Differentially Private Conditional Independence Testing
With I. Kalemaj and A. Ramdas

Debiasing Conditional Stochastic Optimization
With L. He

Interventional and Counterfactual Inference with Diffusion Models
With P. Chao and P. Bloebaum

Thompson Sampling with Diffusion Generative Prior
With Y. Hsieh, B. Kveton, and P. Bloebaum
In proceedings of ICML 2023

Sequential Kernelized Independence Testing
With A. Podkopaev, P. Bloebaum, and A. Ramdas
In proceedings of ICML 2023

Uplifting Bandits
With Y. Hsieh and B. Kveton
In proceedings of NeurIPS 2022

On Measuring Causal Contributions via do-interventions
With Y. Jung, J. Tian, D. Janzing, P. Bloebaum, and E. Bareinboim
In proceedings of ICML 2022

Balancing Utility and Scalability in Metric Differential Privacy
With J. Imola, S. White, A. Aggarwal, and N. Teissier
In proceedings of UAI 2022

Reconstructing Test Labels from Noisy Loss Functions
With A. Aggarwal, Z. Xu, O. Feyisetan, and N. Teissier
In proceedings of AISTATS 2022

Collaborative Causal Discovery with Atomic Interventions
With R. Addanki
In proceedings of NeurIPS 2021

Label Inference Attacks from Log-loss Scores
With A. Aggarwal, Z. Xu, O. Feyisetan, and N. Teissier
In proceedings of ICML 2021 (selected for long oral presentation)

Federated Learning under Arbitrary Communication Patterns
With Dmitrii Avdyukhin
In proceedings of ICML 2021

SGD with Low-Dimensional Gradients with Applications to Private and Distributed Learning
In proceedings of UAI 2021

Private Release of Text Embedding Vectors
With O. Feyisetan
In proceedings of First Workshop on Trustworthy Natural Language Processing (part of ACL 2021)

Restricted Isometry Property under High Correlations
With M. Rudelson

Efficient Intervention Design for Causal Discovery with Latents
With R. Addanki, A. McGregor, and C. Musco
In proceedings of ICML 2020

Contextual Online False Discovery Rate Control
With S. Chen
In proceedings of AISTATS 2020

Subsampled Renyi Differential Privacy and Analytical Moments Accountant
With Y. Wang and B. Balle
In proceedings of AISTATS 2019 (selected for oral presentation)
Full version, In Journal of Privacy and Confidentiality, 2020
A preliminary version appeared at workshops: PPML 2018 and TPDP 2018 - Theory and Practice of Differential Privacy

Restricted Eigenvalue from Stable Rank with Applications to Sparse Linear Regression
With M. Rudelson
In proceedings of COLT 2018

Semi-Supervised Learning on Data Streams via Temporal Label Propagation
With T. Wagner, S. Guha, and N. Mishra
In proceedings of ICML 2018

Network Approximation using Tensor Sketching
With N. Narodytska and H. Jin
In proceedings of IJCAI 2018
Preliminary version appeared at the NIPS 2016 Workshop on Deep Learning: Bridging Theory and Practice
Full version of this paper can be found here

Verifying Properties of Binarized Deep Neural Networks
With N. Narodytska, L. Ryzhyk, M. Sagiv, and T. Walsh
In proceedings of AAAI 2018

Simple Black-Box Adversarial Attacks on Deep Neural Networks
With N. Narodytska
In proceedings of CVPR 2017 Workshops
Preliminary version appeared at the NIPS 2016 Workshop on Adversarial Training

Private Incremental Regression
With K. Nissim and H. Jin
In proceedings of PODS 2017

Efficient Private Empirical Risk Minimization for High-dimensional Learning
With H. Jin
In proceedings of ICML 2016

Streaming Anomaly Detection Using Randomized Matrix Sketching
With H. Huang
In proceedings of VLDB 2016

Streaming Spectral Clustering
With S. Yoo and H. Huang
In proceedings of ICDE 2016

Private Spatial Data Aggregation in the Local Setting
With R. Chen, H. Li, A.K. Win, and H. Jin
In proceedings of ICDE 2016
Invited to IEEE Transactions on Knowledge and Data Engineering (special issue)

Spectral Norm of Random Kernel Matrices with Applications to Privacy
With M. Rudelson
In proceedings of RANDOM 2015

Unsupervised Feature Selection on Data Streams
With H. Huang and S. Yoo
In proceedings of CIKM 2015

Online Dictionary Learning on Symmetric Positive Definite Manifolds with Vision Applications
With S. Zhang, P. Yuen, and M. Harandi
In proceedings of AAAI 2015
Associated code can be found here: here

On the Semantics of Differential Privacy: A 'Bayesian' Formulation
With A. Smith
In Journal of Privacy and Confidentiality, 2014
Earlier version: A Note on Differential Privacy: Defining Resistance to Arbitrary Side Information

Bounds on the Sample Complexity for Private Learning and Private Data Release
With A. Beimel, H. Brenner, and K. Nissim
In Machine Learning Journal, 2014
Earlier version appeared in proceedings of TCC 2010

The Power of Linear Reconstruction Attacks
With M. Rudelson and A. Smith
In proceedings of SODA 2013

Analyzing Graphs with Node Differential Privacy
With K. Nissim, S. Raskhodnikova, and A. Smith
In proceedings of TCC 2013
Full version of this paper can be found here

Fast Online L1-Dictionary Learning Algorithms For Novel Document Detection
In proceedings of ICASSP 2013 (Invited Presentation)
Special session on Sparse Signal Techniques for Web Information Processing

Novel Document Detection on Massive Data Streams using Distributed Dictionary Learning
With G. Cong, P. Melville, and R. Lawrence
In IBM Journal of Research and Development, 2013

Approximately Counting Embeddings into Random Graphs
With M. Furer
In Combinatorics, Probability & Computing, 2014 (special issue on Analysis of Algorithms)
Earlier version appeared in proceedings of RANDOM 2008

An Exponential Time 2-Approximation Algorithm for Bandwidth
With M. Furer and S. Gaspers
In Theoretical Computer Science, 2013 (special issue on Exact & Parameterized Computation)
Earlier version appeared in proceedings of IWPEC 2009

Online L1-Dictionary Learning with Application to Novel Document Detection
With H. Wang, A. Banerjee, and P. Melville
In proceedings of NIPS 2012
Full version of this paper can be found here
Preliminary version appeared at the KDD SOMA Workshop 2012

Efficient and Practical Stochastic Subgradient Descent for Nuclear Norm Regularization
With H. Avron, S. Kale, and V. Sindhwani
In proceedings of ICML 2012

Emerging Topic Detection Using Dictionary Learning
With P. Melville, A. Banerjee, and V. Sindhwani
In proceedings of CIKM 2011
Full version of this paper can be found here

Geography-Based Analysis of the Internet Infrastructure
With S. Eidenbenz and G. Yan
In proceedings of IEEE INFOCOM (mini-conference) 2011
Full version of this paper can be found here

The Rigidity Transition for Random Graphs
With C. Moore and L. Theran
In proceedings of SODA 2011

Efficient Placement of Directional Antennas in Infrastructure-based Wireless Networks
With F. Pan
In proceedings of MILCOM 2011

What Can We Learn Privately?
With H. K. Lee, K. Nissim, S. Raskhodnikova, and A. Smith
In SIAM Journal on Computing, 2011 (special issue for selected papers from FOCS 2008)
Earlier version appeared in proceedings of FOCS 2008

The Price of Privately Releasing Contingency Tables and the Spectra of Random Matrices with Correlated Rows
With M. Rudelson, A. Smith, and J. Ullman
In proceedings of ACM STOC 2010
Full version of this paper can be found here

Matrix Interdiction Problem
With F. Pan
In proceedings of CPAIOR 2010

Spatial Scattering for Load Balancing in Conservatively Synchronized Parallel Discrete-Event Simulations
With S. Thulasidasan, S. Eidenbenz, and P. Romero
In proceedings of ACM/IEEE/SCS PADS 2010

Bandwidth Provisioning in Infrastructure based Wireless Networks Employing Directional Antennas
With B. Zhao, B. Urgaonkar, and S. Vasudevan
In Pervasive and Mobile Computing, 2011 (special issue for selected papers from ICDCN 2010)
Earlier version appeared in proceedings of ICDCN 2010

Designing Systems for Large-Scale, Discrete-Event Simulations: Experiences with the FastTrans Microsimulator
With S. Thulasidasan, S. Eidenbenz, E. Galli, S. Mniszewski, and P. Romero
In proceedings of IEEE HIPC 2009

Composition Attacks and Auxiliary Information in Data Privacy
With S. R. Ganta and A. Smith
In proceedings of ACM SIGKDD 2008

Approximation Algorithms for Graph Problems (please email me for a copy)
Ph.D. Thesis, Penn State University, 2008

Packing to Angles and Sectors
With P. Berman, J. Jeong, and B. Urgaonkar
In proceedings of ACM SPAA 2007

Spanners for Geometric Intersection Graphs with Applications
With M. Furer
In Journal of Computational Geometry, 2012
Earlier version appeared in proceedings of WADS 2007

Faster Approximation of Distances in Graphs
With P. Berman
In proceedings of WADS 2007

Exact Max 2-SAT: Easier and Faster
With M. Furer
In proceedings of SOFSEM 2007

Approximate Distance Queries in Disk Graphs
With M. Furer
In proceedings of WAOA 2006

Combinatorics of TCP Reordering
With A. Hansson and G. Istrate
In Journal of Combinatorial Optimization, 2006

Approximately Counting Perfect Matchings in General Graphs
With M. Furer
In proceedings of SIAM ALENEX/ANLACO 2005

Algorithms for Counting 2-SAT Solutions and Colorings with Applications
With M. Furer
In proceedings of AAIM 2007
Full version appeared as ECCC report TR05-033, 2005

An Almost Linear Time Approximation Algorithm for the Permanent of Random (0-1) Matrix
With M. Furer
In proceedings of FSTTCS 2004

Debiasing Conditional Stochastic Optimization

Interventional and Counterfactual Inference with Diffusion Models

Thompson Sampling with Diffusion Generative Prior

Sequential Kernelized Independence Testing

Uplifting Bandits

On Measuring Causal Contributions via do-interventions

Balancing Utility and Scalability in Metric Differential Privacy

Reconstructing Test Labels from Noisy Loss Functions

Collaborative Causal Discovery with Atomic Interventions

Label Inference Attacks from Log-loss Scores

Federated Learning under Arbitrary Communication Patterns

SGD with Low-Dimensional Gradients with Applications to Private and Distributed Learning

Private Release of Text Embedding Vectors

Restricted Isometry Property under High Correlations

Efficient Intervention Design for Causal Discovery with Latents

Contextual Online False Discovery Rate Control

Subsampled Renyi Differential Privacy and Analytical Moments Accountant

**Winner of Notable Paper Award at AISTATS 2019**

Restricted Eigenvalue from Stable Rank with Applications to Sparse Linear Regression

Semi-Supervised Learning on Data Streams via Temporal Label Propagation

Network Approximation using Tensor Sketching

Verifying Properties of Binarized Deep Neural Networks

Simple Black-Box Adversarial Attacks on Deep Neural Networks

Private Incremental Regression

Efficient Private Empirical Risk Minimization for High-dimensional Learning

Streaming Anomaly Detection Using Randomized Matrix Sketching

Streaming Spectral Clustering

Private Spatial Data Aggregation in the Local Setting

Spectral Norm of Random Kernel Matrices with Applications to Privacy

Unsupervised Feature Selection on Data Streams

Online Dictionary Learning on Symmetric Positive Definite Manifolds with Vision Applications

On the Semantics of Differential Privacy: A 'Bayesian' Formulation

Bounds on the Sample Complexity for Private Learning and Private Data Release

The Power of Linear Reconstruction Attacks

Analyzing Graphs with Node Differential Privacy

Fast Online L1-Dictionary Learning Algorithms For Novel Document Detection

Novel Document Detection on Massive Data Streams using Distributed Dictionary Learning

Approximately Counting Embeddings into Random Graphs

An Exponential Time 2-Approximation Algorithm for Bandwidth

Online L1-Dictionary Learning with Application to Novel Document Detection

Efficient and Practical Stochastic Subgradient Descent for Nuclear Norm Regularization

Emerging Topic Detection Using Dictionary Learning

Geography-Based Analysis of the Internet Infrastructure

The Rigidity Transition for Random Graphs

Efficient Placement of Directional Antennas in Infrastructure-based Wireless Networks

What Can We Learn Privately?

The Price of Privately Releasing Contingency Tables and the Spectra of Random Matrices with Correlated Rows

Matrix Interdiction Problem

Spatial Scattering for Load Balancing in Conservatively Synchronized Parallel Discrete-Event Simulations

Bandwidth Provisioning in Infrastructure based Wireless Networks Employing Directional Antennas

Designing Systems for Large-Scale, Discrete-Event Simulations: Experiences with the FastTrans Microsimulator

Composition Attacks and Auxiliary Information in Data Privacy

Approximation Algorithms for Graph Problems (please email me for a copy)

Packing to Angles and Sectors

Spanners for Geometric Intersection Graphs with Applications

Faster Approximation of Distances in Graphs

Exact Max 2-SAT: Easier and Faster

**Winner of best paper award**

Approximate Distance Queries in Disk Graphs

Combinatorics of TCP Reordering

Approximately Counting Perfect Matchings in General Graphs

Algorithms for Counting 2-SAT Solutions and Colorings with Applications

An Almost Linear Time Approximation Algorithm for the Permanent of Random (0-1) Matrix