Negar Kiyavash

Orcid: 0000-0002-8545-7709

According to our database1, Negar Kiyavash authored at least 185 papers between 2003 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Recursive Causal Discovery.
CoRR, 2024

Confounded Budgeted Causal Bandits.
CoRR, 2024

s-ID: Causal Effect Identification in a Sub-population.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Editorial Special Issue on Causality: Fundamental Limits and Applications.
IEEE J. Sel. Areas Inf. Theory, 2023

Analysis of Large Market Data Using Neural Networks: A Causal Approach.
IEEE J. Sel. Areas Inf. Theory, 2023

Modeling Systemic Risk: A Time-Varying Nonparametric Causal Inference Framework.
CoRR, 2023

Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous Data.
CoRR, 2023

Efficiently Escaping Saddle Points for Non-Convex Policy Optimization.
CoRR, 2023

CausalCite: A Causal Formulation of Paper Citations.
CoRR, 2023

On sample complexity of conditional independence testing with Von Mises estimator with application to causal discovery.
CoRR, 2023

Gaussian Database Alignment and Gaussian Planted Matching.
CoRR, 2023

Learning Causal Graphs via Monotone Triangular Transport Maps.
CoRR, 2023

Causal Bandits without Graph Learning.
CoRR, 2023

On Identifiability of Conditional Causal Effects.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

A Cross-Moment Approach for Causal Effect Estimation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Causal Imitability Under Context-Specific Independence Relations.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Causal Effect Identification in Uncertain Causal Networks.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Novel Ordering-Based Approaches for Causal Structure Learning in the Presence of Unobserved Variables.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Causal Discovery in Probabilistic Networks with an Identifiable Causal Effect.
CoRR, 2022

Stochastic Second-Order Methods Provably Beat SGD For Gradient-Dominated Functions.
CoRR, 2022

A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models.
CoRR, 2022

Adaptive Momentum-Based Policy Gradient with Second-Order Information.
CoRR, 2022

Revisiting the general identifiability problem.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Causal Discovery in Linear Latent Variable Models Subject to Measurement Error.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Functions.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sharp Analysis of Stochastic Optimization under Global Kurdyka-Lojasiewicz Inequality.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Minimum Cost Intervention Design for Causal Effect Identification.
Proceedings of the International Conference on Machine Learning, 2022

Causal Discovery in Linear Structural Causal Models with Deterministic Relations.
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

Causal Effect Identification with Context-specific Independence Relations of Control Variables.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Learning Bayesian Networks in the Presence of Structural Side Information.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Optimal Adversarial Policies in the Multiplicative Learning System With a Malicious Expert.
IEEE Trans. Inf. Forensics Secur., 2021

Editorial.
Proc. ACM Meas. Anal. Comput. Syst., 2021

Information Theoretic Measures for Fairness-aware Feature Selection.
CoRR, 2021

The complexity of nonconvex-strongly-concave minimax optimization.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Recursive Markov Boundary-Based Approach to Causal Structure Learning.
Proceedings of the KDD 2021 Workshop on Causal Discovery, 2021

The KDD 2021 Workshop on Causal Discovery (CD2021).
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Preface: The 2021 ACM SIGKDD Workshop on Causal Discovery.
Proceedings of the KDD 2021 Workshop on Causal Discovery, 2021

Impact of Data Processing on Fairness in Supervised Learning.
Proceedings of the IEEE International Symposium on Information Theory, 2021

Cumulants of Hawkes Processes are Robust to Observation Noise.
Proceedings of the 38th International Conference on Machine Learning, 2021

Selective Labeling in Learning with Expert Advice.
Proceedings of the 2021 American Control Conference, 2021

A Variational Inference Approach to Learning Multivariate Wold Processes.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Graph Signal Processing: Foundations and Emerging Directions [From the Guest Editors].
IEEE Signal Process. Mag., 2020

Guest Editorial.
IEEE J. Sel. Areas Inf. Theory, 2020

Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables.
J. Mach. Learn. Res., 2020

A Recursive Markov Blanket-Based Approach to Causal Structure Learning.
CoRR, 2020

Global Convergence and Variance-Reduced Optimization for a Class of Nonconvex-Nonconcave Minimax Problems.
CoRR, 2020

Adversarial Policies in Learning Systems with Malicious Experts.
CoRR, 2020

Model-Augmented Conditional Mutual Information Estimation for Feature Selection.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Partial Recovery of Erdős-Rényi Graph Alignment via k-Core Alignment.
Proceedings of the Abstracts of the 2020 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems, 2020

A Catalyst Framework for Minimax Optimization.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

The Devil is in the Detail: A Framework for Macroscopic Prediction via Microscopic Models.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Global Convergence and Variance Reduction for a Class of Nonconvex-Nonconcave Minimax Problems.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Achievability of nearly-exact alignment for correlated Gaussian databases.
Proceedings of the IEEE International Symposium on Information Theory, 2020

Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs.
Proceedings of the 37th International Conference on Machine Learning, 2020

LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Analysis of a Canonical Labeling Algorithm for the Alignment of Correlated Erdos-Rényi Graphs.
Proc. ACM Meas. Anal. Comput. Syst., 2019

Partial Recovery of Erdðs-Rényi Graph Alignment via k-Core Alignment.
Proc. ACM Meas. Anal. Comput. Syst., 2019

A bi-criteria multiple-choice secretary problem.
IISE Trans., 2019

Model-Augmented Nearest-Neighbor Estimation of Conditional Mutual Information for Feature Selection.
CoRR, 2019

Characterizing Distribution Equivalence for Cyclic and Acyclic Directed Graphs.
CoRR, 2019

Interventional Experiment Design for Causal Structure Learning.
CoRR, 2019

A Novel Side-Channel in Real-Time Schedulers.
Proceedings of the 25th IEEE Real-Time and Embedded Technology and Applications Symposium, 2019

Learning Positive Functions with Pseudo Mirror Descent.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning Hawkes Processes Under Synchronization Noise.
Proceedings of the 36th International Conference on Machine Learning, 2019

Database Alignment with Gaussian Features.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Counting and Sampling from Markov Equivalent DAGs Using Clique Trees.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Learning From Sleeping Experts: Rewarding Informative, Available, and Accurate Experts.
ACM Trans. Design Autom. Electr. Syst., 2018

Optimal Attack Strategies Against Predictors - Learning From Expert Advice.
IEEE Trans. Inf. Forensics Secur., 2018

A Covert Queueing Channel in FCFS Schedulers.
IEEE Trans. Inf. Forensics Secur., 2018

Guest Editorial: Special Issue on Causal Discovery 2017.
Int. J. Data Sci. Anal., 2018

ScheduLeak: A Novel Scheduler Side-Channel Attack Against Real-Time Autonomous Control Systems.
CoRR, 2018

REORDER: Securing Dynamic-Priority Real-Time Systems Using Schedule Obfuscation.
CoRR, 2018

On the Performance of a Canonical Labeling for Matching Correlated Erdős-Rényi Graphs.
CoRR, 2018

Counting and Uniform Sampling from Markov Equivalent DAGs.
CoRR, 2018

Adversarial Machine Learning: The Case of Recommendation Systems.
Proceedings of the 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2018

Predictive Approximate Bayesian Computation via Saddle Points.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Multi-domain Causal Structure Learning in Linear Systems.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Fairness in Supervised Learning: An Information Theoretic Approach.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Fundamental Limits of Database Alignment.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Budgeted Experiment Design for Causal Structure Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

Learning Vector Autoregressive Models With Latent Processes.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Measuring Causal Relationships in Dynamical Systems through Recovery of Functional Dependencies.
IEEE Trans. Signal Inf. Process. over Networks, 2017

Bounded-Degree Connected Approximations of Stochastic Networks.
IEEE Trans. Mol. Biol. Multi Scale Commun., 2017

Phonion: Practical Protection of Metadata in Telephony Networks.
Proc. Priv. Enhancing Technol., 2017

Exact alignment recovery for correlated Erdos Renyi graphs.
CoRR, 2017

Significance of Side Information in the Graph Matching Problem.
CoRR, 2017

Learning Latent Networks in Vector Auto Regressive Models.
CoRR, 2017

A Covert Queueing Channel in Round Robin Schedulers.
CoRR, 2017

Optimal Experiment Design for Causal Discovery from Fixed Number of Experiments.
CoRR, 2017

A New Measure of Conditional Dependence for Causal Structural Learning.
CoRR, 2017

A Reconnaissance Attack Mechanism for Fixed-Priority Real-Time Systems.
CoRR, 2017

Online Learning for Multivariate Hawkes Processes.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learning Causal Structures Using Regression Invariance.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Identifying nonlinear 1-step causal influences in presence of latent variables.
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Interaction information for causal inference: The case of directed triangle.
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Efficient neighborhood selection for walk summable Gaussian graphical models.
Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

2016
Mitigating Timing Side Channel in Shared Schedulers.
IEEE/ACM Trans. Netw., 2016

Quantifying the Information Leakage in Timing Side Channels in Deterministic Work-Conserving Schedulers.
IEEE/ACM Trans. Netw., 2016

Restricted Composition Deletion Correcting Codes.
IEEE Trans. Inf. Theory, 2016

Generalized Sphere-Packing Bounds on the Size of Codes for Combinatorial Channels.
IEEE Trans. Inf. Theory, 2016

Learning Minimal Latent Directed Information Polytrees.
Neural Comput., 2016

On the Vulnerability of Digital Fingerprinting Systems to Finite Alphabet Collusion Attacks.
CoRR, 2016

On the Simultaneous Preservation of Privacy and Community Structure in Anonymized Networks.
CoRR, 2016

Learning Network of Multivariate Hawkes Processes: A Time Series Approach.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Improved Achievability and Converse Bounds for Erdos-Renyi Graph Matching.
Proceedings of the 2016 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Science, 2016

Message partitioning and limited auxiliary randomness: Alternatives to Honey Encryption.
Proceedings of the IEEE International Symposium on Information Theory, 2016

Interventional dependency graphs: An approach for discovering influence structure.
Proceedings of the IEEE International Symposium on Information Theory, 2016

Sneak-Peek: High speed covert channels in data center networks.
Proceedings of the 35th Annual IEEE International Conference on Computer Communications, 2016

2015
Directed Information Graphs.
IEEE Trans. Inf. Theory, 2015

Delay-Privacy Tradeoff in the Design of Scheduling Policies.
IEEE Trans. Inf. Theory, 2015

Efficient Neighborhood Selection for Gaussian Graphical Models.
CoRR, 2015

Bounded Degree Approximations of Stochastic Networks.
CoRR, 2015

Combinatorial channels from partially ordered sets.
Proceedings of the 2015 IEEE Information Theory Workshop, 2015

Capacity limit of queueing timing channel in shared FCFS schedulers.
Proceedings of the IEEE International Symposium on Information Theory, 2015

2014
Non-Blind Watermarking of Network Flows.
IEEE/ACM Trans. Netw., 2014

An Improvement to Levenshtein's Upper Bound on the Cardinality of Deletion Correcting Codes.
IEEE Trans. Inf. Theory, 2014

Dynamic and Succinct Statistical Analysis of Neuroscience Data.
Proc. IEEE, 2014

On the Varshamov-Tenengolts construction on binary strings.
Discret. Math., 2014

Timing Side Channels in Shared Queues.
CoRR, 2014

Generalized sphere-packing and sphere-covering bounds on the size of codes for combinatorial channels.
CoRR, 2014

A novel collusion attack on finite alphabet digital fingerprinting systems.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Generalized sphere-packing upper bounds on the size of codes for combinatorial channels.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Directed Information Graphs: A generalization of Linear Dynamical Graphs.
Proceedings of the American Control Conference, 2014

2013
Efficient Methods to Compute Optimal Tree Approximations of Directed Information Graphs.
IEEE Trans. Signal Process., 2013

Fingerprinting With Equiangular Tight Frames.
IEEE Trans. Inf. Theory, 2013

Nonasymptotic Upper Bounds for Deletion Correcting Codes.
IEEE Trans. Inf. Theory, 2013

A Timing Channel Spyware for the CSMA/CA Protocol.
IEEE Trans. Inf. Forensics Secur., 2013

Invisible Flow Watermarks for Channels With Dependent Substitution, Deletion, and Bursty Insertion Errors.
IEEE Trans. Inf. Forensics Secur., 2013

Preventing Timing Analysis in Networks: A Statistical Inference Perspective.
IEEE Signal Process. Mag., 2013

An Information Theoretic Study of Timing Side Channels in Two-user Schedulers.
CoRR, 2013

Optimal bounded-degree approximations of joint distributions of networks of stochastic processes.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

Robust directed tree approximations for networks of stochastic processes.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

Delay optimal policies offer very little privacy.
Proceedings of the IEEE INFOCOM 2013, Turin, Italy, April 14-19, 2013, 2013

Timing side channels for traffic analysis.
Proceedings of the IEEE International Conference on Acoustics, 2013

Optimal adversarial strategies in learning with expert advice.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

2012
Designing Router Scheduling Policies: A Privacy Perspective.
IEEE Trans. Signal Process., 2012

Characterizing the Efficacy of the NRL Network Pump in Mitigating Covert Timing Channels.
IEEE Trans. Inf. Forensics Secur., 2012

Two Approaches to the Construction of Deletion Correcting Codes: Weight Partitioning and Optimal Colorings
CoRR, 2012

Non-asymptotic Upper Bounds for Deletion Correcting Codes
CoRR, 2012

Multi-Flow Attacks Against Network Flow Watermarks: Analysis and Countermeasures
CoRR, 2012

Website Detection Using Remote Traffic Analysis.
Proceedings of the Privacy Enhancing Technologies - 12th International Symposium, 2012

Scheduling with privacy constraints.
Proceedings of the 2012 IEEE Information Theory Workshop, 2012

Learning minimal latent directed information trees.
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

A coloring approach to constructing deletion correcting codes from constant weight subgraphs.
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

Mitigating timing based information leakage in shared schedulers.
Proceedings of the IEEE INFOCOM 2012, Orlando, FL, USA, March 25-30, 2012, 2012

Invisible flow watermarks for channels with dependent substitution and deletion errors.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2011
Estimating the directed information to infer causal relationships in ensemble neural spike train recordings.
J. Comput. Neurosci., 2011

Causal Dependence Tree Approximations of Joint Distributions for Multiple Random Processes
CoRR, 2011

An algorithmic approach for finding deletion correcting codes.
Proceedings of the 2011 IEEE Information Theory Workshop, 2011

Equivalence between minimal generative model graphs and directed information graphs.
Proceedings of the 2011 IEEE International Symposium on Information Theory Proceedings, 2011

Information theoretic analysis of side channel information leakage in FCFS schedulers.
Proceedings of the 2011 IEEE International Symposium on Information Theory Proceedings, 2011

Equiangular tight frame fingerprinting codes.
Proceedings of the IEEE International Conference on Acoustics, 2011

Designing privacy preserving router scheduling policies.
Proceedings of the 45st Annual Conference on Information Sciences and Systems, 2011

Convergence analysis for an online recommendation system.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

A minimal approach to causal inference on topologies with bounded indegree.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

2010
Approximating discrete probability distributions with causal dependence trees.
Proceedings of the International Symposium on Information Theory and its Applications, 2010

Directed information and the NRL Network Pump.
Proceedings of the International Symposium on Information Theory and its Applications, 2010

Low-Cost Side Channel Remote Traffic Analysis Attack in Packet Networks.
Proceedings of IEEE International Conference on Communications, 2010

Fingerprinting websites using remote traffic analysis.
Proceedings of the 17th ACM Conference on Computer and Communications Security, 2010

2009
Regular simplex fingerprints and their optimality properties.
IEEE Trans. Inf. Forensics Secur., 2009

Performance of orthogonal fingerprinting codes under worst-case noise.
IEEE Trans. Inf. Forensics Secur., 2009

RAINBOW: A Robust And Invisible Non-Blind Watermark for Network Flows.
Proceedings of the Network and Distributed System Security Symposium, 2009

Novel Shaping and Complexity-Reduction Techniques for Approaching Capacity over Queuing Timing Channels.
Proceedings of IEEE International Conference on Communications, 2009

Covert timing channels codes for communication over interactive traffic.
Proceedings of the IEEE International Conference on Acoustics, 2009

Multi-flow attack resistant watermarks for network flows.
Proceedings of the IEEE International Conference on Acoustics, 2009

Distributed triangulation in the presence faulty and byzantine beacons in aircraft networks with ADS-B technology.
Proceedings of the American Control Conference, 2009

2008
Multi-flow Attacks Against Network Flow Watermarking Schemes.
Proceedings of the 17th USENIX Security Symposium, 2008

Practical codes for queueing channels: An algebraic, state-space, message-passing approach.
Proceedings of the 2008 IEEE Information Theory Workshop, 2008

Trusted Integrated Circuits: A Nondestructive Hidden Characteristics Extraction Approach.
Proceedings of the Information Hiding, 10th International Workshop, 2008

The Rate-Distortion Function of a Poisson Process with a Queueing Distortion Measure.
Proceedings of the 2008 Data Compression Conference (DCC 2008), 2008

Sparse graph codes and practical decoding algorithms for communicating over packet timings in networks.
Proceedings of the 42nd Annual Conference on Information Sciences and Systems, 2008

2007
Sphere packing lower bound on fingerprinting error probability.
Proceedings of the Security, Steganography, and Watermarking of Multimedia Contents IX, 2007

Anti-Collusion Position Estimation in Wireless Sensor Networks.
Proceedings of the IEEE 4th International Conference on Mobile Adhoc and Sensor Systems, 2007

Expurgated Gaussian Fingerprinting Codes.
Proceedings of the IEEE International Symposium on Information Theory, 2007

Performance of Random Fingerprinting Codes Under Arbitrary Nonlinear Attacks.
Proceedings of the IEEE International Conference on Acoustics, 2007

2006
Information Theoretic Limits for Secure Multimedia and Magnetic Recording
PhD thesis, 2006

On Capacity of a Constrained Two-Dimensional Channel in Presence of Violations.
Proceedings of the Proceedings 2006 IEEE International Symposium on Information Theory, 2006

On Optimal Collusion Strategies for Fingerprinting.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

A Framework for Optimizing Nonlinear Collusion Attacks on Fingerprinting Systems.
Proceedings of the 40th Annual Conference on Information Sciences and Systems, 2006

2005
The Vector Decomposition Problem for Elliptic and Hyperelliptic Curves.
IACR Cryptol. ePrint Arch., 2005

Regular Simplex Fingerprints and Their Optimality Properties.
Proceedings of the Digital Watermarking, 4th International Workshop, 2005

On the minimal pseudo-codewords of codes from finite geometries.
Proceedings of the 2005 IEEE International Symposium on Information Theory, 2005

2004
On the vector decomposition problem for m-torsion points on an elliptic curve.
Proceedings of the 2004 IEEE International Symposium on Information Theory, 2004

2003
Secure smartcardbased fingerprint authentication.
Proceedings of the 2003 ACM SIGMM Workshop on Biometrics Methods and Applications, 2003


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