Amin Karbasi - RankMe

263 papers A* 75A 18B 8Misc 4Journal 136Unranked 21

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Llama-3.1-FoundationAI-SecurityLLM-Reasoning-8B Technical Report. CoRR Zhuoran Yang, Ed Li, Jianliang He, Aman Priyanshu, Baturay Saglam, Paul Kassianik, Sajana Weerawardhena, Anu Vellore, Blaine Nelson, Neusha Javidnia, Arthur Goldblatt, Fraser Burch, Avi Zohary, Assaf Eisenman, Mahdi Sabbaghi, Supriti Vijay, Rahim Dharssi, Dhruv Kedia, Kojin Oshiba, Yaron Singer, Amin Karbasi
2025	J	`jnl`	(Im)possibility of Automated Hallucination Detection in Large Language Models. CoRR Amin Karbasi, Omar Montasser, John Sous, Grigoris Velegkas
2025	J	`jnl`	A Flow-based Truncated Denoising Diffusion Model for super-resolution Magnetic Resonance Spectroscopic Imaging. Medical Image Anal. Siyuan Dong, Zhuotong Cai, Gilbert Hangel, Wolfgang Bogner, Georg Widhalm, Yaqing Huang, Qinghao Liang, Chenyu You, Chathura Kumaragamage, Robert K. Fulbright, Amit Mahajan, Amin Karbasi, John A. Onofrey, Robin A. de Graaf, James S. Duncan
2025	A*	`conf`	Adversarial Reasoning at Jailbreaking Time. ICML Mahdi Sabbaghi, Paul Kassianik, George J. Pappas, Amin Karbasi, Hamed Hassani
2025	J	`jnl`	Adversarial Reasoning at Jailbreaking Time. CoRR Mahdi Sabbaghi, Paul Kassianik, George J. Pappas, Yaron Singer, Amin Karbasi, Hamed Hassani
2025	J	`jnl`	Gödel Test: Can Large Language Models Solve Easy Conjectures? CoRR Moran Feldman, Amin Karbasi
2025	A*	`conf`	Intelligence at the Edge of Chaos. ICLR Shiyang Zhang, Aakash Patel, Syed Asad Rizvi, Nianchen Liu, Sizhuang He, Amin Karbasi, Emanuele Zappala, David van Dijk
2025	—	`conf`	Large Language Models Encode Semantics and Alignment in Linearly Separable Representations. IJCNLP-AACL (long papers) Baturay Saglam, Paul Kassianik, Blaine Nelson, Sajana Weerawardhena, Yaron Singer, Amin Karbasi
2025	J	`jnl`	Large Language Models Encode Semantics in Low-Dimensional Linear Subspaces. CoRR Baturay Saglam, Paul Kassianik, Blaine Nelson, Sajana Weerawardhena, Yaron Singer, Amin Karbasi
2025	J	`jnl`	LatentBreak: Jailbreaking Large Language Models through Latent Space Feedback. CoRR Raffaele Mura, Giorgio Piras, Kamile Lukosiute, Maura Pintor, Amin Karbasi, Battista Biggio
2025	—	`conf`	Learning Task Representations from In-Context Learning. ACL (Findings) Baturay Saglam, Xinyang Hu, Zhuoran Yang, Dionysis Kalogerias, Amin Karbasi
2025	J	`jnl`	Learning Task Representations from In-Context Learning. CoRR Baturay Saglam, Zhuoran Yang, Dionysis Kalogerias, Amin Karbasi
2025	J	`jnl`	Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report. CoRR Sajana Weerawardhena, Paul Kassianik, Blaine Nelson, Baturay Saglam, Anu Vellore, Aman Priyanshu, Supriti Vijay, Massimo Aufiero, Arthur Goldblatt, Fraser Burch, Ed Li, Jianliang He, Dhruv Kedia, Kojin Oshiba, Zhouran Yang, Yaron Singer, Amin Karbasi
2025	J	`jnl`	Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report. CoRR Paul Kassianik, Baturay Saglam, Alexander Chen, Blaine Nelson, Anu Vellore, Massimo Aufiero, Fraser Burch, Dhruv Kedia, Avi Zohary, Sajana Weerawardhena, Aman Priyanshu, Adam Swanda, Amy Chang, Hyrum S. Anderson, Kojin Oshiba, Omar Santos, Yaron Singer, Amin Karbasi
2025	J	`jnl`	On Union-Closedness of Language Generation. CoRR Steve Hanneke, Amin Karbasi, Anay Mehrotra, Grigoris Velegkas
2025	J	`jnl`	PolarQuant: Quantizing KV Caches with Polar Transformation. CoRR Insu Han, Praneeth Kacham, Amin Karbasi, Vahab Mirrokni, Amir Zandieh
2025	A*	`conf`	Procurement Auctions via Approximately Optimal Submodular Optimization. ICML Yuan Deng, Amin Karbasi, Vahab Mirrokni, Renato Paes Leme, Grigoris Velegkas, Song Zuo
2025	J	`jnl`	Risk-Averse Constrained Reinforcement Learning with Optimized Certainty Equivalents. CoRR Jane H. Lee, Baturay Saglam, Spyridon Pougkakiotis, Amin Karbasi, Dionysis Kalogerias
2025	J	`jnl`	Select without Fear: Almost All Minibatch Schedules Generalize Optimally. SIAM J. Math. Data Sci. Konstantinos E. Nikolakakis, Amin Karbasi, Dionysis Kalogerias
2025	J	`jnl`	Think Before You Retrieve: Learning Test-Time Adaptive Search with Small Language Models. CoRR Supriti Vijay, Aman Priyanshu, Anu Vellore, Baturay Saglam, Amin Karbasi
2024	J	`jnl`	A Flow-based Truncated Denoising Diffusion Model for Super-resolution Magnetic Resonance Spectroscopic Imaging. CoRR Siyuan Dong, Zhuotong Cai, Gilbert Hangel, Wolfgang Bogner, Georg Widhalm, Yaqing Huang, Qinghao Liang, Chenyu You, Chathura Kumaragamage, Robert K. Fulbright, Amit Mahajan, Amin Karbasi, John A. Onofrey, Robin A. de Graaf, James S. Duncan
2024	A*	`conf`	Cell2Sentence: Teaching Large Language Models the Language of Biology. ICML Daniel LeVine, Syed Asad Rizvi, Sacha Lévy, Nazreen Pallikkavaliyaveetil, David Zhang, Xingyu Chen, Sina Ghadermarzi, Ruiming Wu, Zihe Zheng, Ivan Vrkic, Anna Zhong, Daphne Raskin, Insu Han, Antonio Henrique de Oliveira Fonseca, Josue Ortega Caro, Amin Karbasi, Rahul Madhav Dhodapkar, David van Dijk
2024	J	`jnl`	Cognitive Overload Attack:Prompt Injection for Long Context. CoRR Bibek Upadhayay, Vahid Behzadan, Amin Karbasi
2024	J	`jnl`	Criteria and Bias of Parameterized Linear Regression under Edge of Stability Regime. CoRR Peiyuan Zhang, Amin Karbasi
2024	J	`jnl`	Extracting Memorized Training Data via Decomposition. CoRR Ellen Su, Anu Vellore, Amy Chang, Raffaele Mura, Blaine Nelson, Paul Kassianik, Amin Karbasi
2024	A*	`conf`	HyperAttention: Long-context Attention in Near-Linear Time. ICLR Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh
2024	J	`jnl`	Injecting Undetectable Backdoors in Deep Learning and Language Models. CoRR Alkis Kalavasis, Amin Karbasi, Argyris Oikonomou, Katerina Sotiraki, Grigoris Velegkas, Manolis Zampetakis
2024	A*	`conf`	Injecting Undetectable Backdoors in Obfuscated Neural Networks and Language Models. NeurIPS Alkis Kalavasis, Amin Karbasi, Argyris Oikonomou, Katerina Sotiraki, Grigoris Velegkas, Manolis Zampetakis
2024	J	`jnl`	Intelligence at the Edge of Chaos. CoRR Shiyang Zhang, Aakash Patel, Syed Asad Rizvi, Nianchen Liu, Sizhuang He, Amin Karbasi, Emanuele Zappala, David van Dijk
2024	A*	`conf`	On the Computational Landscape of Replicable Learning. NeurIPS Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas, Felix Zhou
2024	J	`jnl`	On the Computational Landscape of Replicable Learning. CoRR Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas, Felix Zhou
2024	J	`jnl`	Procurement Auctions via Approximately Optimal Submodular Optimization. CoRR Yuan Deng, Amin Karbasi, Vahab Mirrokni, Renato Paes Leme, Grigoris Velegkas, Song Zuo
2024	A*	`conf`	Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning. ICLR Patrik Okanovic, Roger Waleffe, Vasilis Mageirakos, Konstantinos E. Nikolakakis, Amin Karbasi, Dionysios S. Kalogerias, Nezihe Merve Gürel, Theodoros Rekatsinas
2024	A*	`conf`	Replicable Learning of Large-Margin Halfspaces. ICML Alkis Kalavasis, Amin Karbasi, Kasper Green Larsen, Grigoris Velegkas, Felix Zhou
2024	J	`jnl`	Replicable Learning of Large-Margin Halfspaces. CoRR Alkis Kalavasis, Amin Karbasi, Kasper Green Larsen, Grigoris Velegkas, Felix Zhou
2024	J	`jnl`	SubGen: Token Generation in Sublinear Time and Memory. CoRR Amir Zandieh, Insu Han, Vahab Mirrokni, Amin Karbasi
2024	A	`conf`	Submodular Minimax Optimization: Finding Effective Sets. AISTATS Loay Raed Mualem, Ethan R. Elenberg, Moran Feldman, Amin Karbasi
2024	A*	`conf`	TSDS: Data Selection for Task-Specific Model Finetuning. NeurIPS Zifan Liu, Amin Karbasi, Theodoros Rekatsinas
2024	J	`jnl`	TSDS: Data Selection for Task-Specific Model Finetuning. CoRR Zifan Liu, Amin Karbasi, Theodoros Rekatsinas
2024	B	`conf`	The Impossibility of Parallelizing Boosting. ALT Amin Karbasi, Kasper Green Larsen
2024	A*	`conf`	Tree of Attacks: Jailbreaking Black-Box LLMs Automatically. NeurIPS Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, Blaine Nelson, Hyrum S. Anderson, Yaron Singer, Amin Karbasi
2024	A*	`conf`	Universal Rates for Active Learning. NeurIPS Steve Hanneke, Amin Karbasi, Shay Moran, Grigoris Velegkas
2024	A*	`conf`	Universal Rates for Regression: Separations between Cut-Off and Absolute Loss. COLT Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas
2023	A*	`conf`	Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD. ICLR Konstantinos E. Nikolakakis, Farzin Haddadpour, Amin Karbasi, Dionysios S. Kalogerias
2023	J	`jnl`	Cross Atlas Remapping via Optimal Transport (CAROT): Creating connectomes for different atlases when raw data is not available. Medical Image Anal. Javid Dadashkarimi, Amin Karbasi, Qinghao Liang, Matthew Rosenblatt, Stephanie Noble, Maya Foster, Raimundo X. Rodriguez, Brendan Adkinson, Jean Ye, Huili Sun, Chris Camp, Michael Farruggia, Link Tejavibulya, Wei Dai, Rongtao Jiang, Angeliki Pollatou, Dustin Scheinost
2023	A	`conf`	Exact Gradient Computation for Spiking Neural Networks via Forward Propagation. AISTATS Jane H. Lee, Saeid Haghighatshoar, Amin Karbasi
2023	J	`jnl`	How Do You Want Your Greedy: Simultaneous or Repeated? J. Mach. Learn. Res. Moran Feldman, Christopher Harshaw, Amin Karbasi
2023	J	`jnl`	HyperAttention: Long-context Attention in Near-Linear Time. CoRR Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh
2023	A*	`conf`	KDEformer: Accelerating Transformers via Kernel Density Estimation. ICML Amir Zandieh, Insu Han, Majid Daliri, Amin Karbasi
2023	J	`jnl`	KDEformer: Accelerating Transformers via Kernel Density Estimation. CoRR Amir Zandieh, Insu Han, Majid Daliri, Amin Karbasi
2023	A*	`conf`	Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning. ICML Amin Karbasi, Nikki Lijing Kuang, Yi-An Ma, Siddharth Mitra
2023	J	`jnl`	Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning. CoRR Amin Karbasi, Nikki Lijing Kuang, Yi-An Ma, Siddharth Mitra
2023	J	`jnl`	Learning from Aggregated Data: Curated Bags versus Random Bags. CoRR Lin Chen, Gang Fu, Amin Karbasi, Vahab Mirrokni
2023	A*	`conf`	Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization. NeurIPS Liang Zhang, Junchi Yang, Amin Karbasi, Niao He
2023	J	`jnl`	Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization. CoRR Liang Zhang, Junchi Yang, Amin Karbasi, Niao He
2023	A*	`conf`	Optimal Learners for Realizable Regression: PAC Learning and Online Learning. NeurIPS Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas
2023	J	`jnl`	Optimal Learners for Realizable Regression: PAC Learning and Online Learning. CoRR Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas
2023	J	`jnl`	Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning. CoRR Patrik Okanovic, Roger Waleffe, Vasilis Mageirakos, Konstantinos E. Nikolakakis, Amin Karbasi, Dionysios S. Kalogerias, Nezihe Merve Gürel, Theodoros Rekatsinas
2023	A*	`conf`	Replicability in Reinforcement Learning. NeurIPS Amin Karbasi, Grigoris Velegkas, Lin Yang, Felix Zhou
2023	J	`jnl`	Replicability in Reinforcement Learning. CoRR Amin Karbasi, Grigoris Velegkas, Lin F. Yang, Felix Zhou
2023	A*	`conf`	Replicable Bandits. ICLR Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni, Grigoris Velegkas
2023	A*	`conf`	Replicable Clustering. NeurIPS Hossein Esfandiari, Amin Karbasi, Vahab Mirrokni, Grigoris Velegkas, Felix Zhou
2023	J	`jnl`	Replicable Clustering. CoRR Hossein Esfandiari, Amin Karbasi, Vahab Mirrokni, Grigoris Velegkas, Felix Zhou
2023	J	`jnl`	Select without Fear: Almost All Mini-Batch Schedules Generalize Optimally. CoRR Konstantinos E. Nikolakakis, Amin Karbasi, Dionysis Kalogerias
2023	Misc	`conf`	Stacking multiple optimal transport policies to map functional connectomes. CISS Javid Dadashkarimi, Matthew Rosenblatt, Amin Karbasi, Dustin Scheinost
2023	A*	`conf`	Statistical Indistinguishability of Learning Algorithms. ICML Alkis Kalavasis, Amin Karbasi, Shay Moran, Grigoris Velegkas
2023	J	`jnl`	Statistical Indistinguishability of Learning Algorithms. CoRR Alkis Kalavasis, Amin Karbasi, Shay Moran, Grigoris Velegkas
2023	J	`jnl`	Submodular Minimax Optimization: Finding Effective Sets. CoRR Loay Mualem, Ethan R. Elenberg, Moran Feldman, Amin Karbasi
2023	J	`jnl`	The Impossibility of Parallelizing Boosting. CoRR Amin Karbasi, Kasper Green Larsen
2023	J	`jnl`	Tree of Attacks: Jailbreaking Black-Box LLMs Automatically. CoRR Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, Blaine Nelson, Hyrum S. Anderson, Yaron Singer, Amin Karbasi
2022	J	`jnl`	Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD. CoRR Konstantinos E. Nikolakakis, Farzin Haddadpour, Amin Karbasi, Dionysios S. Kalogerias
2022	J	`jnl`	Black-Box Generalization. CoRR Konstantinos E. Nikolakakis, Farzin Haddadpour, Dionysios S. Kalogerias, Amin Karbasi
2022	A*	`conf`	Black-Box Generalization: Stability of Zeroth-Order Learning. NeurIPS Konstantinos E. Nikolakakis, Farzin Haddadpour, Dionysios S. Kalogerias, Amin Karbasi
2022	—	`conf`	Combining Multiple Atlases to Estimate Data-Driven Mappings Between Functional Connectomes Using Optimal Transport. MICCAI (1) Javid Dadashkarimi, Amin Karbasi, Dustin Scheinost
2022	J	`jnl`	Exact Gradient Computation for Spiking Neural Networks Through Forward Propagation. CoRR Jane H. Lee, Saeid Haghighatshoar, Amin Karbasi
2022	A*	`conf`	Fast Neural Kernel Embeddings for General Activations. NeurIPS Insu Han, Amir Zandieh, Jaehoon Lee, Roman Novak, Lechao Xiao, Amin Karbasi
2022	J	`jnl`	Fast Neural Kernel Embeddings for General Activations. CoRR Insu Han, Amir Zandieh, Jaehoon Lee, Roman Novak, Lechao Xiao, Amin Karbasi
2022	A	`conf`	Federated Functional Gradient Boosting. AISTATS Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi
2022	A*	`conf`	Learning Distributionally Robust Models at Scale via Composite Optimization. ICLR Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Amin Karbasi
2022	J	`jnl`	Learning Distributionally Robust Models at Scale via Composite Optimization. CoRR Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Amin Karbasi
2022	A*	`conf`	Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes. NeurIPS Alkis Kalavasis, Grigoris Velegkas, Amin Karbasi
2022	J	`jnl`	Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes. CoRR Alkis Kalavasis, Grigoris Velegkas, Amin Karbasi
2022	A*	`conf`	On Optimal Learning Under Targeted Data Poisoning. NeurIPS Steve Hanneke, Amin Karbasi, Mohammad Mahmoody, Idan Mehalel, Shay Moran
2022	J	`jnl`	On Optimal Learning Under Targeted Data Poisoning. CoRR Steve Hanneke, Amin Karbasi, Mohammad Mahmoody, Idan Mehalel, Shay Moran
2022	A*	`conf`	Reinforcement Learning with Logarithmic Regret and Policy Switches. NeurIPS Grigoris Velegkas, Zhuoran Yang, Amin Karbasi
2022	J	`jnl`	Reproducible Bandits. CoRR Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni, Grigoris Velegkas
2022	A*	`conf`	Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes. ICML Insu Han, Mike Gartrell, Elvis Dohmatob, Amin Karbasi
2022	J	`jnl`	Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes. CoRR Insu Han, Mike Gartrell, Elvis Dohmatob, Amin Karbasi
2022	A*	`conf`	Scalable Sampling for Nonsymmetric Determinantal Point Processes. ICLR Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, Amin Karbasi
2022	J	`jnl`	Scalable Sampling for Nonsymmetric Determinantal Point Processes. CoRR Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, Amin Karbasi
2022	A*	`conf`	Self-Consistency of the Fokker Planck Equation. COLT Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani
2022	J	`jnl`	Self-Consistency of the Fokker-Planck Equation. CoRR Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani
2022	A*	`conf`	Submodular Maximization in Clean Linear Time. NeurIPS Wenxin Li, Moran Feldman, Ehsan Kazemi, Amin Karbasi
2022	J	`jnl`	The Best of Both Worlds: Reinforcement Learning with Logarithmic Regret and Policy Switches. CoRR Grigoris Velegkas, Zhuoran Yang, Amin Karbasi
2022	J	`jnl`	The Exact Class of Graph Functions Generated by Graph Neural Networks. CoRR Mohammad Fereydounian, Hamed Hassani, Javid Dadashkarimi, Amin Karbasi
2022	J	`jnl`	The Power of Subsampling in Submodular Maximization. Math. Oper. Res. Christopher Harshaw, Ehsan Kazemi, Moran Feldman, Amin Karbasi
2022	—	`conf`	Transforming Connectomes to "Any" Parcellation via Graph Matching. ISGIE/GRAIL@MICCAI Qinghao Liang, Javid Dadashkarimi, Wei Dai, Amin Karbasi, Joseph Chang, Harrison H. Zhou, Dustin Scheinost
2022	A*	`conf`	Universal Rates for Interactive Learning. NeurIPS Steve Hanneke, Amin Karbasi, Shay Moran, Grigoris Velegkas
2021	A*	`conf`	Adaptivity in Adaptive Submodularity. COLT Hossein Esfandiari, Amin Karbasi, Vahab S. Mirrokni
2021	A*	`conf`	An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks. NeurIPS Shashank Rajput, Kartik Sreenivasan, Dimitris S. Papailiopoulos, Amin Karbasi
2021	J	`jnl`	An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks. CoRR Shashank Rajput, Kartik Sreenivasan, Dimitris S. Papailiopoulos, Amin Karbasi
2021	J	`jnl`	Batched Neural Bandits. CoRR Quanquan Gu, Amin Karbasi, Khashayar Khosravi, Vahab S. Mirrokni, Dongruo Zhou
2021	—	`conf`	Data-Driven Mapping Between Functional Connectomes Using Optimal Transport. MICCAI (3) Javid Dadashkarimi, Amin Karbasi, Dustin Scheinost
2021	J	`jnl`	Data-driven mapping between functional connectomes using optimal transport. CoRR Javid Dadashkarimi, Amin Karbasi, Dustin Scheinost
2021	J	`jnl`	Federated Functional Gradient Boosting. CoRR Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi
2021	J	`jnl`	Learning and Certification under Instance-targeted Poisoning. CoRR Ji Gao, Amin Karbasi, Mohammad Mahmoody
2021	A	`conf`	Learning and certification under instance-targeted poisoning. UAI Ji Gao, Amin Karbasi, Mohammad Mahmoody
2021	A	`conf`	Meta Learning in the Continuous Time Limit. AISTATS Ruitu Xu, Lin Chen, Amin Karbasi
2021	A*	`conf`	Multiple Descent: Design Your Own Generalization Curve. NeurIPS Lin Chen, Yifei Min, Mikhail Belkin, Amin Karbasi
2021	A*	`conf`	Parallelizing Thompson Sampling. NeurIPS Amin Karbasi, Vahab S. Mirrokni, Mohammad Shadravan
2021	J	`jnl`	Parallelizing Thompson Sampling. CoRR Amin Karbasi, Vahab S. Mirrokni, Mohammad Shadravan
2021	A*	`conf`	Regret Bounds for Batched Bandits. AAAI Hossein Esfandiari, Amin Karbasi, Abbas Mehrabian, Vahab S. Mirrokni
2021	A*	`conf`	Regularized Submodular Maximization at Scale. ICML Ehsan Kazemi, Shervin Minaee, Moran Feldman, Amin Karbasi
2021	A*	`conf`	Submodular + Concave. NeurIPS Siddharth Mitra, Moran Feldman, Amin Karbasi
2021	J	`jnl`	Submodular + Concave. CoRR Siddharth Mitra, Moran Feldman, Amin Karbasi
2021	J	`jnl`	The Power of Subsampling in Submodular Maximization. CoRR Christopher Harshaw, Ehsan Kazemi, Moran Feldman, Amin Karbasi
2021	A	`conf`	The curious case of adversarially robust models: More data can help, double descend, or hurt generalization. UAI Yifei Min, Lin Chen, Amin Karbasi
2020	A	`conf`	Black Box Submodular Maximization: Discrete and Continuous Settings. AISTATS Lin Chen, Mingrui Zhang, Hamed Hassani, Amin Karbasi
2020	A*	`conf`	Continuous Submodular Maximization: Beyond DR-Submodularity. NeurIPS Moran Feldman, Amin Karbasi
2020	J	`jnl`	Continuous Submodular Maximization: Beyond DR-Submodularity. CoRR Moran Feldman, Amin Karbasi
2020	J	`jnl`	Individualized functional networks reconfigure with cognitive state. NeuroImage Mehraveh Salehi, Amin Karbasi, Daniel S. Barron, Dustin Scheinost, R. Todd Constable
2020	J	`jnl`	Meta Learning in the Continuous Time Limit. CoRR Ruitu Xu, Lin Chen, Amin Karbasi
2020	A*	`conf`	Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transition. NeurIPS Lin Chen, Qian Yu, Hannah Lawrence, Amin Karbasi
2020	A*	`conf`	More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard Models. ICML Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi
2020	J	`jnl`	More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models. CoRR Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi
2020	J	`jnl`	Multiple Descent: Design Your Own Generalization Curve. CoRR Lin Chen, Yifei Min, Mikhail Belkin, Amin Karbasi
2020	A	`conf`	One Sample Stochastic Frank-Wolfe. AISTATS Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi
2020	A*	`conf`	Online MAP Inference of Determinantal Point Processes. NeurIPS Aditya Bhaskara, Amin Karbasi, Silvio Lattanzi, Morteza Zadimoghaddam
2020	A	`conf`	Quantized Frank-Wolfe: Faster Optimization, Lower Communication, and Projection Free. AISTATS Mingrui Zhang, Lin Chen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi
2020	J	`jnl`	Regularized Submodular Maximization at Scale. CoRR Ehsan Kazemi, Shervin Minaee, Moran Feldman, Amin Karbasi
2020	J	`jnl`	Safe Learning under Uncertain Objectives and Constraints. CoRR Mohammad Fereydounian, Zebang Shen, Aryan Mokhtari, Amin Karbasi, Hamed Hassani
2020	J	`jnl`	Simultaneous Greedys: A Swiss Army Knife for Constrained Submodular Maximization. CoRR Moran Feldman, Christopher Harshaw, Amin Karbasi
2020	J	`jnl`	Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization. J. Mach. Learn. Res. Aryan Mokhtari, Hamed Hassani, Amin Karbasi
2020	J	`jnl`	Stochastic Conditional Gradient++: (Non)Convex Minimization and Continuous Submodular Maximization. SIAM J. Optim. Hamed Hassani, Amin Karbasi, Aryan Mokhtari, Zebang Shen
2020	A*	`conf`	Streaming Submodular Maximization under a k-Set System Constraint. ICML Ran Haba, Ehsan Kazemi, Moran Feldman, Amin Karbasi
2020	J	`jnl`	Streaming Submodular Maximization under a k-Set System Constraint. CoRR Ran Haba, Ehsan Kazemi, Moran Feldman, Amin Karbasi
2020	A*	`conf`	Submodular Maximization Through Barrier Functions. NeurIPS Ashwinkumar Badanidiyuru, Amin Karbasi, Ehsan Kazemi, Jan Vondrák
2020	J	`jnl`	Submodular Maximization Through Barrier Functions. CoRR Ashwinkumar Badanidiyuru, Amin Karbasi, Ehsan Kazemi, Jan Vondrák
2020	J	`jnl`	Submodularity in Action: From Machine Learning to Signal Processing Applications. IEEE Signal Process. Mag. Ehsan Tohidi, Rouhollah Amiri, Mario Coutino, David Gesbert, Geert Leus, Amin Karbasi
2020	J	`jnl`	The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization. CoRR Yifei Min, Lin Chen, Amin Karbasi
2020	J	`jnl`	There is no single functional atlas even for a single individual: Functional parcel definitions change with task. NeuroImage Mehraveh Salehi, Abigail S. Greene, Amin Karbasi, Xilin Shen, Dustin Scheinost, R. Todd Constable
2019	A*	`conf`	Adaptive Sequence Submodularity. NeurIPS Marko Mitrovic, Ehsan Kazemi, Moran Feldman, Andreas Krause, Amin Karbasi
2019	J	`jnl`	Adaptive Sequence Submodularity. CoRR Marko Mitrovic, Ehsan Kazemi, Moran Feldman, Andreas Krause, Amin Karbasi
2019	J	`jnl`	Adaptivity in Adaptive Submodularity. CoRR Hossein Esfandiari, Amin Karbasi, Vahab S. Mirrokni
2019	J	`jnl`	Batched Multi-Armed Bandits with Optimal Regret. CoRR Hossein Esfandiari, Amin Karbasi, Abbas Mehrabian, Vahab S. Mirrokni
2019	J	`jnl`	Black Box Submodular Maximization: Discrete and Continuous Settings. CoRR Lin Chen, Mingrui Zhang, Hamed Hassani, Amin Karbasi
2019	A*	`conf`	Eliminating Latent Discrimination: Train Then Mask. AAAI Soheil Ghili, Ehsan Kazemi, Amin Karbasi
2019	J	`jnl`	Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transition. CoRR Lin Chen, Qian Yu, Hannah Lawrence, Amin Karbasi
2019	J	`jnl`	One Sample Stochastic Frank-Wolfe. CoRR Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi
2019	A*	`conf`	Online Continuous Submodular Maximization: From Full-Information to Bandit Feedback. NeurIPS Mingrui Zhang, Lin Chen, Hamed Hassani, Amin Karbasi
2019	J	`jnl`	Online Continuous Submodular Maximization: From Full-Information to Bandit Feedback. CoRR Mingrui Zhang, Lin Chen, Hamed Hassani, Amin Karbasi
2019	A	`conf`	Projection-Free Bandit Convex Optimization. AISTATS Lin Chen, Mingrui Zhang, Amin Karbasi
2019	J	`jnl`	Quantized Frank-Wolfe: Communication-Efficient Distributed Optimization. CoRR Mingrui Zhang, Lin Chen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi
2019	J	`jnl`	Stochastic Conditional Gradient++. CoRR Hamed Hassani, Amin Karbasi, Aryan Mokhtari, Zebang Shen
2019	A*	`conf`	Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match. NeurIPS Amin Karbasi, Hamed Hassani, Aryan Mokhtari, Zebang Shen
2019	J	`jnl`	Submodular Maximization Beyond Non-negativity: Guarantees, Fast Algorithms, and Applications. CoRR Christopher Harshaw, Moran Feldman, Justin Ward, Amin Karbasi
2019	A*	`conf`	Submodular Maximization beyond Non-negativity: Guarantees, Fast Algorithms, and Applications. ICML Chris Harshaw, Moran Feldman, Justin Ward, Amin Karbasi
2019	A*	`conf`	Submodular Streaming in All Its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity. ICML Ehsan Kazemi, Marko Mitrovic, Morteza Zadimoghaddam, Silvio Lattanzi, Amin Karbasi
2019	J	`jnl`	Submodular Streaming in All its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity. CoRR Ehsan Kazemi, Marko Mitrovic, Morteza Zadimoghaddam, Silvio Lattanzi, Amin Karbasi
2019	A*	`conf`	Unconstrained submodular maximization with constant adaptive complexity. STOC Lin Chen, Moran Feldman, Amin Karbasi
2018	J	`jnl`	An exemplar-based approach to individualized parcellation reveals the need for sex specific functional networks. NeuroImage Mehraveh Salehi, Amin Karbasi, Xilin Shen, Dustin Scheinost, R. Todd Constable
2018	A	`conf`	Comparison Based Learning from Weak Oracles. AISTATS Ehsan Kazemi, Lin Chen, Sanjoy Dasgupta, Amin Karbasi
2018	J	`jnl`	Comparison Based Learning from Weak Oracles. CoRR Ehsan Kazemi, Lin Chen, Sanjoy Dasgupta, Amin Karbasi
2018	A	`conf`	Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap. AISTATS Aryan Mokhtari, Hamed Hassani, Amin Karbasi
2018	A*	`conf`	Data Summarization at Scale: A Two-Stage Submodular Approach. ICML Marko Mitrovic, Ehsan Kazemi, Morteza Zadimoghaddam, Amin Karbasi
2018	J	`jnl`	Data Summarization at Scale: A Two-Stage Submodular Approach. CoRR Marko Mitrovic, Ehsan Kazemi, Morteza Zadimoghaddam, Amin Karbasi
2018	A*	`conf`	Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings. ICML Aryan Mokhtari, Hamed Hassani, Amin Karbasi
2018	A*	`conf`	Do Less, Get More: Streaming Submodular Maximization with Subsampling. NeurIPS Moran Feldman, Amin Karbasi, Ehsan Kazemi
2018	J	`jnl`	Do Less, Get More: Streaming Submodular Maximization with Subsampling. CoRR Moran Feldman, Amin Karbasi, Ehsan Kazemi
2018	J	`jnl`	Eliminating Latent Discrimination: Train Then Mask. CoRR Soheil Ghili, Ehsan Kazemi, Amin Karbasi
2018	J	`jnl`	Learning neural connectivity from firing activity: efficient algorithms with provable guarantees on topology. J. Comput. Neurosci. Amin Karbasi, Amir Hesam Salavati, Martin Vetterli
2018	A	`conf`	Online Continuous Submodular Maximization. AISTATS Lin Chen, Hamed Hassani, Amin Karbasi
2018	J	`jnl`	Online Continuous Submodular Maximization. CoRR Lin Chen, Hamed Hassani, Amin Karbasi
2018	J	`jnl`	Projection-Free Bandit Convex Optimization. CoRR Lin Chen, Mingrui Zhang, Amin Karbasi
2018	A*	`conf`	Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity. ICML Lin Chen, Christopher Harshaw, Hamed Hassani, Amin Karbasi
2018	A*	`conf`	Scalable Deletion-Robust Submodular Maximization: Data Summarization with Privacy and Fairness Constraints. ICML Ehsan Kazemi, Morteza Zadimoghaddam, Amin Karbasi
2018	J	`jnl`	Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization. CoRR Aryan Mokhtari, Hamed Hassani, Amin Karbasi
2018	A	`conf`	Submodularity on Hypergraphs: From Sets to Sequences. AISTATS Marko Mitrovic, Moran Feldman, Andreas Krause, Amin Karbasi
2018	J	`jnl`	Submodularity on Hypergraphs: From Sets to Sequences. CoRR Marko Mitrovic, Moran Feldman, Andreas Krause, Amin Karbasi
2018	J	`jnl`	Unconstrained Submodular Maximization with Constant Adaptive Complexity. CoRR Lin Chen, Moran Feldman, Amin Karbasi
2018	A*	`conf`	Weakly Submodular Maximization Beyond Cardinality Constraints: Does Randomization Help Greedy? ICML Lin Chen, Moran Feldman, Amin Karbasi
2017	—	`conf`	A Submodular Approach to Create Individualized Parcellations of the Human Brain. MICCAI (1) Mehraveh Salehi, Amin Karbasi, Dustin Scheinost, R. Todd Constable
2017	J	`jnl`	Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap. CoRR Aryan Mokhtari, S. Hamed Hassani, Amin Karbasi
2017	J	`jnl`	Deletion-Robust Submodular Maximization at Scale. CoRR Ehsan Kazemi, Morteza Zadimoghaddam, Amin Karbasi
2017	A*	`conf`	Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten". ICML Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause
2017	A*	`conf`	Differentially Private Submodular Maximization: Data Summarization in Disguise. ICML Marko Mitrovic, Mark Bun, Andreas Krause, Amin Karbasi
2017	—	`conf`	Gradient Methods for Submodular Maximization. NIPS S. Hamed Hassani, Mahdi Soltanolkotabi, Amin Karbasi
2017	J	`jnl`	Gradient Methods for Submodular Maximization. CoRR S. Hamed Hassani, Mahdi Soltanolkotabi, Amin Karbasi
2017	A*	`conf`	Greed Is Good: Near-Optimal Submodular Maximization via Greedy Optimization. COLT Moran Feldman, Christopher Harshaw, Amin Karbasi
2017	J	`jnl`	Greed is Good: Near-Optimal Submodular Maximization via Greedy Optimization. CoRR Moran Feldman, Christopher Harshaw, Amin Karbasi
2017	—	`conf`	Interactive Submodular Bandit. NIPS Lin Chen, Andreas Krause, Amin Karbasi
2017	A*	`conf`	Near-Optimal Active Learning of Halfspaces via Query Synthesis in the Noisy Setting. AAAI Lin Chen, Seyed Hamed Hassani, Amin Karbasi
2017	A*	`conf`	Probabilistic Submodular Maximization in Sub-Linear Time. ICML Serban Stan, Morteza Zadimoghaddam, Andreas Krause, Amin Karbasi
2017	—	`conf`	Streaming Weak Submodularity: Interpreting Neural Networks on the Fly. NIPS Ethan R. Elenberg, Alexandros G. Dimakis, Moran Feldman, Amin Karbasi
2017	J	`jnl`	Streaming Weak Submodularity: Interpreting Neural Networks on the Fly. CoRR Ethan R. Elenberg, Alexandros G. Dimakis, Moran Feldman, Amin Karbasi
2017	A	`conf`	Submodular Variational Inference for Network Reconstruction. UAI Lin Chen, Forrest W. Crawford, Amin Karbasi
2017	J	`jnl`	Weakly Submodular Maximization Beyond Cardinality Constraints: Does Randomization Help Greedy? CoRR Lin Chen, Moran Feldman, Amin Karbasi
2016	J	`jnl`	Dimension Coupling: Optimal Active Learning of Halfspaces via Query Synthesis. CoRR Lin Chen, S. Hamed Hassani, Amin Karbasi
2016	J	`jnl`	Distributed Submodular Maximization. J. Mach. Learn. Res. Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause
2016	—	`conf`	Estimating the Size of a Large Network and its Communities from a Random Sample. NIPS Lin Chen, Amin Karbasi, Forrest W. Crawford
2016	J	`jnl`	Estimating the Size of a Large Network and its Communities from a Random Sample. CoRR Lin Chen, Amin Karbasi, Forrest W. Crawford
2016	A*	`conf`	Fast Constrained Submodular Maximization: Personalized Data Summarization. ICML Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi
2016	—	`conf`	Fast Distributed Submodular Cover: Public-Private Data Summarization. NIPS Baharan Mirzasoleiman, Morteza Zadimoghaddam, Amin Karbasi
2016	Misc	`conf`	Learning network structures from firing patterns. ICASSP Amin Karbasi, Amir Hesam Salavati, Martin Vetterli
2016	A*	`conf`	Seeing the Unseen Network: Inferring Hidden Social Ties from Respondent-Driven Sampling. AAAI Lin Chen, Forrest W. Crawford, Amin Karbasi
2016	J	`jnl`	Submodular Variational Inference for Network Reconstruction. CoRR Lin Chen, Amin Karbasi, Forrest W. Crawford
2016	J	`jnl`	Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning. CoRR Mario Lucic, Mesrob I. Ohannessian, Amin Karbasi, Andreas Krause
2015	B	`conf`	Asynchronous decoding of LDPC codes over BEC. ISIT Saeid Haghighatshoar, Amin Karbasi, Amir Hesam Salavati
2015	—	`conf`	Distributed Submodular Cover: Succinctly Summarizing Massive Data. NIPS Baharan Mirzasoleiman, Amin Karbasi, Ashwinkumar Badanidiyuru, Andreas Krause
2015	A*	`conf`	Fast Mixing for Discrete Point Processes. COLT Patrick Rebeschini, Amin Karbasi
2015	J	`jnl`	From Small-World Networks to Comparison-Based Search. IEEE Trans. Inf. Theory Amin Karbasi, Stratis Ioannidis, Laurent Massoulié
2015	A*	`conf`	Lazier Than Lazy Greedy. AAAI Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi, Jan Vondrák, Andreas Krause
2015	A*	`conf`	Non-Monotone Adaptive Submodular Maximization. IJCAI Alkis Gotovos, Amin Karbasi, Andreas Krause
2015	—	`conf`	Normalization Phenomena in Asynchronous Networks. ICALP (2) Amin Karbasi, Johannes Lengler, Angelika Steger
2015	J	`jnl`	Seeing the Unseen Network: Inferring Hidden Social Ties from Respondent-Driven Sampling. CoRR Lin Chen, Forrest W. Crawford, Amin Karbasi
2015	A*	`conf`	Sequential Information Maximization: When is Greedy Near-optimal? COLT Yuxin Chen, S. Hamed Hassani, Amin Karbasi, Andreas Krause
2015	A*	`conf`	Submodular Surrogates for Value of Information. AAAI Yuxin Chen, Shervin Javdani, Amin Karbasi, J. Andrew Bagnell, Siddhartha S. Srinivasa, Andreas Krause
2015	A	`conf`	Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning. AISTATS Mario Lucic, Mesrob I. Ohannessian, Amin Karbasi, Andreas Krause
2014	J	`jnl`	Convolutional Neural Associative Memories: Massive Capacity with Noise Tolerance. CoRR Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi
2014	J	`jnl`	Distributed Submodular Maximization. CoRR Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause
2014	J	`jnl`	Lazier Than Lazy Greedy. CoRR Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi, Jan Vondrák, Andreas Krause
2014	A	`conf`	Near Optimal Bayesian Active Learning for Decision Making. AISTATS Shervin Javdani, Yuxin Chen, Amin Karbasi, Andreas Krause, Drew Bagnell, Siddhartha S. Srinivasa
2014	J	`jnl`	Near Optimal Bayesian Active Learning for Decision Making. CoRR Shervin Javdani, Yuxin Chen, Amin Karbasi, Andreas Krause, J. Andrew Bagnell, Siddhartha S. Srinivasa
2014	A*	`conf`	Near-Optimally Teaching the Crowd to Classify. ICML Adish Singla, Ilija Bogunovic, Gábor Bartók, Amin Karbasi, Andreas Krause
2014	J	`jnl`	Near-Optimally Teaching the Crowd to Classify. CoRR Adish Singla, Ilija Bogunovic, Gábor Bartók, Amin Karbasi, Andreas Krause
2014	J	`jnl`	Noise Facilitation in Associative Memories of Exponential Capacity. CoRR Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi, Lav R. Varshney
2014	J	`jnl`	Noise Facilitation in Associative Memories of Exponential Capacity. Neural Comput. Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi, Lav R. Varshney
2014	A*	`conf`	Streaming submodular maximization: massive data summarization on the fly. KDD Ashwinkumar Badanidiyuru, Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause
2013	J	`jnl`	Calibration Using Matrix Completion With Application to Ultrasound Tomography. IEEE Trans. Signal Process. Reza Parhizkar, Amin Karbasi, Sewoong Oh, Martin Vetterli
2013	A	`conf`	Constrained Binary Identification Problem. STACS Amin Karbasi, Morteza Zadimoghaddam
2013	J	`jnl`	Coupled Neural Associative Memories CoRR Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi
2013	B	`conf`	Coupled neural associative memories. ITW Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi
2013	—	`conf`	Distributed Submodular Maximization: Identifying Representative Elements in Massive Data. NIPS Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause
2013	—	`conf`	Iterative Learning and Denoising in Convolutional Neural Associative Memories. ICML (1) Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi
2013	—	`conf`	Noise-Enhanced Associative Memories. NIPS Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi, Lav R. Varshney
2013	J	`jnl`	Robust Localization From Incomplete Local Information. IEEE/ACM Trans. Netw. Amin Karbasi, Sewoong Oh
2012	J	`jnl`	Comparison-Based Learning with Rank Nets CoRR Amin Karbasi, Stratis Ioannidis, Laurent Massoulié
2012	A*	`conf`	Comparison-Based Learning with Rank Nets. ICML Amin Karbasi, Stratis Ioannidis, Laurent Massoulié
2012	—	`—`	Graph-Based Information Processing - Scaling Laws and Applications. Amin Karbasi
2012	J	`jnl`	Graph-Constrained Group Testing. IEEE Trans. Inf. Theory Mahdi Cheraghchi, Amin Karbasi, Soheil Mohajer, Venkatesh Saligrama
2012	Misc	`conf`	Hot or not: Interactive content search using comparisons. ITA Amin Karbasi, Stratis Ioannidis, Laurent Massoulié
2012	J	`jnl`	Low-Rank Matrix Approximation Using Point-Wise Operators. IEEE Trans. Inf. Theory Arash Amini, Amin Karbasi, Farokh Marvasti
2012	J	`jnl`	Multi-Level Error-Resilient Neural Networks with Learning CoRR Amir Hesam Salavati, Amin Karbasi
2012	B	`conf`	Multi-level error-resilient neural networks. ISIT Amir Hesam Salavati, Amin Karbasi
2012	B	`conf`	Sequential group testing with graph constraints. ITW Amin Karbasi, Morteza Zadimoghaddam
2011	J	`jnl`	Adaptive Content Search Through Comparisons CoRR Amin Karbasi, Stratis Ioannidis, Laurent Massoulié
2011	Misc	`conf`	Calibration in circular ultrasound tomography devices. ICASSP Reza Parhizkar, Amin Karbasi, Martin Vetterli
2011	B	`conf`	Compression with graphical constraints: An interactive browser. ISIT Amin Karbasi, Morteza Zadimoghaddam
2011	—	`conf`	Content Search through Comparisons. ICALP (2) Amin Karbasi, Stratis Ioannidis, Laurent Massoulié
2011	J	`jnl`	Group Testing With Probabilistic Tests: Theory, Design and Application. IEEE Trans. Inf. Theory Mahdi Cheraghchi, Ali Hormati, Amin Karbasi, Martin Vetterli
2011	J	`jnl`	Robust Localization from Incomplete Local Information CoRR Amin Karbasi, Sewoong Oh
2010	J	`jnl`	Calibration for Ultrasound Breast Tomography Using Matrix Completion CoRR Reza Parhizkar, Amin Karbasi, Sewoong Oh, Martin Vetterli
2010	A*	`conf`	Distributed sensor network localization from local connectivity: performance analysis for the HOP-TERRAIN algorithm. SIGMETRICS Amin Karbasi, Sewoong Oh
2010	—	`conf`	From centralized to distributed sensor localization. S3@MobiCom Amin Karbasi
2010	J	`jnl`	Graph-Constrained Group Testing CoRR Mahdi Cheraghchi, Amin Karbasi, Soheil Mohajer, Venkatesh Saligrama
2010	B	`conf`	Graph-constrained group testing. ISIT Mahdi Cheraghchi, Amin Karbasi, Soheil Mohajer, Venkatesh Saligrama
2010	J	`jnl`	Group Testing with Probabilistic Tests: Theory, Design and Application CoRR Mahdi Cheraghchi, Ali Hormati, Amin Karbasi, Martin Vetterli
2009	J	`jnl`	An Estimation Theoretic Approach for Sparsity Pattern Recovery in the Noisy Setting CoRR Ali Hormati, Amin Karbasi, Soheil Mohajer, Martin Vetterli
2009	J	`jnl`	Compressed Sensing with Probabilistic Measurements: A Group Testing Solution CoRR Mahdi Cheraghchi, Ali Hormati, Amin Karbasi, Martin Vetterli
2009	—	`conf`	Compressed sensing with probabilistic measurements: A group testing solution. Allerton Mahdi Cheraghchi, Ali Hormati, Amin Karbasi, Martin Vetterli
2009	B	`conf`	Support recovery in compressed sensing: An estimation theoretic approach. ISIT Amin Karbasi, Ali Hormati, Soheil Mohajer, Martin Vetterli
2007	—	`conf`	A new DOA estimation method using a circular microphone array. EUSIPCO Amin Karbasi, Akihiko Sugiyama
2006	—	`conf`	A DOA estimation method for an arbitrary triangular microphone arrangement. EUSIPCO Amin Karbasi, Akihiko Sugiyama