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Alireza F. Pour
PhD student, University of Waterloo
Joined
September 2021
Names
Alireza F. Pour
(Preferred)
,
Alireza Fathollah Pour
Emails
****@gmail.com
(Confirmed)
,
****@mcmaster.ca
(Confirmed)
,
****@uwaterloo.ca
(Confirmed)
Personal Links
Google Scholar
DBLP
LinkedIn
Career & Education History
PhD student
University of Waterloo
(uwaterloo.ca)
2023
–
Present
Researcher
McMaster University
(mcmaster.ca)
2022
–
2023
MS student
McMaster University
(mcmaster.ca)
2021
–
2022
Bachelor of Science Student
Amirkabir University of Technology
(aut.ac.ir)
2014
–
2019
Advisors, Relations & Conflicts
No relations added
Expertise
Differential Privacy
2022
–
Present
Generalization in Deep Learning
2021
–
Present
Sample complexity of learning algorithms
2021
–
Present
Statistical learning theory
2021
–
Present
Learning theory
2021
–
Present
Recurrent Neural Networks(RNNs)
2019
–
Present
Deep Learning
2018
–
Present
Publications
A Novel Data-Dependent Learning Paradigm for Large Hypothesis Classes
Alireza F. Pour
,
Shai Ben-David
ALT 2026
Readers:
Everyone
Query-Efficient Locally Private Hypothesis Selection via the Scheffe Graph
Gautam Kamath
,
Alireza F. Pour
,
Matthew Regehr
,
David Woodruff
NeurIPS 2025 poster
Readers:
Everyone
Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity
Alireza Fathollah Pour
,
Hassan Ashtiani
,
Shahab Asoodeh
COLT 2024
Readers:
Everyone
On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences
Alireza Fathollah Pour
,
Hassan Ashtiani
NeurIPS 2023 poster
Readers:
Everyone
Benefits of Additive Noise in Composing Classes with Bounded Capacity
Alireza Fathollah Pour
,
Hassan Ashtiani
Published: 31 Oct 2022, Last Modified: 08 Feb 2026
NeurIPS 2022 Accept
Readers:
Everyone
Co-Authors
David Woodruff
Gautam Kamath
Hassan Ashtiani
Matthew Regehr
Shahab Asoodeh
Shai Ben-David