Hassan Ashtiani

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 32

Top Topics

Density Estimation

Gaussian Mixture

Top Venues

Publications

Alireza Fathollah Pour, Hassan Ashtiani, Shahab Asoodeh
Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity. COLT (2024)
Mohammad Afzali, Hassan Ashtiani, Christopher Liaw
Agnostic Private Density Estimation via Stable List Decoding. CoRR (2024)
Mohammad Afzali, Hassan Ashtiani, Christopher Liaw
Mixtures of Gaussians are Privately Learnable with a Polynomial Number of Samples. ALT (2024)
Alireza Fathollah Pour, Hassan Ashtiani, Shahab Asoodeh
Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity. CoRR (2023)
Jamil Arbas, Hassan Ashtiani, Christopher Liaw
Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models. ICML (2023)
Hassan Ashtiani, Vinayak Pathak, Ruth Urner
Adversarially Robust Learning with Tolerance. ALT (2023)
Mohammad Afzali, Hassan Ashtiani, Christopher Liaw
Mixtures of Gaussians are Privately Learnable with a Polynomial Number of Samples. CoRR (2023)
Jamil Arbas, Hassan Ashtiani, Christopher Liaw
Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models. CoRR (2023)
Alireza Fathollah Pour, Hassan Ashtiani
On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences. NeurIPS (2023)
Alireza Fathollah Pour, Hassan Ashtiani
On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences. CoRR (2023)
Hassan Ashtiani, Vinayak Pathak, Ruth Urner
Adversarially Robust Learning with Tolerance. CoRR (2022)
Hassan Ashtiani, Christopher Liaw
Private and polynomial time algorithms for learning Gaussians and beyond. COLT (2022)
Alireza Fathollah Pour, Hassan Ashtiani
Benefits of Additive Noise in Composing Classes with Bounded Capacity. NeurIPS (2022)
Alireza Fathollah Pour, Hassan Ashtiani
Benefits of Additive Noise in Composing Classes with Bounded Capacity. CoRR (2022)
Ishaq Aden-Ali, Hassan Ashtiani, Christopher Liaw
Privately Learning Mixtures of Axis-Aligned Gaussians. CoRR (2021)
Ishaq Aden-Ali, Hassan Ashtiani, Gautam Kamath
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians. ALT (2021)
Hassan Ashtiani, Christopher Liaw
Private and polynomial time algorithms for learning Gaussians and beyond. CoRR (2021)
Ishaq Aden-Ali, Hassan Ashtiani, Christopher Liaw
Privately Learning Mixtures of Axis-Aligned Gaussians. NeurIPS (2021)
Hassan Ashtiani, Vinayak Pathak, Ruth Urner
Black-box Certification and Learning under Adversarial Perturbations. CoRR (2020)
Ishaq Aden-Ali, Hassan Ashtiani
On the Sample Complexity of Learning Sum-Product Networks. AISTATS (2020)
Hassan Ashtiani, Vinayak Pathak, Ruth Urner
Black-box Certification and Learning under Adversarial Perturbations. ICML (2020)
Hassan Ashtiani, Shai Ben-David, Nicholas J. A. Harvey, Christopher Liaw, Abbas Mehrabian, Yaniv Plan
Near-optimal Sample Complexity Bounds for Robust Learning of Gaussian Mixtures via Compression Schemes. J. ACM 67 (6) (2020)
Ishaq Aden-Ali, Hassan Ashtiani, Gautam Kamath
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians. CoRR (2020)
Ishaq Aden-Ali, Hassan Ashtiani
On the Sample Complexity of Learning Sum-Product Networks. CoRR (2019)
Amir Dezfouli, Hassan Ashtiani, Omar Ghattas, Richard Nock, Peter Dayan, Cheng Soon Ong
Disentangled behavioural representations. NeurIPS (2019)
Hassan Ashtiani, Shai Ben-David, Abbas Mehrabian
Sample-Efficient Learning of Mixtures. AAAI (2018)
Hassan Ashtiani, Abbas Mehrabian
Some techniques in density estimation. CoRR (2018)
Hassan Ashtiani, Shai Ben-David, Nicholas J. A. Harvey, Christopher Liaw, Abbas Mehrabian, Yaniv Plan
Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes. NeurIPS (2018)
Hassan Ashtiani, Shai Ben-David, Abbas Mehrabian
Sample-Efficient Learning of Mixtures. CoRR (2017)
Hassan Ashtiani, Shai Ben-David, Abbas Mehrabian
Agnostic Distribution Learning via Compression. CoRR (2017)
Hassan Ashtiani, Shrinu Kushagra, Shai Ben-David
Clustering with Same-Cluster Queries. NIPS (2016)
Hassan Ashtiani, Shrinu Kushagra, Shai Ben-David
Clustering with Same-Cluster Queries. CoRR (2016)
Hassan Ashtiani, Shai Ben-David
Representation Learning for Clustering: A Statistical Framework. CoRR (2015)
Hassan Ashtiani, Shai Ben-David
Representation Learning for Clustering: A Statistical Framework. UAI (2015)
Hassan Ashtiani, Ali Ghodsi
A Dimension-Independent Generalization Bound for Kernel Supervised Principal Component Analysis. FE@NIPS (2015)