Saeed Mahloujifar
22 papers · 2018–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π Conference Polyglot (6) π§ Keyword Pioneer π Interdisciplinary Bridge π Academic Marathon (7)
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Cross-Pollinator
(12)
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Renaissance Researcher
(6)
πΊοΈ
Taxonomy Completionist
(29)
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Triple Crown
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Grand Slam
π€
Dynamic Duo
(10)
π¬
Deep Specialist
(13)
ποΈ
Keyword Collector
(80)
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The Questioner
(2)
β‘
Prolific Year
(6)
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Conference Pioneer
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Trend Setter
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Century Club
(22)
π₯
Unstoppable
(8)
Conferences
NIPS (8)
ICML (7)
ALT (3)
ICLR (2)
AAAI (1)
AISTATS (1)
Top co-authors
Research topics
Keywords
poisoning attack
(6)
adversarial learning
(5)
adversarial robustness
(5)
adversarial attack
(5)
differential privacy
(3)
federated learning
(2)
robust classification
(2)
evasion attack
(2)
adversarial example
(2)
learning theory
(2)
gradient clipping
(2)
privacy-preserving machine learning
(2)
computational hardness
(2)
convex optimization
(1)
domain adaptation
(1)
stochastic gradient descent
(1)
domain generalization
(1)
data poisoning
(1)
image classification
(1)
pac learning
(1)
Papers
Auditing $f$-differential privacy in one run
ICML 2025
A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization
ICML 2024
Revisiting the Assumption of Latent Separability for Backdoor Defenses
ICLR 2023
Effectively Using Public Data in Privacy Preserving Machine Learning
ICML 2023
A Randomized Approach to Tight Privacy Accounting
NIPS 2023
MultiRobustBench: Benchmarking Robustness Against Multiple Attacks
ICML 2023
Bounding training data reconstruction in DP-SGD
NIPS 2023
Uncovering Adversarial Risks of Test-Time Adaptation
ICML 2023
Formulating Robustness Against Unforeseen Attacks
NIPS 2022
Overparameterization from Computational Constraints
NIPS 2022
Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning
NIPS 2022
SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification
AISTATS 2022
Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?
ICLR 2022
A Separation Result Between Data-oblivious and Data-aware Poisoning Attacks
NIPS 2021
Model-Targeted Poisoning Attacks with Provable Convergence
ICML 2021
Adversarially Robust Learning Could Leverage Computational Hardness.
ALT 2020
Can Adversarially Robust Learning LeverageComputational Hardness?
ALT 2019
Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness
NIPS 2019
The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure
AAAI 2019
Universal Multi-Party Poisoning Attacks
ICML 2019
Adversarial Risk and Robustness: General Definitions and Implications for the Uniform Distribution
NIPS 2018
Learning under $p$-Tampering Attacks
ALT 2018