Search Results for author:
Found 7 papers, 2 papers with code
SUBSUME: A Dataset for Subjective Summary Extraction from Wikipedia Documents
Several datasets exist for summarization with objective intents where, for each document and intent (e. g., “weather”), a single summary suffices for all users.
Non-Invasive Fairness in Learning through the Lens of Data Drift
We use a simple but key insight: the divergence of trends between different populations, and, consecutively, between a learned model and minority populations, is analogous to data drift, which indicates the poor conformance between parts of the data and the trained model.
Stochastic Package Queries in Probabilistic Databases
We provide methods for specifying -- via a SQL extension -- and processing stochastic package queries (SPQs), in order to solve optimization problems over uncertain data, right where the data resides.
Decision Making
Decision Making Under Uncertainty
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Databases
Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification
Data management research is showing an increasing presence and interest in topics related to data and algorithmic fairness, including the topic of fair classification.
Example-Driven Query Intent Discovery: Abductive Reasoning using Semantic Similarity
In this paper, we present SQuID, a system that performs semantic similarity-aware query intent discovery.
Databases
Fairness Testing: Testing Software for Discrimination
This paper defines software fairness and discrimination and develops a testing-based method for measuring if and how much software discriminates, focusing on causality in discriminatory behavior.
Lifted Inference Seen from the Other Side : The Tractable Features
Lifted inference algorithms for representations that combine first-order logic and probabilistic graphical models have been the focus of much recent research.
