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ORCIDAmin Karbasi
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2020 – today
- 2024
[c116]Loay Raed Mualem, Ethan R. Elenberg, Moran Feldman, Amin Karbasi:
Submodular Minimax Optimization: Finding Effective Sets. AISTATS 2024: 1081-1089- [c115]Amin Karbasi, Kasper Green Larsen:
The Impossibility of Parallelizing Boosting. ALT 2024: 635-653 - [c114]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 - [c113]Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh:
HyperAttention: Long-context Attention in Near-Linear Time. ICLR 2024 - [c112]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 - [c111]Alkis Kalavasis, Amin Karbasi, Kasper Green Larsen, Grigoris Velegkas, Felix Zhou:
Replicable Learning of Large-Margin Halfspaces. ICML 2024 - [c110]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:
Cell2Sentence: Teaching Large Language Models the Language of Biology. ICML 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]