Publications [Google Scholar]

* equal contribution authors; otherwise, the order is based on contribution unless authors are listed in alphabetical order (noted explicitly).

Papers

• The Distillation Game in LLMs: Adaptive Attacks & Efficient Defenses
  Y. Allouah*, M. Haghifam*, R. Shokri, S. Koyejo
  Submitted, 2026
  Code

• Adaptive Generate-and-Verify: Inference-Time Search with Costly Verification
  S. Dughmi, M. Haghifam, Y.H. Kalayci (authors listed in alphabetic order)
  Under Submission, 2026
  Code

• Black-Box Data Reconstruction via List Decoding: The Necessity of List Memorization for Learning
  G. Brown, M. Haghifam, E. Linder, R. Livni, G. Thampakkul, N. Weinberger (authors listed in alphabetic order)
  Forthcoming, 2026

• The Sample Complexity of Membership Inference and Privacy Auditing
  M. Haghifam, A. Smith, J. Ullman (authors listed in alphabetic order)
  Pre-print, 2025

• On Traceability in Stochastic Convex Optimization
  S. Voitovych*, M. Haghifam*, I. Attias, G. K. Dziugaite, R. Livni, D. M. Roy
  Advances in Neural Information Processing Systems (NeurIPS), 2025 (Spotlight, <3% of submissions)

• Private Geometric Median
  M. Haghifam, T. Steinke, J. Ullman (authors listed in alphabetic order)
  Advances in Neural Information Processing Systems (NeurIPS), 2024
  Talk Code

• Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization
  I. Attias, G. K. Dziugaite, M. Haghifam, R. Livni, D. M. Roy (authors listed in alphabetic order)
  International Conference on Machine Learning (ICML), 2024 (Oral, Best Paper Award: Top 10 of 10,000 submissions)
  Talk

• Faster Differentially Private Convex Optimization via Second-Order Methods
  A. Ganesh, M. Haghifam, T. Steinke, A. Thakurta (authors listed in alphabetic order)
  Advances in Neural Information Processing Systems (NeurIPS), 2023
  Code

• Why Is Public Pretraining Necessary for Private Model Training?
  A. Ganesh, M. Haghifam, M. Nasr, S. Oh, T. Steinke, O. Thakkar, A. Thakurta, L. Wang (authors listed in alphabetic order)
  International Conference on Machine Learning (ICML), 2023

• Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization
  M. Haghifam*, B. Rodriguez-Galvez*, R. Thobaben, M. Skoglund, D. M. Roy, G. K. Dziugaite
  International Conference on Algorithmic Learning Theory (ALT), 2023

• Privacy-Preserving and Approximately Truthful Local Electricity Markets: A Differentially Private VCG Mechanism
  M. Hoseinpour, M. Hoseinpour, M. Haghifam, M. R. Haghifam
  IEEE Transactions on Smart Grid, 2023

• Understanding Generalization via Leave-One-Out Conditional Mutual Information
  M. Haghifam, S. Moran, D. M. Roy, G. K. Dziugaite
  International Symposium on Information Theory (ISIT), 2022

• Towards a Unified Information–Theoretic Framework for Generalization
  M. Haghifam, G. K. Dziugaite, S. Moran, D. M. Roy
  Advances in Neural Information Processing Systems (NeurIPS), 2021 (Spotlight, <3% of submissions)
  Talk

• On Streaming Codes With Unequal Error Protection
  M. Haghifam*, M. N. Krishnan*, A. Khisti, X. Zhu, W. Dan, J. Apostolopoulos
  IEEE Journal on Selected Areas in Information Theory, 2021

• Information-Theoretic Generalization Bounds for Stochastic Gradient Descent
  G. Neu, G. K. Dziugaite*, M. Haghifam*, D. M. Roy*
  Annual Conference on Learning Theory (COLT), 2021

• Sequential Classification with Empirically Observed Statistics
  M. Haghifam, V. Y. F. Tan, A. Khisti
  IEEE Transactions on Information Theory, 2021

• Sharpened Generalization Bounds based on Conditional Mutual Information and an Application to Noisy, Iterative Algorithms
  M. Haghifam, J. Negrea, A. Khisti, D. M. Roy, G. K. Dziugaite
  Advances in Neural Information Processing Systems (NeurIPS), 2020
  Talk Code

• Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates
  J. Negrea*, M. Haghifam*, G. K. Dziugaite, A. Khisti, D. M. Roy
  Advances in Neural Information Processing Systems (NeurIPS), 2019
  Code

• Joint Sum Rate And Error Probability Optimization: Finite Blocklength Analysis
  M. Haghifam, M. Robat Mili, B. Makki, M. Nasiri-Kenari, T. Svensson
  IEEE Wireless Communications Letters, 2017

Workshop Papers

• Differential Privacy with MedMNIST
  L. Zhang, S. Allin, M. Haghifam, M. Pawliuk, R. Engineer, F. Shkurti
  15th Symposium on Educational Advances in Artificial Intelligence (teaching paper based on the design of course material on DP)

• Sequential Classification with Empirically Observed Statistics
  M. Haghifam, V. Y. F. Tan, and A. Khisti
  IEEE Information Theory Workshop, 2019

• Streaming Codes with Unequal Error Protection against Burst Losses
  M. Haghifam, A. Badr, A. Khisti, X. Zhu, W. Dan, J. Apostolopoulos
  The 29th Biennial Symposium on Communications, 2018

• On joint information and energy transfer in relay networks with an imperfect power amplifier
  M. Haghifam, B. Makki, M. Nasiri-Kenari, T. Svensson
  IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), 2016

• State estimation in electric distribution networks in presence of distributed generation using the PMUs
  M. Haghifam, M. R. Haghifam, B. Safari Chabook
  CIRED 2012