542 citations · 1.6k across the 85 of their papers we have counts for
9 papers · 1 filter
Why does Throwing Away Data Improve Worst-Group Error?
Kamalika Chaudhuri, Kartik Ahuja, Martin Arjovsky +1
When facing data with imbalanced classes or groups, practitioners follow an intriguing strategy to achieve best results. They throw away examples until the classes or groups are ba…
The Label Complexity of Active Learning from Observational Data
Songbai Yan, Kamalika Chaudhuri, Tara Javidi
Counterfactual learning from observational data involves learning a classifier on an entire population based on data that is observed conditioned on a selection policy. This work c…
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples
Yizhen Wang, Somesh Jha, Kamalika Chaudhuri
Motivated by safety-critical applications, test-time attacks on classifiers via adversarial examples has recently received a great deal of attention. However, there is a general la…
Variational Bayes In Private Settings (VIPS)
Mijung Park, James Foulds, Kamalika Chaudhuri +1
Many applications of Bayesian data analysis involve sensitive information, motivating methods which ensure that privacy is protected. We introduce a general privacy-preserving fram…
Private Topic Modeling
Mijung Park, James Foulds, Kamalika Chaudhuri +1
We develop a privatised stochastic variational inference method for Latent Dirichlet Allocation (LDA). The iterative nature of stochastic variational inference presents challenges:…
Spectral Learning of Large Structured HMMs for Comparative Epigenomics
Chicheng Zhang, Jimin Song, Kevin C Chen +1
We develop a latent variable model and an efficient spectral algorithm motivated by the recent emergence of very large data sets of chromatin marks from multiple human cell types.…
Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons
James Y. Zou, Kamalika Chaudhuri, Adam Tauman Kalai
We introduce an unsupervised approach to efficiently discover the underlying features in a data set via crowdsourcing. Our queries ask crowd members to articulate a feature common…
Consistent procedures for cluster tree estimation and pruning
Kamalika Chaudhuri, Sanjoy Dasgupta, Samory Kpotufe +1
For a density on , a {\it high-density cluster} is any connected component of , for some . The set of all high-density clusters forms a…
Near-Optimal Algorithms for Differentially-Private Principal Components
Kamalika Chaudhuri, Anand D. Sarwate, Kaushik Sinha
Principal components analysis (PCA) is a standard tool for identifying good low-dimensional approximations to data in high dimension. Many data sets of interest contain private or…