Publications (94)
Distribution-Free Distribution Regression
Barnabas Poczos, Alessandro Rinaldo, Aarti Singh +1
`Distribution regression' refers to the situation where a response Y depends on a covariate P where P is a probability distribution. The model is Y=f(P) + mu where f is an unknown…
Controllable Text Generation in the Instruction-Tuning Era
Dhananjay Ashok, Barnabas Poczos
While most research on controllable text generation has focused on steering base Language Models, the emerging instruction-tuning and prompting paradigm offers an alternate approac…
Equivariance Through Parameter-Sharing
Siamak Ravanbakhsh, Jeff Schneider, Barnabas Poczos
We propose to study equivariance in deep neural networks through parameter symmetries. In particular, given a group that acts discretely on the input and output of a…
Autonomous discovery of battery electrolytes with robotic experimentation and machine-learning
Adarsh Dave, Jared Mitchell, Kirthevasan Kandasamy +5
Innovations in batteries take years to formulate and commercialize, requiring extensive experimentation during the design and optimization phases. We approached the design and sele…
Influence Functions for Machine Learning: Nonparametric Estimators for Entropies, Divergences and Mutual Informations
Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabas Poczos +2
We propose and analyze estimators for statistical functionals of one or more distributions under nonparametric assumptions. Our estimators are based on the theory of influence func…
Politeness Transfer: A Tag and Generate Approach
Aman Madaan, Amrith Setlur, Tanmay Parekh +6
This paper introduces a new task of politeness transfer which involves converting non-polite sentences to polite sentences while preserving the meaning. We also provide a dataset o…