57 citations · 150 across the 24 of their papers we have counts for
13 papers · 1 filter
PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect
Lokesh Nagalapatti, Pranava Singhal, Avishek Ghosh +1
Given a dataset of individuals each described by a covariate vector, a treatment, and an observed outcome on the treatment, the goal of the individual treatment effect (ITE) estima…
Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing
Lokesh Nagalapatti, Akshay Iyer, Abir De +1
We address the Individualized continuous treatment effect (ICTE) estimation problem where we predict the effect of any continuous-valued treatment on an individual using observatio…
Active Assessment of Prediction Services as Accuracy Surface Over Attribute Combinations
Vihari Piratla, Soumen Chakrabarty, Sunita Sarawagi
Our goal is to evaluate the accuracy of a black-box classification model, not as a single aggregate on a given test data distribution, but as a surface over a large number of combi…
Long Horizon Forecasting With Temporal Point Processes
Prathamesh Deshpande, Kamlesh Marathe, Abir De +1
In recent years, marked temporal point processes (MTPPs) have emerged as a powerful modeling machinery to characterize asynchronous events in a wide variety of applications. MTPPs…
NLP Service APIs and Models for Efficient Registration of New Clients
Sahil Shah, Vihari Piratla, Soumen Chakrabarti +1
State-of-the-art NLP inference uses enormous neural architectures and models trained for GPU-months, well beyond the reach of most consumers of NLP. This has led to one-size-fits-a…
Learning from Rules Generalizing Labeled Exemplars
Abhijeet Awasthi, Sabyasachi Ghosh, Rasna Goyal +1
In many applications labeled data is not readily available, and needs to be collected via pain-staking human supervision. We propose a rule-exemplar method for collecting human sup…