Hassan Ashtiani

40 papers A* 12A 2B 4Journal 20Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	B	`conf`	Agnostic Private Density Estimation for GMMs via List Global Stability. ALT Mohammad Afzali, Hassan Ashtiani, Christopher Liaw
2025	A*	`conf`	Simplifying Adversarially Robust PAC Learning With Tolerance. COLT Hassan Ashtiani, Vinayak Pathak, Ruth Urner
2025	J	`jnl`	Simplifying Adversarially Robust PAC Learning with Tolerance. CoRR Hassan Ashtiani, Vinayak Pathak, Ruth Urner
2024	J	`jnl`	Agnostic Private Density Estimation via Stable List Decoding. CoRR Mohammad Afzali, Hassan Ashtiani, Christopher Liaw
2024	B	`conf`	Mixtures of Gaussians are Privately Learnable with a Polynomial Number of Samples. ALT Mohammad Afzali, Hassan Ashtiani, Christopher Liaw
2024	A*	`conf`	Sample-Efficient Private Learning of Mixtures of Gaussians. NeurIPS Hassan Ashtiani, Mahbod Majid, Shyam Narayanan
2024	J	`jnl`	Sample-Efficient Private Learning of Mixtures of Gaussians. CoRR Hassan Ashtiani, Mahbod Majid, Shyam Narayanan
2024	A*	`conf`	Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity. COLT Alireza Fathollah Pour, Hassan Ashtiani, Shahab Asoodeh
2023	B	`conf`	Adversarially Robust Learning with Tolerance. ALT Hassan Ashtiani, Vinayak Pathak, Ruth Urner
2023	J	`jnl`	Mixtures of Gaussians are Privately Learnable with a Polynomial Number of Samples. CoRR Mohammad Afzali, Hassan Ashtiani, Christopher Liaw
2023	A*	`conf`	On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences. NeurIPS Alireza Fathollah Pour, Hassan Ashtiani
2023	J	`jnl`	On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences. CoRR Alireza Fathollah Pour, Hassan Ashtiani
2023	A*	`conf`	Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models. ICML Jamil Arbas, Hassan Ashtiani, Christopher Liaw
2023	J	`jnl`	Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models. CoRR Jamil Arbas, Hassan Ashtiani, Christopher Liaw
2023	J	`jnl`	Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity. CoRR Alireza Fathollah Pour, Hassan Ashtiani, Shahab Asoodeh
2022	J	`jnl`	Adversarially Robust Learning with Tolerance. CoRR Hassan Ashtiani, Vinayak Pathak, Ruth Urner
2022	A*	`conf`	Benefits of Additive Noise in Composing Classes with Bounded Capacity. NeurIPS Alireza Fathollah Pour, Hassan Ashtiani
2022	J	`jnl`	Benefits of Additive Noise in Composing Classes with Bounded Capacity. CoRR Alireza Fathollah Pour, Hassan Ashtiani
2022	A*	`conf`	Private and polynomial time algorithms for learning Gaussians and beyond. COLT Hassan Ashtiani, Christopher Liaw
2021	B	`conf`	On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians. ALT Ishaq Aden-Ali, Hassan Ashtiani, Gautam Kamath
2021	J	`jnl`	Private and polynomial time algorithms for learning Gaussians and beyond. CoRR Hassan Ashtiani, Christopher Liaw
2021	A*	`conf`	Privately Learning Mixtures of Axis-Aligned Gaussians. NeurIPS Ishaq Aden-Ali, Hassan Ashtiani, Christopher Liaw
2021	J	`jnl`	Privately Learning Mixtures of Axis-Aligned Gaussians. CoRR Ishaq Aden-Ali, Hassan Ashtiani, Christopher Liaw
2020	A*	`conf`	Black-box Certification and Learning under Adversarial Perturbations. ICML Hassan Ashtiani, Vinayak Pathak, Ruth Urner
2020	J	`jnl`	Black-box Certification and Learning under Adversarial Perturbations. CoRR Hassan Ashtiani, Vinayak Pathak, Ruth Urner
2020	J	`jnl`	Near-optimal Sample Complexity Bounds for Robust Learning of Gaussian Mixtures via Compression Schemes. J. ACM Hassan Ashtiani, Shai Ben-David, Nicholas J. A. Harvey, Christopher Liaw, Abbas Mehrabian, Yaniv Plan
2020	A	`conf`	On the Sample Complexity of Learning Sum-Product Networks. AISTATS Ishaq Aden-Ali, Hassan Ashtiani
2020	J	`jnl`	On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians. CoRR Ishaq Aden-Ali, Hassan Ashtiani, Gautam Kamath
2019	A*	`conf`	Disentangled behavioural representations. NeurIPS Amir Dezfouli, Hassan Ashtiani, Omar Ghattas, Richard Nock, Peter Dayan, Cheng Soon Ong
2019	J	`jnl`	On the Sample Complexity of Learning Sum-Product Networks. CoRR Ishaq Aden-Ali, Hassan Ashtiani
2018	A*	`conf`	Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes. NeurIPS Hassan Ashtiani, Shai Ben-David, Nicholas J. A. Harvey, Christopher Liaw, Abbas Mehrabian, Yaniv Plan
2018	A*	`conf`	Sample-Efficient Learning of Mixtures. AAAI Hassan Ashtiani, Shai Ben-David, Abbas Mehrabian
2018	J	`jnl`	Some techniques in density estimation. CoRR Hassan Ashtiani, Abbas Mehrabian
2017	J	`jnl`	Agnostic Distribution Learning via Compression. CoRR Hassan Ashtiani, Shai Ben-David, Abbas Mehrabian
2017	J	`jnl`	Sample-Efficient Learning of Mixtures. CoRR Hassan Ashtiani, Shai Ben-David, Abbas Mehrabian
2016	—	`conf`	Clustering with Same-Cluster Queries. NIPS Hassan Ashtiani, Shrinu Kushagra, Shai Ben-David
2016	J	`jnl`	Clustering with Same-Cluster Queries. CoRR Hassan Ashtiani, Shrinu Kushagra, Shai Ben-David
2015	—	`conf`	A Dimension-Independent Generalization Bound for Kernel Supervised Principal Component Analysis. FE@NIPS Hassan Ashtiani, Ali Ghodsi
2015	A	`conf`	Representation Learning for Clustering: A Statistical Framework. UAI Hassan Ashtiani, Shai Ben-David
2015	J	`jnl`	Representation Learning for Clustering: A Statistical Framework. CoRR Hassan Ashtiani, Shai Ben-David