most citedDENS: A Dataset for Multi-class Emotion Analysis

4 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ML2020

Prediction of Spatial Point Processes: Regularized Method with Out-of-Sample Guarantees

Muhammad Osama, Dave Zachariah, Petre Stoica

A spatial point process can be characterized by an intensity function which predicts the number of events that occur across space. In this paper, we develop a method to infer predi…

cs.LG2020

Learning Robust Decision Policies from Observational Data

Muhammad Osama, Dave Zachariah, Peter Stoica

We address the problem of learning a decision policy from observational data of past decisions in contexts with features and associated outcomes. The past policy maybe unknown and…

cs.CL20194 cited

DENS: A Dataset for Multi-class Emotion Analysis

Chen Liu, Muhammad Osama, Anderson de Andrade

We introduce a new dataset for multi-class emotion analysis from long-form narratives in English. The Dataset for Emotions of Narrative Sequences (DENS) was collected from both cla…

stat.ML20192 cited

Robust Risk Minimization for Statistical Learning

Muhammad Osama, Dave Zachariah, Peter Stoica

We consider a general statistical learning problem where an unknown fraction of the training data is corrupted. We develop a robust learning method that only requires specifying an…

stat.ME20192 cited

Inferring Heterogeneous Causal Effects in Presence of Spatial Confounding

Muhammad Osama, Dave Zachariah, Thomas B. Schön

We address the problem of inferring the causal effect of an exposure on an outcome across space, using observational data. The data is possibly subject to unmeasured confounding va…