# Kamalika Chaudhuri

According to our database

Collaborative distances:

^{1}, Kamalika Chaudhuri authored at least 61 papers between 2003 and 2018.Collaborative distances:

## Timeline

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## Bibliography

2018

Special Issue on ALT 2015: Guest Editors' Introduction.

Theor. Comput. Sci., 2018

Active Learning with Logged Data.

Proceedings of the 35th International Conference on Machine Learning, 2018

Analyzing the Robustness of Nearest Neighbors to Adversarial Examples.

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Learning to blame: localizing novice type errors with data-driven diagnosis.

PACMPL, 2017

Pufferfish Privacy Mechanisms for Correlated Data.

Proceedings of the 2017 ACM International Conference on Management of Data, 2017

Bolt-on Differential Privacy for Scalable Stochastic Gradient Descent-based Analytics.

Proceedings of the 2017 ACM International Conference on Management of Data, 2017

Approximation and Convergence Properties of Generative Adversarial Learning.

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Renyi Differential Privacy Mechanisms for Posterior Sampling.

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Active Heteroscedastic Regression.

Proceedings of the 34th International Conference on Machine Learning, 2017

Composition properties of inferential privacy for time-series data.

Proceedings of the 55th Annual Allerton Conference on Communication, 2017

2016

On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis.

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Active Learning from Imperfect Labelers.

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

The Extended Littlestone's Dimension for Learning with Mistakes and Abstentions.

Proceedings of the 29th Conference on Learning Theory, 2016

2015

Bayesian Active Learning With Non-Persistent Noise.

IEEE Trans. Information Theory, 2015

Spectral Learning of Large Structured HMMs for Comparative Epigenomics.

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Active Learning from Weak and Strong Labelers.

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Convergence Rates of Active Learning for Maximum Likelihood Estimation.

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Crowdsourcing Feature Discovery via Adaptively Chosen Comparisons.

Proceedings of the Third AAAI Conference on Human Computation and Crowdsourcing, 2015

Active learning from noisy and abstention feedback.

Proceedings of the 53rd Annual Allerton Conference on Communication, 2015

Learning from Data with Heterogeneous Noise using SGD.

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Consistent Procedures for Cluster Tree Estimation and Pruning.

IEEE Trans. Information Theory, 2014

Beyond Disagreement-Based Agnostic Active Learning.

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

The Large Margin Mechanism for Differentially Private Maximization.

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Rates of Convergence for Nearest Neighbor Classification.

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

Signal Processing and Machine Learning with Differential Privacy: Algorithms and Challenges for Continuous Data.

IEEE Signal Process. Mag., 2013

A near-optimal algorithm for differentially-private principal components.

J. Mach. Learn. Res., 2013

A Stability-based Validation Procedure for Differentially Private Machine Learning.

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Stochastic gradient descent with differentially private updates.

Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

Extrinsic Jensen-Shannon divergence and noisy Bayesian active learning.

Proceedings of the 51st Annual Allerton Conference on Communication, 2013

2012

Spectral Clustering of Graphs with General Degrees in the Extended Planted Partition Model.

Proceedings of the COLT 2012, 2012

iDASH: integrating data for analysis, anonymization, and sharing.

JAMIA, 2012

Near-optimal Differentially Private Principal Components.

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Convergence Rates for Differentially Private Statistical Estimation.

Proceedings of the 29th International Conference on Machine Learning, 2012

Noisy Bayesian active learning.

Proceedings of the 50th Annual Allerton Conference on Communication, 2012

2011

Differentially Private Empirical Risk Minimization.

J. Mach. Learn. Res., 2011

Sample Complexity Bounds for Differentially Private Learning.

Proceedings of the COLT 2011, 2011

Spectral Methods for Learning Multivariate Latent Tree Structure.

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010

An Online Learning-based Framework for Tracking.

Proceedings of the UAI 2010, 2010

Rates of convergence for the cluster tree.

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009

A push-relabel approximation algorithm for approximating the minimum-degree MST problem and its generalization to matroids.

Theor. Comput. Sci., 2009

A Parameter-free Hedging Algorithm.

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Online Bipartite Perfect Matching With Augmentations.

Proceedings of the INFOCOM 2009. 28th IEEE International Conference on Computer Communications, 2009

Multi-view clustering via canonical correlation analysis.

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008

A Network Coloring Game.

Proceedings of the Internet and Network Economics, 4th International Workshop, 2008

Privacy-preserving logistic regression.

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Beyond Gaussians: Spectral Methods for Learning Mixtures of Heavy-Tailed Distributions.

Proceedings of the 21st Annual Conference on Learning Theory, 2008

Learning Mixtures of Product Distributions Using Correlations and Independence.

Proceedings of the 21st Annual Conference on Learning Theory, 2008

Finding Metric Structure in Information Theoretic Clustering.

Proceedings of the 21st Annual Conference on Learning Theory, 2008

2007

A rigorous analysis of population stratification with limited data.

Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2007

Privacy, accuracy, and consistency too: a holistic solution to contingency table release.

Proceedings of the Twenty-Sixth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 2007

2006

On the tandem duplication-random loss model of genome rearrangement.

Proceedings of the Seventeenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2006

A Push-Relabel Algorithm for Approximating Degree Bounded MSTs.

Proceedings of the Automata, Languages and Programming, 33rd International Colloquium, 2006

When Random Sampling Preserves Privacy.

Proceedings of the Advances in Cryptology, 2006

2005

Value-maximizing deadline scheduling and its application to animation rendering.

Proceedings of the SPAA 2005: Proceedings of the 17th Annual ACM Symposium on Parallelism in Algorithms and Architectures, 2005

Deadline scheduling for animation rendering.

Proceedings of the International Conference on Measurements and Modeling of Computer Systems, 2005

Server Allocation Algorithms for Tiered Systems.

Proceedings of the Computing and Combinatorics, 11th Annual International Conference, 2005

What Would Edmonds Do? Augmenting Paths and Witnesses for Degree-Bounded MSTs.

Proceedings of the Approximation, 2005

2004

Selfish caching in distributed systems: a game-theoretic analysis.

Proceedings of the Twenty-Third Annual ACM Symposium on Principles of Distributed Computing, 2004

2003

Location determination of a mobile device using IEEE 802.11b access point signals.

Proceedings of the 2003 IEEE Wireless Communications and Networking, 2003

An Extension of Scalable Global IP Anycasting for Load Balancing in the Internet.

Proceedings of the Information Networking, 2003

Paths, Trees, and Minimum Latency Tours.

Proceedings of the 44th Symposium on Foundations of Computer Science (FOCS 2003), 2003