24 citations · 45 across the 6 of their papers we have counts for
6 papers · 1 filter
Generating High Fidelity Synthetic Data via Coreset selection and Entropic Regularization
Omead Pooladzandi, Pasha Khosravi, Erik Nijkamp +1
Generative models have the ability to synthesize data points drawn from the data distribution, however, not all generated samples are high quality. In this paper, we propose using…
Sales Channel Optimization via Simulations Based on Observational Data with Delayed Rewards: A Case Study at LinkedIn
Diana M. Negoescu, Pasha Khosravi, Shadow Zhao +3
Training models on data obtained from randomized experiments is ideal for making good decisions. However, randomized experiments are often time-consuming, expensive, risky, infeasi…
Probabilistic Sufficient Explanations
Eric Wang, Pasha Khosravi, Guy Van den Broeck
Understanding the behavior of learned classifiers is an important task, and various black-box explanations, logical reasoning approaches, and model-specific methods have been propo…
Handling Missing Data in Decision Trees: A Probabilistic Approach
Pasha Khosravi, Antonio Vergari, YooJung Choi +2
Decision trees are a popular family of models due to their attractive properties such as interpretability and ability to handle heterogeneous data. Concurrently, missing data is a…
On Tractable Computation of Expected Predictions
Pasha Khosravi, YooJung Choi, Yitao Liang +2
Computing expected predictions of discriminative models is a fundamental task in machine learning that appears in many interesting applications such as fairness, handling missing v…
What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features
Pasha Khosravi, Yitao Liang, YooJung Choi +1
While discriminative classifiers often yield strong predictive performance, missing feature values at prediction time can still be a challenge. Classifiers may not behave as expect…