Selected Publications

1. Learning DNF through Generalized Fourier Representations

   M. Heidari*, R. Khardon*,
   Conference on Learning Theory (CoLT'25).

2. Toward Physically Realizable Quantum Neural Networks

   M. Heidari, A. Grama, W. Szpankowski,
   Association for the Advancement of Artificial Intelligence (AAAI), 2022.

3. Faithful Simulation of Distributed Quantum Measurements with Applications in Distributed Rate-Distortion Theory

   T. Anwar Atif, M. Heidari, S. Pradhan,
   in IEEE Transactions on Information Theory, 2022.

4. Finding Relevant Information via a Discrete Fourier Expansion

   M. Heidari, J. K. Sreedharan, G. I. Shamir, W. Szpankowski,
   International Conference on Machine Learning (ICML), 2021.

5. A Theoretical Framework for Learning from Quantum Data

   M. Heidari, A. Padakandla, W. Szpankowski,
   IEEE International Symposium on Information Theory (ISIT), 2021.

All Publications

2025

• Quantum natural stochastic pairwise coordinate descent

  M. A. Sohail, M. Heidari, A. Anastasopoulos, S. Pradhan,
  npj Quantum Inf, 2025.

• Learning DNF through Generalized Fourier Representations

  M. Heidari*, R. Khardon*,
  Conference on Learning Theory (CoLT'25).

• Improved Classical Shadow Tomography Using Quantum Computation

  Z. Honjani, M. Heidari,
  IEEE International Symposium on Information Theory Proceedings (ISIT'25).

• Quantum Data Sketches

  Q. Zhang, M. Heidari,
  International Conference on Database Theory (ICDT'25).

2024

• Learning Spectral Properties of Boolean Functions: A Unifying Theme in Quantum Algorithms

  M. Heidari, A. Sabry,
  International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'24).

• On The Reliability Function of Discrete Memoryless Multiple Access Channel with Feedback

  M. Heidari, A. Anastasopoulos, S. Pradhan,
  IEEE Transactions on Information Theory, 2024.

• New Bounds on Quantum Sample Complexity of Measurement Classes

  M. Heidari, W. Szpankowski,
  IEEE International Symposium on Information Theory (ISIT), 2024.

2023

• Expected Worst Case Regret via Stochastic Sequential Covering

  C. Wu, M. Heidari, A. Grama, W. Szpankowski,
  Transactions on Machine Learning Research (TMLR), 2023.

• Regret Bounds for Log-loss via Bayesian Algorithms

  C. Wu, M. Heidari, A. Grama, W. Szpankowski,
  IEEE Transaction on Information Theory, 2023.

• Learning k-qubit Quantum Operators via Pauli Decomposition

  M. Heidari, W. Szpankowski,
  Artificial Intelligence and Statistics, (AISTATS), 2023.

• Agnostic PAC Learning of k-juntas Using L2-Polynomial Regression

  M. Heidari, W. Szpankowski,
  Artificial Intelligence and Statistics, (AISTATS), 2023.

• On Non-Interactive Source Simulation via Fourier Transform

  F. Shirani, M. Heidari,
  Information Theory Workshop (ITW), 2023.

• Mathematical Modeling of Eicosanoid Metabolism in Bone-Marrow Derived Macrophage Cells: Cybernetic Framework Combined with Novel Information Theoretic Approaches,

  L. Aboulmouna, S. Khanum, M. Heidari, R. Raja, S Gupta, M. R. Maurya, A. Grama, S. Subramaniam, and D. Ramkrishna,
  Processes, 2023.

2022

• Precise Regret Bounds for Log-loss via a Truncated Bayesian Algorithm

  C. Wu, M. Heidari, A. Grama, W. Szpankowski,
  Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022.

• Toward Physically Realizable Quantum Neural Networks

  M. Heidari, A. Grama, W. Szpankowski,
  Association for the Advancement of Artificial Intelligence (AAAI), 2022.

• Sufficiently Informative and Relevant Features: An Information-theoretic and Fourier-based Characterization

  M. Heidari, J. K. Sreedharan, G. I. Shamir, W. Szpankowski
  in IEEE Transactions on Information Theory, 2022.

• Faithful Simulation of Distributed Quantum Measurements with Applications in Distributed Rate-Distortion Theory

  T. Anwar Atif, M. Heidari, S. Pradhan,
  in IEEE Transactions on Information Theory, 2022.

• Sequential vs Fixed Design Regrets in Online Learning

  C. Wu, M. Heidari, A. Grama, W. Szpankowski,
  IEEE International Symposium on Information Theory (ISIT), 2022.

• Upper Bounds on the Feedback Error Exponent of Channels with State and Memory

  M. Heidari, A. Anastasopoulos, S. Pradhan,
  IEEE International Symposium on Information Theory (ISIT), 2022.

2021

• Finding Relevant Information via a Discrete Fourier Expansion

  M. Heidari, J. K. Sreedharan, G. I. Shamir, W. Szpankowski,
  International Conference on Machine Learning (ICML), 2021.

• A Theoretical Framework for Learning from Quantum Data

  M. Heidari, A. Padakandla, W. Szpankowski,
  IEEE International Symposium on Information Theory (ISIT), 2021.

• Information Sufficiency via Fourier Expansion

  M. Heidari, J. K. Sreedharan, G. I. Shamir, W. Szpankowski,
  IEEE International Symposium on Information Theory (ISIT), 2021.

2020

• Structured Mappings and Conferencing Common Information for Multiple-Access Channels

  M. Heidari, S. Pradhan,
  in IEEE Transactions on Information Theory, 2020.

2019

• Quasi Structured Codes for Multi-Terminal Communications

  M. Heidari, F. Shirani, S. Pradhan,
  in IEEE Transactions on Information Theory, 2019.

• Faithful Simulation of Distributed Quantum Measurements

  M. Heidari, T. Atif, S. Pradhan,
  IEEE International Symposium on Information Theory (ISIT), 2019.

• Boolean Functions with Biased Inputs: Approximation and Noise Sensitivity

  M. Heidari , R. Venkataramanan, S. Pradhan,
  IEEE International Symposium on Information Theory (ISIT), 2019.

2018 and before

• On The Reliability Function of Discrete Memoryless Multiple-Access Channel with Feedback

  M. Heidari , A. Anastasopoulos, S. Pradhan,
  Information Theory Workshop (ITW), 2018.

• Bounds on the Effective-length of Optimal Codes for Interference Channel with Feedback

  M. Heidari, F. Shirani, S. Pradhan,
  IEEE International Symposium on Information Theory (ISIT), July 2018.

• A New Achievable Rate Region for Multiple Access Channel with States

  M. Heidari, F. Shirani, S. Pradhan,
  IEEE International Symposium on Information Theory (ISIT), July 2017.

• On The Necessity of Structured codes for Communications over MAC with Feedback

  M. Heidari , F. Shirani, S. Pradhan,
  IEEE International Symposium on Information Theory (ISIT), July 2017.

• How to Compute Modulo Prime-Power Sums

  M. Heidari, S. Pradhan,
  IEEE International Symposium on Information Theory (ISIT), Jun 2016.

• New Sufficient Conditions for Multiple-Access Channel with Correlated Sources

  M. Heidari, F. Shirani, S. Pradhan,
  IEEE International Symposium on Information Theory (ISIT), Jun 2016.

• Quasi Linear Codes: Application to Point-to-Point and Multi-Terminal Source Coding

  F. Shirani, M. Heidari , S. Pradhan,
  IEEE International Symposium on Information Theory (ISIT), Jun 2016.

• Beyond Group Capacity in Multi-terminal Communications

  M. Heidari, F. Shirani, S. Pradhan,
  IEEE International Symposium on Information Theory (ISIT), Jun 2015.

• New Lattice Codes For Multiple Descriptions

  F. Shirani, M. Heidari , S. Pradhan,
  IEEE International Symposium on Information Theory (ISIT), Jun 2015.

• Modem based on sphere packing techniques in high-dimensional Euclidean sub-space for efficient data over voice communication through mobile voice channels

  R. Kazemi, M. Boloursaz, M.H. Khoozani, F. Behnia,
  IET Communications 2015, 9, (4), p. 508-516, DOI: 10.1049/iet-com.2014.0610

• Finding Sub-Optimum Signature Matrices for Overloaded Code Division Multiple Access Systems

  M.H. Khoozani, F. Marvasti, E. Azghani, M. Ghassemian,
  IET Communications 2013, 7, (4), p. 295-306, DOI: 10.1049/iet-com.2012.0208.

• Almost-Optimum Signature Matrices in Binary-Input Synchronous Overloaded CDMA

  M. H. Khoozani, A. Rashidinejad, M.H.L Froushani, P. Pad, and F.Marvasti,
  18th IEEE Int. Conf. on Telecommunications (ICT), 2011.

PhD Thesis

• Capacity, Error Exponent, and Structural Results for Communication Networks.