Hassan Ashtiani
17 papers · 2016–2025 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+4 more ↓ Show less ↑
π£ Hot Topic Early Bird π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (24)
π
Trend Setter
π
Century Club Β· Bronze
π₯
Unstoppable Β· Bronze
ποΈ
Keyword Collector
(65)
Top co-authors
Research topics
Machine Learning
(17)
Optimization & Theory
(14)
Application Areas
(7)
Learning Types
(7)
Core Methods
(6)
Artificial Intelligence
(5)
Mathematics & Optimization
(4)
Bayesian & Probabilistic Β· Artificial Intelligence
(3)
Mathematics
(3)
Security & Privacy
(2)
Core AI
(2)
Differential Privacy
(2)
Deep Learning
(1)
Bayesian & Probabilistic Β· Machine Learning
(1)
Optimization
(1)
Keywords
sample complexity
(10)
differential privacy
(6)
mixture of gaussian
(3)
distribution learning
(3)
total variation distance
(3)
pac learning
(3)
robust learning
(3)
gaussian distribution
(3)
hypothesis selection
(2)
sample compression
(2)
statistical learning
(2)
vc dimension
(2)
density estimation
(2)
gaussian mixture
(2)
gaussian mixture model
(2)
recurrent neural network
(2)
stochastic process
(1)
machine learning
(1)
parameter estimation
(1)
statistical estimation
(1)
Papers
Agnostic Private Density Estimation for GMMs via List Global Stability
ALT 2025
Simplifying Adversarially Robust PAC Learning With Tolerance
COLT 2025
Mixtures of Gaussians are Privately Learnable with a Polynomial Number of Samples
ALT 2024
Sample-Efficient Private Learning of Mixtures of Gaussians
NeurIPS 2024
Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity
COLT 2024
Adversarially Robust Learning with Tolerance
ALT 2023
On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences
NeurIPS 2023
Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models
ICML 2023
Benefits of Additive Noise in Composing Classes with Bounded Capacity
NeurIPS 2022
Private and polynomial time algorithms for learning Gaussians and beyond
COLT 2022
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians
ALT 2021
Privately Learning Mixtures of Axis-Aligned Gaussians
NeurIPS 2021
Black-box Certification and Learning under Adversarial Perturbations
ICML 2020
On the Sample Complexity of Learning Sum-Product Networks
AISTATS 2020
Disentangled behavioural representations
NeurIPS 2019
Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes
NeurIPS 2018
Clustering with Same-Cluster Queries
NeurIPS 2016