no code implementations • 8 Apr 2024 • Tejas Kasetty, Divyat Mahajan, Gintare Karolina Dziugaite, Alexandre Drouin, Dhanya Sridhar
Numerous decision-making tasks require estimating causal effects under interventions on different parts of a system.
no code implementations • 8 Feb 2024 • Sophie Xhonneux, David Dobre, Jian Tang, Gauthier Gidel, Dhanya Sridhar
Specifically, we investigate whether in-context learning (ICL) can be used to re-learn forbidden tasks despite the explicit fine-tuning of the model to refuse them.
1 code implementation • 24 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.
1 code implementation • 20 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.
1 code implementation • 2 Sep 2021 • Amir Feder, Katherine A. Keith, Emaad Manzoor, Reid Pryzant, Dhanya Sridhar, Zach Wood-Doughty, Jacob Eisenstein, Justin Grimmer, Roi Reichart, Margaret E. Roberts, Brandon M. Stewart, Victor Veitch, Diyi Yang
A fundamental goal of scientific research is to learn about causal relationships.
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.
no code implementations • 19 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.
1 code implementation • 10 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.
4 code implementations • 29 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.
no code implementations • 26 May 2019 • Yixin Wang, Dhanya Sridhar, David M. Blei
Machine learning (ML) can automate decision-making by learning to predict decisions from historical data.
no code implementations • 3 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.
no code implementations • 16 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.
no code implementations • 2 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.