21 citations · 22 across the 19 of their papers we have counts for
7 papers · 1 filter
Label Differential Privacy via Aggregation
Anand Brahmbhatt, Rishi Saket, Shreyas Havaldar +3
This paper explores the use of linear aggregation to protect the privacy of sensitive training labels through the concept of \emph{label differential privacy} (label-DP) while main…
PAC Learning Linear Thresholds from Label Proportions
Anand Brahmbhatt, Rishi Saket, Aravindan Raghuveer
Learning from label proportions (LLP) is a generalization of supervised learning in which the training data is available as sets or bags of feature-vectors (instances) along with t…
LLP-Bench: A Large Scale Tabular Benchmark for Learning from Label Proportions
Anand Brahmbhatt, Mohith Pokala, Rishi Saket +1
In the task of Learning from Label Proportions (LLP), a model is trained on groups (a.k.a bags) of instances and their corresponding label proportions to predict labels for individ…
Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation
Shreyas Havaldar, Navodita Sharma, Shubhi Sareen +2
Learning from Label Proportions (LLP) is a learning problem where only aggregate level labels are available for groups of instances, called bags, during training, and the aim is to…
Fairness under Covariate Shift: Improving Fairness-Accuracy tradeoff with few Unlabeled Test Samples
Shreyas Havaldar, Jatin Chauhan, Karthikeyan Shanmugam +2
Covariate shift in the test data is a common practical phenomena that can significantly downgrade both the accuracy and the fairness performance of the model. Ensuring fairness acr…
BiPhone: Modeling Inter Language Phonetic Influences in Text
Abhirut Gupta, Ananya B. Sai, Richard Sproat +5
A large number of people are forced to use the Web in a language they have low literacy in due to technology asymmetries. Written text in the second language (L2) from such users o…
ReTAG: Reasoning Aware Table to Analytic Text Generation
Deepanway Ghosal, Preksha Nema, Aravindan Raghuveer
The task of table summarization involves generating text that both succinctly and accurately represents the table or a specific set of highlighted cells within a table. While signi…