Search Results for author: Dhanya Sridhar

Found 13 papers, 6 papers with code

Estimating Social Influence from Observational Data

1 code implementation24 Mar 2022 Dhanya Sridhar, Caterina De Bacco, David Blei

We consider the problem of estimating social influence, the effect that a person's behavior has on the future behavior of their peers.

Identifiable Deep Generative Models via Sparse Decoding

1 code implementation20 Oct 2021 Gemma E. Moran, Dhanya Sridhar, Yixin Wang, David M. Blei

The underlying model is sparse in that each observed feature (i. e. each dimension of the data) depends on a small subset of the latent factors.

Representation Learning

Causal Effects of Linguistic Properties

1 code implementation NAACL 2021 Reid Pryzant, Dallas Card, Dan Jurafsky, Victor Veitch, Dhanya Sridhar

Second, in practice, we only have access to noisy proxies for the linguistic properties of interest -- e. g., predictions from classifiers and lexicons.

Language Modelling

Valid Causal Inference with (Some) Invalid Instruments

no code implementations19 Jun 2020 Jason Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown

The technique is simple to apply and is "black-box" in the sense that it may be used with any instrumental variable estimator as long as the treatment effect is identified for each valid instrument independently.

Causal Inference

Estimating Causal Effects of Tone in Online Debates

1 code implementation10 Jun 2019 Dhanya Sridhar, Lise Getoor

In this paper, we estimate the causal effect of reply tones in debates on linguistic and sentiment changes in subsequent responses.

Adapting Text Embeddings for Causal Inference

4 code implementations29 May 2019 Victor Veitch, Dhanya Sridhar, David M. Blei

To address this challenge, we develop causally sufficient embeddings, low-dimensional document representations that preserve sufficient information for causal identification and allow for efficient estimation of causal effects.

Causal Identification Causal Inference +4

Equal Opportunity and Affirmative Action via Counterfactual Predictions

no code implementations26 May 2019 Yixin Wang, Dhanya Sridhar, David M. Blei

Machine learning (ML) can automate decision-making by learning to predict decisions from historical data.

Decision Making Fairness

Scalable Structure Learning for Probabilistic Soft Logic

no code implementations3 Jul 2018 Varun Embar, Dhanya Sridhar, Golnoosh Farnadi, Lise Getoor

We introduce a greedy search-based algorithm and a novel optimization method that trade-off scalability and approximations to the structure learning problem in varying ways.

Using Noisy Extractions to Discover Causal Knowledge

no code implementations16 Nov 2017 Dhanya Sridhar, Jay Pujara, Lise Getoor

Knowledge bases (KB) constructed through information extraction from text play an important role in query answering and reasoning.

Causal Discovery

Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks

no code implementations2 Jul 2016 Shobeir Fakhraei, Dhanya Sridhar, Jay Pujara, Lise Getoor

A neighborhood graph, which represents the instances as vertices and their relations as weighted edges, is the basis of many semi-supervised and relational models for node labeling and link prediction.

graph construction Link Prediction

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