactual outcome…
Identifying Best Fair Intervention
Ruijiang Gao, Han Feng
We study the problem of best arm identification with a fairness constraint in a given causal model. The goal is to find a soft intervention on a given node to maximize the outcome…
Loss Functions for Discrete Contextual Pricing with Observational Data
Max Biggs, Ruijiang Gao, Wei Sun
We study a pricing setting where each customer is offered a contextualized price based on customer and/or product features. Often only historical sales data are available, so we ob…
AE-StyleGAN: Improved Training of Style-Based Auto-Encoders
Ligong Han, Sri Harsha Musunuri, Martin Renqiang Min +3
StyleGANs have shown impressive results on data generation and manipulation in recent years, thanks to its disentangled style latent space. A lot of efforts have been made in inver…
Dual Projection Generative Adversarial Networks for Conditional Image Generation
Ligong Han, Martin Renqiang Min, Anastasis Stathopoulos +4
Conditional Generative Adversarial Networks (cGANs) extend the standard unconditional GAN framework to learning joint data-label distributions from samples, and have been establish…
Cost-Accuracy Aware Adaptive Labeling for Active Learning
Ruijiang Gao, Maytal Saar-tsechansky
Conventional active learning algorithms assume a single labeler that produces noiseless label at a given, fixed cost, and aim to achieve the best generalization performance for giv…
Human-AI Collaboration with Bandit Feedback
Ruijiang Gao, Maytal Saar-Tsechansky, Maria De-Arteaga +3
Human-machine complementarity is important when neither the algorithm nor the human yield dominant performance across all instances in a given domain. Most research on algorithmic…