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Amin Karbasi
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2020 – today
- 2024
- [c114]Loay Raed Mualem, Ethan R. Elenberg, Moran Feldman, Amin Karbasi:
Submodular Minimax Optimization: Finding Effective Sets. AISTATS 2024: 1081-1089 - [c113]Amin Karbasi, Kasper Green Larsen:
The Impossibility of Parallelizing Boosting. ALT 2024: 635-653 - [c112]Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas:
Universal Rates for Regression: Separations between Cut-Off and Absolute Loss. COLT 2024: 359-405 - [c111]Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh:
HyperAttention: Long-context Attention in Near-Linear Time. ICLR 2024 - [c110]Patrik Okanovic, Roger Waleffe, Vasilis Mageirakos, Konstantinos E. Nikolakakis, Amin Karbasi, Dionysios S. Kalogerias, Nezihe Merve Gürel, Theodoros Rekatsinas:
Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning. ICLR 2024 - [i96]Amir Zandieh, Insu Han, Vahab Mirrokni, Amin Karbasi:
SubGen: Token Generation in Sublinear Time and Memory. CoRR abs/2402.06082 (2024) - [i95]Alkis Kalavasis, Amin Karbasi, Kasper Green Larsen, Grigoris Velegkas, Felix Zhou:
Replicable Learning of Large-Margin Halfspaces. CoRR abs/2402.13857 (2024) - [i94]Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas, Felix Zhou:
On the Computational Landscape of Replicable Learning. CoRR abs/2405.15599 (2024) - [i93]Alkis Kalavasis, Amin Karbasi, Argyris Oikonomou, Katerina Sotiraki, Grigoris Velegkas, Manolis Zampetakis:
Injecting Undetectable Backdoors in Deep Learning and Language Models. CoRR abs/2406.05660 (2024) - 2023
- [j18]Moran Feldman, Christopher Harshaw, Amin Karbasi:
How Do You Want Your Greedy: Simultaneous or Repeated? J. Mach. Learn. Res. 24: 72:1-72:87 (2023) - [j17]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
:
Cross Atlas Remapping via Optimal Transport (CAROT): Creating connectomes for different atlases when raw data is not available. Medical Image Anal. 88: 102864 (2023) - [c109]Jane H. Lee, Saeid Haghighatshoar, Amin Karbasi:
Exact Gradient Computation for Spiking Neural Networks via Forward Propagation. AISTATS 2023: 1812-1831 - [c108]Javid Dadashkarimi, Matthew Rosenblatt, Amin Karbasi, Dustin Scheinost:
Stacking multiple optimal transport policies to map functional connectomes. CISS 2023: 1-6 - [c107]Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni, Grigoris Velegkas:
Replicable Bandits. ICLR 2023 - [c106]Konstantinos E. Nikolakakis, Farzin Haddadpour, Amin Karbasi, Dionysios S. Kalogerias:
Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD. ICLR 2023 - [c105]Alkis Kalavasis, Amin Karbasi, Shay Moran, Grigoris Velegkas:
Statistical Indistinguishability of Learning Algorithms. ICML 2023: 15586-15622 - [c104]Amin Karbasi, Nikki Lijing Kuang, Yi-An Ma, Siddharth Mitra:
Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning. ICML 2023: 15828-15860 - [c103]Amir Zandieh, Insu Han, Majid Daliri, Amin Karbasi:
KDEformer: Accelerating Transformers via Kernel Density Estimation. ICML 2023: 40605-40623 - [c102]Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas:
Optimal Learners for Realizable Regression: PAC Learning and Online Learning. NeurIPS 2023 - [c101]Hossein Esfandiari, Amin Karbasi, Vahab Mirrokni, Grigoris Velegkas, Felix Zhou:
Replicable Clustering. NeurIPS 2023 - [c100]Amin Karbasi, Grigoris Velegkas, Lin Yang, Felix Zhou:
Replicability in Reinforcement Learning. NeurIPS 2023 - [c99]Liang Zhang, Junchi Yang, Amin Karbasi, Niao He:
Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization. NeurIPS 2023 - [i92]Amin Karbasi, Kasper Green Larsen:
The Impossibility of Parallelizing Boosting. CoRR abs/2301.09627 (2023) - [i91]Amir Zandieh, Insu Han, Majid Daliri, Amin Karbasi:
KDEformer: Accelerating Transformers via Kernel Density Estimation. CoRR abs/2302.02451 (2023) - [i90]Hossein Esfandiari, Amin Karbasi, Vahab Mirrokni, Grigoris Velegkas, Felix Zhou:
Replicable Clustering. CoRR abs/2302.10359 (2023) - [i89]Konstantinos E. Nikolakakis, Amin Karbasi, Dionysis Kalogerias
:
Select without Fear: Almost All Mini-Batch Schedules Generalize Optimally. CoRR abs/2305.02247 (2023) - [i88]Lin Chen, Gang Fu, Amin Karbasi, Vahab Mirrokni:
Learning from Aggregated Data: Curated Bags versus Random Bags. CoRR abs/2305.09557 (2023) - [i87]Alkis Kalavasis, Amin Karbasi, Shay Moran, Grigoris Velegkas:
Statistical Indistinguishability of Learning Algorithms. CoRR abs/2305.14311 (2023) - [i86]Loay Mualem, Ethan R. Elenberg, Moran Feldman, Amin Karbasi:
Submodular Minimax Optimization: Finding Effective Sets. CoRR abs/2305.16903 (2023) - [i85]Patrik Okanovic, Roger Waleffe, Vasilis Mageirakos, Konstantinos E. Nikolakakis, Amin Karbasi, Dionysios S. Kalogerias, Nezihe Merve Gürel, Theodoros Rekatsinas:
Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning. CoRR abs/2305.18424 (2023) - [i84]Amin Karbasi, Grigoris Velegkas, Lin F. Yang, Felix Zhou:
Replicability in Reinforcement Learning. CoRR abs/2305.19562 (2023) - [i83]Amin Karbasi, Nikki Lijing Kuang, Yi-An Ma, Siddharth Mitra:
Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning. CoRR abs/2306.08803 (2023) - [i82]Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas:
Optimal Learners for Realizable Regression: PAC Learning and Online Learning. CoRR abs/2307.03848 (2023) - [i81]Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh:
HyperAttention: Long-context Attention in Near-Linear Time. CoRR abs/2310.05869 (2023) - [i80]Liang Zhang, Junchi Yang, Amin Karbasi, Niao He:
Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization. CoRR abs/2310.17759 (2023) - [i79]Anay Mehrotra, Manolis Zampetakis
, Paul Kassianik, Blaine Nelson, Hyrum S. Anderson, Yaron Singer, Amin Karbasi:
Tree of Attacks: Jailbreaking Black-Box LLMs Automatically. CoRR abs/2312.02119 (2023) - 2022
- [j16]Christopher Harshaw
, Ehsan Kazemi
, Moran Feldman
, Amin Karbasi:
The Power of Subsampling in Submodular Maximization. Math. Oper. Res. 47(2): 1365-1393 (2022) - [c98]Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi:
Federated Functional Gradient Boosting. AISTATS 2022: 7814-7840 - [c97]Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani:
Self-Consistency of the Fokker Planck Equation. COLT 2022: 817-841 - [c96]Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Amin Karbasi:
Learning Distributionally Robust Models at Scale via Composite Optimization. ICLR 2022 - [c95]Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, Amin Karbasi:
Scalable Sampling for Nonsymmetric Determinantal Point Processes. ICLR 2022 - [c94]Insu Han, Mike Gartrell, Elvis Dohmatob, Amin Karbasi:
Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes. ICML 2022: 8213-8229 - [c93]Qinghao Liang, Javid Dadashkarimi, Wei Dai, Amin Karbasi, Joseph Chang, Harrison H. Zhou, Dustin Scheinost:
Transforming Connectomes to "Any" Parcellation via Graph Matching. ISGIE/GRAIL@MICCAI 2022: 118-127 - [c92]Javid Dadashkarimi, Amin Karbasi, Dustin Scheinost:
Combining Multiple Atlases to Estimate Data-Driven Mappings Between Functional Connectomes Using Optimal Transport. MICCAI (1) 2022: 386-395 - [c91]Insu Han, Amir Zandieh, Jaehoon Lee, Roman Novak, Lechao Xiao, Amin Karbasi:
Fast Neural Kernel Embeddings for General Activations. NeurIPS 2022 - [c90]Steve Hanneke, Amin Karbasi, Mohammad Mahmoody, Idan Mehalel, Shay Moran:
On Optimal Learning Under Targeted Data Poisoning. NeurIPS 2022 - [c89]Steve Hanneke, Amin Karbasi, Shay Moran, Grigoris Velegkas:
Universal Rates for Interactive Learning. NeurIPS 2022 - [c88]Alkis Kalavasis, Grigoris Velegkas, Amin Karbasi:
Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes. NeurIPS 2022 - [c87]Wenxin Li, Moran Feldman, Ehsan Kazemi, Amin Karbasi:
Submodular Maximization in Clean Linear Time. NeurIPS 2022 - [c86]Konstantinos E. Nikolakakis, Farzin Haddadpour, Dionysios S. Kalogerias, Amin Karbasi:
Black-Box Generalization: Stability of Zeroth-Order Learning. NeurIPS 2022 - [c85]Grigoris Velegkas, Zhuoran Yang, Amin Karbasi:
Reinforcement Learning with Logarithmic Regret and Policy Switches. NeurIPS 2022 - [i78]Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, Amin Karbasi:
Scalable Sampling for Nonsymmetric Determinantal Point Processes. CoRR abs/2201.08417 (2022) - [i77]Konstantinos E. Nikolakakis, Farzin Haddadpour, Dionysios S. Kalogerias, Amin Karbasi:
Black-Box Generalization. CoRR abs/2202.06880 (2022) - [i76]Mohammad Fereydounian, Hamed Hassani, Javid Dadashkarimi, Amin Karbasi:
The Exact Class of Graph Functions Generated by Graph Neural Networks. CoRR abs/2202.08833 (2022) - [i75]Grigoris Velegkas, Zhuoran Yang, Amin Karbasi:
The Best of Both Worlds: Reinforcement Learning with Logarithmic Regret and Policy Switches. CoRR abs/2203.01491 (2022) - [i74]Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Amin Karbasi:
Learning Distributionally Robust Models at Scale via Composite Optimization. CoRR abs/2203.09607 (2022) - [i73]Konstantinos E. Nikolakakis, Farzin Haddadpour, Amin Karbasi, Dionysios S. Kalogerias
:
Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD. CoRR abs/2204.12446 (2022) - [i72]Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani:
Self-Consistency of the Fokker-Planck Equation. CoRR abs/2206.00860 (2022) - [i71]Insu Han, Mike Gartrell, Elvis Dohmatob, Amin Karbasi:
Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes. CoRR abs/2207.00486 (2022) - [i70]Insu Han, Amir Zandieh, Jaehoon Lee, Roman Novak, Lechao Xiao, Amin Karbasi:
Fast Neural Kernel Embeddings for General Activations. CoRR abs/2209.04121 (2022) - [i69]Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni, Grigoris Velegkas:
Reproducible Bandits. CoRR abs/2210.01898 (2022) - [i68]Alkis Kalavasis, Grigoris Velegkas, Amin Karbasi:
Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes. CoRR abs/2210.02297 (2022) - [i67]Steve Hanneke, Amin Karbasi, Mohammad Mahmoody, Idan Mehalel, Shay Moran:
On Optimal Learning Under Targeted Data Poisoning. CoRR abs/2210.02713 (2022) - [i66]Jane H. Lee, Saeid Haghighatshoar, Amin Karbasi:
Exact Gradient Computation for Spiking Neural Networks Through Forward Propagation. CoRR abs/2210.15415 (2022) - 2021
- [c84]Hossein Esfandiari, Amin Karbasi, Abbas Mehrabian, Vahab S. Mirrokni:
Regret Bounds for Batched Bandits. AAAI 2021: 7340-7348 - [c83]Ruitu Xu, Lin Chen, Amin Karbasi:
Meta Learning in the Continuous Time Limit. AISTATS 2021: 3052-3060 - [c82]Hossein Esfandiari, Amin Karbasi, Vahab S. Mirrokni:
Adaptivity in Adaptive Submodularity. COLT 2021: 1823-1846 - [c81]Ehsan Kazemi, Shervin Minaee, Moran Feldman, Amin Karbasi:
Regularized Submodular Maximization at Scale. ICML 2021: 5356-5366 - [c80]Javid Dadashkarimi, Amin Karbasi, Dustin Scheinost:
Data-Driven Mapping Between Functional Connectomes Using Optimal Transport. MICCAI (3) 2021: 293-302 - [c79]Lin Chen, Yifei Min, Mikhail Belkin, Amin Karbasi:
Multiple Descent: Design Your Own Generalization Curve. NeurIPS 2021: 8898-8912 - [c78]Amin Karbasi, Vahab S. Mirrokni, Mohammad Shadravan:
Parallelizing Thompson Sampling. NeurIPS 2021: 10535-10548 - [c77]Siddharth Mitra, Moran Feldman, Amin Karbasi:
Submodular + Concave. NeurIPS 2021: 11577-11591 - [c76]Shashank Rajput, Kartik Sreenivasan, Dimitris S. Papailiopoulos, Amin Karbasi:
An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks. NeurIPS 2021: 12674-12685 - [c75]Yifei Min, Lin Chen, Amin Karbasi:
The curious case of adversarially robust models: More data can help, double descend, or hurt generalization. UAI 2021: 129-139 - [c74]Ji Gao, Amin Karbasi, Mohammad Mahmoody:
Learning and certification under instance-targeted poisoning. UAI 2021: 2135-2145 - [i65]Quanquan Gu, Amin Karbasi, Khashayar Khosravi, Vahab S. Mirrokni, Dongruo Zhou:
Batched Neural Bandits. CoRR abs/2102.13028 (2021) - [i64]Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi:
Federated Functional Gradient Boosting. CoRR abs/2103.06972 (2021) - [i63]Christopher Harshaw, Ehsan Kazemi, Moran Feldman, Amin Karbasi:
The Power of Subsampling in Submodular Maximization. CoRR abs/2104.02772 (2021) - [i62]Ji Gao, Amin Karbasi, Mohammad Mahmoody:
Learning and Certification under Instance-targeted Poisoning. CoRR abs/2105.08709 (2021) - [i61]Amin Karbasi, Vahab S. Mirrokni, Mohammad Shadravan:
Parallelizing Thompson Sampling. CoRR abs/2106.01420 (2021) - [i60]Siddharth Mitra, Moran Feldman, Amin Karbasi:
Submodular + Concave. CoRR abs/2106.04769 (2021) - [i59]Shashank Rajput, Kartik Sreenivasan, Dimitris S. Papailiopoulos, Amin Karbasi:
An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks. CoRR abs/2106.07724 (2021) - [i58]Javid Dadashkarimi, Amin Karbasi, Dustin Scheinost:
Data-driven mapping between functional connectomes using optimal transport. CoRR abs/2107.01303 (2021) - 2020
- [j15]Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization. J. Mach. Learn. Res. 21: 105:1-105:49 (2020) - [j14]Mehraveh Salehi, Amin Karbasi, Daniel S. Barron, Dustin Scheinost, R. Todd Constable
:
Individualized functional networks reconfigure with cognitive state. NeuroImage 206 (2020) - [j13]Mehraveh Salehi, Abigail S. Greene
, Amin Karbasi, Xilin Shen
, Dustin Scheinost, R. Todd Constable
:
There is no single functional atlas even for a single individual: Functional parcel definitions change with task. NeuroImage 208: 116366 (2020) - [j12]Hamed Hassani, Amin Karbasi, Aryan Mokhtari
, Zebang Shen
:
Stochastic Conditional Gradient++: (Non)Convex Minimization and Continuous Submodular Maximization. SIAM J. Optim. 30(4): 3315-3344 (2020) - [j11]Ehsan Tohidi
, Rouhollah Amiri
, Mario Coutino, David Gesbert, Geert Leus
, Amin Karbasi:
Submodularity in Action: From Machine Learning to Signal Processing Applications. IEEE Signal Process. Mag. 37(5): 120-133 (2020) - [c73]Lin Chen, Mingrui Zhang, Hamed Hassani, Amin Karbasi:
Black Box Submodular Maximization: Discrete and Continuous Settings. AISTATS 2020: 1058-1070 - [c72]Mingrui Zhang, Lin Chen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
Quantized Frank-Wolfe: Faster Optimization, Lower Communication, and Projection Free. AISTATS 2020: 3696-3706 - [c71]Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
One Sample Stochastic Frank-Wolfe. AISTATS 2020: 4012-4023 - [c70]Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi:
More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard Models. ICML 2020: 1670-1680 - [c69]Ran Haba, Ehsan Kazemi, Moran Feldman, Amin Karbasi:
Streaming Submodular Maximization under a k-Set System Constraint. ICML 2020: 3939-3949 - [c68]Ashwinkumar Badanidiyuru, Amin Karbasi, Ehsan Kazemi, Jan Vondrák:
Submodular Maximization Through Barrier Functions. NeurIPS 2020 - [c67]Aditya Bhaskara, Amin Karbasi, Silvio Lattanzi, Morteza Zadimoghaddam:
Online MAP Inference of Determinantal Point Processes. NeurIPS 2020 - [c66]Lin Chen, Qian Yu, Hannah Lawrence, Amin Karbasi:
Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transition. NeurIPS 2020 - [c65]Moran Feldman, Amin Karbasi:
Continuous Submodular Maximization: Beyond DR-Submodularity. NeurIPS 2020 - [i57]Ran Haba, Ehsan Kazemi, Moran Feldman, Amin Karbasi:
Streaming Submodular Maximization under a k-Set System Constraint. CoRR abs/2002.03352 (2020) - [i56]Ehsan Kazemi, Shervin Minaee, Moran Feldman, Amin Karbasi:
Regularized Submodular Maximization at Scale. CoRR abs/2002.03503 (2020) - [i55]Ashwinkumar Badanidiyuru, Amin Karbasi, Ehsan Kazemi, Jan Vondrák:
Submodular Maximization Through Barrier Functions. CoRR abs/2002.03523 (2020) - [i54]Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi:
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models. CoRR abs/2002.04725 (2020) - [i53]Yifei Min, Lin Chen, Amin Karbasi:
The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization. CoRR abs/2002.11080 (2020) - [i52]Ruitu Xu, Lin Chen, Amin Karbasi:
Meta Learning in the Continuous Time Limit. CoRR abs/2006.10921 (2020) - [i51]Moran Feldman, Amin Karbasi:
Continuous Submodular Maximization: Beyond DR-Submodularity. CoRR abs/2006.11726 (2020) - [i50]Mohammad Fereydounian, Zebang Shen, Aryan Mokhtari, Amin Karbasi, Hamed Hassani:
Safe Learning under Uncertain Objectives and Constraints. CoRR abs/2006.13326 (2020) - [i49]Lin Chen, Yifei Min, Mikhail Belkin, Amin Karbasi:
Multiple Descent: Design Your Own Generalization Curve. CoRR abs/2008.01036 (2020) - [i48]Moran Feldman, Christopher Harshaw, Amin Karbasi:
Simultaneous Greedys: A Swiss Army Knife for Constrained Submodular Maximization. CoRR abs/2009.13998 (2020)
2010 – 2019
- 2019
- [c64]Soheil Ghili, Ehsan Kazemi
, Amin Karbasi:
Eliminating Latent Discrimination: Train Then Mask. AAAI 2019: 3672-3680 - [c63]Lin Chen, Mingrui Zhang, Amin Karbasi:
Projection-Free Bandit Convex Optimization. AISTATS 2019: 2047-2056 - [c62]Chris Harshaw, Moran Feldman, Justin Ward, Amin Karbasi:
Submodular Maximization beyond Non-negativity: Guarantees, Fast Algorithms, and Applications. ICML 2019: 2634-2643 - [c61]Ehsan Kazemi, Marko Mitrovic, Morteza Zadimoghaddam, Silvio Lattanzi, Amin Karbasi:
Submodular Streaming in All Its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity. ICML 2019: 3311-3320 - [c60]Marko Mitrovic, Ehsan Kazemi, Moran Feldman, Andreas Krause, Amin Karbasi:
Adaptive Sequence Submodularity. NeurIPS 2019: 5353-5364 - [c59]Mingrui Zhang, Lin Chen, Hamed Hassani, Amin Karbasi:
Online Continuous Submodular Maximization: From Full-Information to Bandit Feedback. NeurIPS 2019: 9206-9217 - [c58]Amin Karbasi, Hamed Hassani, Aryan Mokhtari, Zebang Shen:
Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match. NeurIPS 2019: 13066-13076 - [c57]Lin Chen, Moran Feldman, Amin Karbasi:
Unconstrained submodular maximization with constant adaptive complexity. STOC 2019: 102-113 - [i47]Lin Chen, Mingrui Zhang, Hamed Hassani, Amin Karbasi:
Black Box Submodular Maximization: Discrete and Continuous Settings. CoRR abs/1901.09515 (2019) - [i46]Marko Mitrovic, Ehsan Kazemi, Moran Feldman, Andreas Krause, Amin Karbasi:
Adaptive Sequence Submodularity. CoRR abs/1902.05981 (2019) - [i45]Mingrui Zhang, Lin Chen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
Quantized Frank-Wolfe: Communication-Efficient Distributed Optimization. CoRR abs/1902.06332 (2019) - [i44]Hamed Hassani, Amin Karbasi, Aryan Mokhtari, Zebang Shen:
Stochastic Conditional Gradient++. CoRR abs/1902.06992 (2019) - [i43]Christopher Harshaw, Moran Feldman, Justin Ward, Amin Karbasi:
Submodular Maximization Beyond Non-negativity: Guarantees, Fast Algorithms, and Applications. CoRR abs/1904.09354 (2019) - [i42]Ehsan Kazemi, Marko Mitrovic, Morteza Zadimoghaddam, Silvio Lattanzi, Amin Karbasi:
Submodular Streaming in All its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity. CoRR abs/1905.00948 (2019) - [i41]Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
One Sample Stochastic Frank-Wolfe. CoRR abs/1910.04322 (2019) - [i40]Hossein Esfandiari, Amin Karbasi, Abbas Mehrabian, Vahab S. Mirrokni:
Batched Multi-Armed Bandits with Optimal Regret. CoRR abs/1910.04959 (2019) - [i39]Lin Chen, Qian Yu, Hannah Lawrence, Amin Karbasi:
Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transition. CoRR abs/1910.10873 (2019) - [i38]Mingrui Zhang, Lin Chen, Hamed Hassani, Amin Karbasi:
Online Continuous Submodular Maximization: From Full-Information to Bandit Feedback. CoRR abs/1910.12424 (2019) - [i37]Hossein Esfandiari, Amin Karbasi, Vahab S. Mirrokni:
Adaptivity in Adaptive Submodularity. CoRR abs/1911.03620 (2019) - 2018
- [j10]Amin Karbasi, Amir Hesam Salavati
, Martin Vetterli:
Learning neural connectivity from firing activity: efficient algorithms with provable guarantees on topology. J. Comput. Neurosci. 44(2): 253-272 (2018) - [j9]Mehraveh Salehi
, Amin Karbasi, Xilin Shen
, Dustin Scheinost
, R. Todd Constable
:
An exemplar-based approach to individualized parcellation reveals the need for sex specific functional networks. NeuroImage 170: 54-67 (2018) - [c56]Marko Mitrovic, Moran Feldman, Andreas Krause, Amin Karbasi:
Submodularity on Hypergraphs: From Sets to Sequences. AISTATS 2018: 1177-1184 - [c55]Ehsan Kazemi, Lin Chen, Sanjoy Dasgupta, Amin Karbasi:
Comparison Based Learning from Weak Oracles. AISTATS 2018: 1849-1858 - [c54]Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap. AISTATS 2018: 1886-1895 - [c53]Lin Chen, Hamed Hassani, Amin Karbasi:
Online Continuous Submodular Maximization. AISTATS 2018: 1896-1905 - [c52]Lin Chen, Moran Feldman, Amin Karbasi:
Weakly Submodular Maximization Beyond Cardinality Constraints: Does Randomization Help Greedy? ICML 2018: 803-812 - [c51]Lin Chen, Christopher Harshaw, Hamed Hassani, Amin Karbasi:
Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity. ICML 2018: 813-822 - [c50]Ehsan Kazemi, Morteza Zadimoghaddam, Amin Karbasi:
Scalable Deletion-Robust Submodular Maximization: Data Summarization with Privacy and Fairness Constraints. ICML 2018: 2549-2558 - [c49]Marko Mitrovic, Ehsan Kazemi, Morteza Zadimoghaddam, Amin Karbasi:
Data Summarization at Scale: A Two-Stage Submodular Approach. ICML 2018: 3593-3602 - [c48]Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings. ICML 2018: 3613-3622 - [c47]Moran Feldman, Amin Karbasi, Ehsan Kazemi:
Do Less, Get More: Streaming Submodular Maximization with Subsampling. NeurIPS 2018: 730-740 - [i36]Lin Chen, Hamed Hassani, Amin Karbasi:
Online Continuous Submodular Maximization. CoRR abs/1802.06052 (2018) - [i35]Ehsan Kazemi, Lin Chen, Sanjoy Dasgupta, Amin Karbasi:
Comparison Based Learning from Weak Oracles. CoRR abs/1802.06942 (2018) - [i34]Moran Feldman, Amin Karbasi, Ehsan Kazemi:
Do Less, Get More: Streaming Submodular Maximization with Subsampling. CoRR abs/1802.07098 (2018) - [i33]Marko Mitrovic, Moran Feldman, Andreas Krause, Amin Karbasi:
Submodularity on Hypergraphs: From Sets to Sequences. CoRR abs/1802.09110 (2018) - [i32]Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization. CoRR abs/1804.09554 (2018) - [i31]Lin Chen, Mingrui Zhang, Amin Karbasi:
Projection-Free Bandit Convex Optimization. CoRR abs/1805.07474 (2018) - [i30]Marko Mitrovic, Ehsan Kazemi, Morteza Zadimoghaddam, Amin Karbasi:
Data Summarization at Scale: A Two-Stage Submodular Approach. CoRR abs/1806.02815 (2018) - [i29]Soheil Ghili, Ehsan Kazemi, Amin Karbasi:
Eliminating Latent Discrimination: Train Then Mask. CoRR abs/1811.04973 (2018) - [i28]Lin Chen, Moran Feldman, Amin Karbasi:
Unconstrained Submodular Maximization with Constant Adaptive Complexity. CoRR abs/1811.06603 (2018) - 2017
- [c46]Lin Chen, Seyed Hamed Hassani, Amin Karbasi:
Near-Optimal Active Learning of Halfspaces via Query Synthesis in the Noisy Setting. AAAI 2017: 1798-1804 - [c45]Moran Feldman, Christopher Harshaw, Amin Karbasi:
Greed Is Good: Near-Optimal Submodular Maximization via Greedy Optimization. COLT 2017: 758-784 - [c44]Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause:
Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten". ICML 2017: 2449-2458 - [c43]Marko Mitrovic, Mark Bun, Andreas Krause, Amin Karbasi:
Differentially Private Submodular Maximization: Data Summarization in Disguise. ICML 2017: 2478-2487 - [c42]Serban Stan, Morteza Zadimoghaddam, Andreas Krause, Amin Karbasi:
Probabilistic Submodular Maximization in Sub-Linear Time. ICML 2017: 3241-3250 - [c41]Mehraveh Salehi
, Amin Karbasi, Dustin Scheinost, R. Todd Constable
:
A Submodular Approach to Create Individualized Parcellations of the Human Brain. MICCAI (1) 2017: 478-485 - [c40]Lin Chen, Andreas Krause, Amin Karbasi:
Interactive Submodular Bandit. NIPS 2017: 141-152 - [c39]Ethan R. Elenberg, Alexandros G. Dimakis, Moran Feldman, Amin Karbasi:
Streaming Weak Submodularity: Interpreting Neural Networks on the Fly. NIPS 2017: 4044-4054 - [c38]S. Hamed Hassani, Mahdi Soltanolkotabi
, Amin Karbasi:
Gradient Methods for Submodular Maximization. NIPS 2017: 5841-5851 - [c37]Lin Chen, Forrest W. Crawford, Amin Karbasi:
Submodular Variational Inference for Network Reconstruction. UAI 2017 - [i27]Ethan R. Elenberg, Alexandros G. Dimakis, Moran Feldman, Amin Karbasi:
Streaming Weak Submodularity: Interpreting Neural Networks on the Fly. CoRR abs/1703.02647 (2017) - [i26]Moran Feldman, Christopher Harshaw, Amin Karbasi:
Greed is Good: Near-Optimal Submodular Maximization via Greedy Optimization. CoRR abs/1704.01652 (2017) - [i25]Lin Chen, Moran Feldman, Amin Karbasi:
Weakly Submodular Maximization Beyond Cardinality Constraints: Does Randomization Help Greedy? CoRR abs/1707.04347 (2017) - [i24]S. Hamed Hassani, Mahdi Soltanolkotabi, Amin Karbasi:
Gradient Methods for Submodular Maximization. CoRR abs/1708.03949 (2017) - [i23]Aryan Mokhtari, S. Hamed Hassani, Amin Karbasi:
Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap. CoRR abs/1711.01660 (2017) - [i22]Ehsan Kazemi, Morteza Zadimoghaddam, Amin Karbasi:
Deletion-Robust Submodular Maximization at Scale. CoRR abs/1711.07112 (2017) - 2016
- [j8]Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause:
Distributed Submodular Maximization. J. Mach. Learn. Res. 17: 238:1-238:44 (2016) - [c36]Lin Chen, Forrest W. Crawford, Amin Karbasi:
Seeing the Unseen Network: Inferring Hidden Social Ties from Respondent-Driven Sampling. AAAI 2016: 1174-1180 - [c35]Amin Karbasi, Amir Hesam Salavati, Martin Vetterli:
Learning network structures from firing patterns. ICASSP 2016: 699-703 - [c34]Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi:
Fast Constrained Submodular Maximization: Personalized Data Summarization. ICML 2016: 1358-1367 - [c33]Lin Chen, Amin Karbasi, Forrest W. Crawford:
Estimating the Size of a Large Network and its Communities from a Random Sample. NIPS 2016: 3072-3080 - [c32]Baharan Mirzasoleiman, Morteza Zadimoghaddam, Amin Karbasi:
Fast Distributed Submodular Cover: Public-Private Data Summarization. NIPS 2016: 3594-3602 - [i21]Lin Chen, S. Hamed Hassani, Amin Karbasi:
Dimension Coupling: Optimal Active Learning of Halfspaces via Query Synthesis. CoRR abs/1603.03515 (2016) - [i20]Lin Chen, Amin Karbasi, Forrest W. Crawford:
Submodular Variational Inference for Network Reconstruction. CoRR abs/1603.08616 (2016) - [i19]Mario Lucic, Mesrob I. Ohannessian, Amin Karbasi, Andreas Krause:
Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning. CoRR abs/1605.00529 (2016) - [i18]Lin Chen, Amin Karbasi, Forrest W. Crawford:
Estimating the Size of a Large Network and its Communities from a Random Sample. CoRR abs/1610.08473 (2016) - 2015
- [j7]Amin Karbasi, Stratis Ioannidis
, Laurent Massoulié:
From Small-World Networks to Comparison-Based Search. IEEE Trans. Inf. Theory 61(6): 3056-3074 (2015) - [c31]Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi, Jan Vondrák, Andreas Krause:
Lazier Than Lazy Greedy. AAAI 2015: 1812-1818 - [c30]Yuxin Chen, Shervin Javdani, Amin Karbasi, J. Andrew Bagnell, Siddhartha S. Srinivasa, Andreas Krause:
Submodular Surrogates for Value of Information. AAAI 2015: 3511-3518 - [c29]Mario Lucic, Mesrob I. Ohannessian, Amin Karbasi, Andreas Krause:
Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning. AISTATS 2015 - [c28]Yuxin Chen, S. Hamed Hassani, Amin Karbasi, Andreas Krause:
Sequential Information Maximization: When is Greedy Near-optimal? COLT 2015: 338-363 - [c27]Patrick Rebeschini, Amin Karbasi:
Fast Mixing for Discrete Point Processes. COLT 2015: 1480-1500 - [c26]Amin Karbasi, Johannes Lengler
, Angelika Steger:
Normalization Phenomena in Asynchronous Networks. ICALP (2) 2015: 688-700 - [c25]Alkis Gotovos, Amin Karbasi, Andreas Krause:
Non-Monotone Adaptive Submodular Maximization. IJCAI 2015: 1996-2003 - [c24]Saeid Haghighatshoar, Amin Karbasi, Amir Hesam Salavati:
Asynchronous decoding of LDPC codes over BEC. ISIT 2015: 2678-2682 - [c23]Baharan Mirzasoleiman, Amin Karbasi, Ashwinkumar Badanidiyuru, Andreas Krause:
Distributed Submodular Cover: Succinctly Summarizing Massive Data. NIPS 2015: 2881-2889 - [i17]Lin Chen, Forrest W. Crawford, Amin Karbasi:
Seeing the Unseen Network: Inferring Hidden Social Ties from Respondent-Driven Sampling. CoRR abs/1511.04137 (2015) - 2014
- [j6]Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi, Lav R. Varshney:
Noise Facilitation in Associative Memories of Exponential Capacity. Neural Comput. 26(11): 2493-2526 (2014) - [c22]Shervin Javdani, Yuxin Chen, Amin Karbasi, Andreas Krause, Drew Bagnell, Siddhartha S. Srinivasa:
Near Optimal Bayesian Active Learning for Decision Making. AISTATS 2014: 430-438 - [c21]Adish Singla
, Ilija Bogunovic, Gábor Bartók, Amin Karbasi, Andreas Krause:
Near-Optimally Teaching the Crowd to Classify. ICML 2014: 154-162 - [c20]Ashwinkumar Badanidiyuru, Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause:
Streaming submodular maximization: massive data summarization on the fly. KDD 2014: 671-680 - [i16]Adish Singla, Ilija Bogunovic, Gábor Bartók, Amin Karbasi, Andreas Krause:
Near-Optimally Teaching the Crowd to Classify. CoRR abs/1402.2092 (2014) - [i15]Shervin Javdani, Yuxin Chen, Amin Karbasi, Andreas Krause, J. Andrew Bagnell, Siddhartha S. Srinivasa:
Near Optimal Bayesian Active Learning for Decision Making. CoRR abs/1402.5886 (2014) - [i14]Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi, Lav R. Varshney:
Noise Facilitation in Associative Memories of Exponential Capacity. CoRR abs/1403.3305 (2014) - [i13]Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi:
Convolutional Neural Associative Memories: Massive Capacity with Noise Tolerance. CoRR abs/1407.6513 (2014) - [i12]Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi, Jan Vondrák, Andreas Krause:
Lazier Than Lazy Greedy. CoRR abs/1409.7938 (2014) - [i11]Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause:
Distributed Submodular Maximization. CoRR abs/1411.0541 (2014) - 2013
- [j5]Amin Karbasi, Sewoong Oh:
Robust Localization From Incomplete Local Information. IEEE/ACM Trans. Netw. 21(4): 1131-1144 (2013) - [j4]Reza Parhizkar, Amin Karbasi, Sewoong Oh, Martin Vetterli
:
Calibration Using Matrix Completion With Application to Ultrasound Tomography. IEEE Trans. Signal Process. 61(20): 4923-4933 (2013) - [c19]Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi:
Iterative Learning and Denoising in Convolutional Neural Associative Memories. ICML (1) 2013: 445-453 - [c18]Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi:
Coupled neural associative memories. ITW 2013: 1-5 - [c17]Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi, Lav R. Varshney:
Noise-Enhanced Associative Memories. NIPS 2013: 1682-1690 - [c16]Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause:
Distributed Submodular Maximization: Identifying Representative Elements in Massive Data. NIPS 2013: 2049-2057 - [c15]Amin Karbasi, Morteza Zadimoghaddam:
Constrained Binary Identification Problem. STACS 2013: 550-561 - [i10]Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi:
Coupled Neural Associative Memories. CoRR abs/1301.1555 (2013) - 2012
- [b1]Amin Karbasi:
Graph-Based Information Processing - Scaling Laws and Applications. EPFL, Switzerland, 2012 - [j3]Mahdi Cheraghchi
, Amin Karbasi, Soheil Mohajer
, Venkatesh Saligrama
:
Graph-Constrained Group Testing. IEEE Trans. Inf. Theory 58(1): 248-262 (2012) - [j2]Arash Amini, Amin Karbasi, Farokh Marvasti:
Low-Rank Matrix Approximation Using Point-Wise Operators. IEEE Trans. Inf. Theory 58(1): 302-310 (2012) - [c14]Amin Karbasi, Stratis Ioannidis, Laurent Massoulié:
Comparison-Based Learning with Rank Nets. ICML 2012 - [c13]Amir Hesam Salavati, Amin Karbasi:
Multi-level error-resilient neural networks. ISIT 2012: 1064-1068 - [c12]Amin Karbasi, Stratis Ioannidis
, Laurent Massoulié:
Hot or not: Interactive content search using comparisons. ITA 2012: 291-297 - [c11]Amin Karbasi, Morteza Zadimoghaddam:
Sequential group testing with graph constraints. ITW 2012: 292-296 - [i9]Amir Hesam Salavati, Amin Karbasi:
Multi-Level Error-Resilient Neural Networks with Learning. CoRR abs/1202.2770 (2012) - [i8]Amin Karbasi, Stratis Ioannidis, Laurent Massoulié:
Comparison-Based Learning with Rank Nets. CoRR abs/1206.4674 (2012) - 2011
- [j1]Mahdi Cheraghchi
, Ali Hormati, Amin Karbasi, Martin Vetterli
:
Group Testing With Probabilistic Tests: Theory, Design and Application. IEEE Trans. Inf. Theory 57(10): 7057-7067 (2011) - [c10]Amin Karbasi, Stratis Ioannidis
, Laurent Massoulié:
Content Search through Comparisons. ICALP (2) 2011: 601-612 - [c9]Reza Parhizkar, Amin Karbasi, Martin Vetterli
:
Calibration in circular ultrasound tomography devices. ICASSP 2011: 549-552 - [c8]Amin Karbasi, Morteza Zadimoghaddam:
Compression with graphical constraints: An interactive browser. ISIT 2011: 953-957 - [i7]Amin Karbasi, Stratis Ioannidis, Laurent Massoulié:
Adaptive Content Search Through Comparisons. CoRR abs/1107.3059 (2011) - [i6]Amin Karbasi, Sewoong Oh:
Robust Localization from Incomplete Local Information. CoRR abs/1110.3018 (2011) - 2010
- [c7]Mahdi Cheraghchi
, Amin Karbasi, Soheil Mohajer, Venkatesh Saligrama
:
Graph-constrained group testing. ISIT 2010: 1913-1917 - [c6]Amin Karbasi:
From centralized to distributed sensor localization. S3@MobiCom 2010: 5-8 - [c5]Amin Karbasi, Sewoong Oh:
Distributed sensor network localization from local connectivity: performance analysis for the HOP-TERRAIN algorithm. SIGMETRICS 2010: 61-70 - [i5]Mahdi Cheraghchi, Amin Karbasi, Soheil Mohajer, Venkatesh Saligrama:
Graph-Constrained Group Testing. CoRR abs/1001.1445 (2010) - [i4]Mahdi Cheraghchi, Ali Hormati, Amin Karbasi, Martin Vetterli:
Group Testing with Probabilistic Tests: Theory, Design and Application. CoRR abs/1009.3186 (2010) - [i3]Reza Parhizkar, Amin Karbasi, Sewoong Oh, Martin Vetterli:
Calibration for Ultrasound Breast Tomography Using Matrix Completion. CoRR abs/1012.4928 (2010)
2000 – 2009
- 2009
- [c4]Mahdi Cheraghchi
, Ali Hormati, Amin Karbasi, Martin Vetterli
:
Compressed sensing with probabilistic measurements: A group testing solution. Allerton 2009: 30-35 - [c3]Amin Karbasi, Ali Hormati, Soheil Mohajer, Martin Vetterli
:
Support recovery in compressed sensing: An estimation theoretic approach. ISIT 2009: 679-683 - [i2]Mahdi Cheraghchi, Ali Hormati, Amin Karbasi, Martin Vetterli:
Compressed Sensing with Probabilistic Measurements: A Group Testing Solution. CoRR abs/0909.3508 (2009) - [i1]Ali Hormati, Amin Karbasi, Soheil Mohajer, Martin Vetterli:
An Estimation Theoretic Approach for Sparsity Pattern Recovery in the Noisy Setting. CoRR abs/0911.4880 (2009) - 2007
- [c2]Amin Karbasi, Akihiko Sugiyama:
A new DOA estimation method using a circular microphone array. EUSIPCO 2007: 778-782 - 2006
- [c1]Amin Karbasi, Akihiko Sugiyama:
A DOA estimation method for an arbitrary triangular microphone arrangement. EUSIPCO 2006: 1-5
Coauthor Index
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