Karbasi, Amin

109 publications

ICML 2025 Adversarial Reasoning at Jailbreaking Time Mahdi Sabbaghi, Paul Kassianik, George J. Pappas, Amin Karbasi, Hamed Hassani

ICLRW 2025 ClusterGen: Token Generation in Sublinear Time and Memory with Clustering KV Cache Amir Zandieh, Insu Han, Amin Karbasi, Vahab Mirrokni

ICLR 2025 Intelligence at the Edge of Chaos Shiyang Zhang, Aakash Patel, Syed A Rizvi, Nianchen Liu, Sizhuang He, Amin Karbasi, Emanuele Zappala, David van Dijk

NeurIPS 2025 On Union-Closedness of Language Generation Steve Hanneke, Amin Karbasi, Anay Mehrotra, Grigoris Velegkas

ICML 2025 Procurement Auctions via Approximately Optimal Submodular Optimization Yuan Deng, Amin Karbasi, Vahab Mirrokni, Renato Paes Leme, Grigoris Velegkas, Song Zuo

NeurIPS 2025 Risk-Averse Constrained Reinforcement Learning with Optimized Certainty Equivalents Jane H. Lee, Baturay Saglam, Spyridon Pougkakiotis, Amin Karbasi, Dionysis Kalogerias

ICLRW 2025 Working Memory Attack on LLMs Bibek Upadhayay, Vahid Behzadan, Amin Karbasi

ICML 2024 Cell2Sentence: Teaching Large Language Models the Language of Biology Daniel Levine, Syed A 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

ICLR 2024 HyperAttention: Long-Context Attention in Near-Linear Time Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David Woodruff, Amir Zandieh

NeurIPS 2024 Injecting Undetectable Backdoors in Obfuscated Neural Networks and Language Models Alkis Kalavasis, Amin Karbasi, Argyris Oikonomou, Katerina Sotiraki, Grigoris Velegkas, Manolis Zampetakis

ICMLW 2024 Learning Task Representations from In-Context Learning Baturay Saglam, Zhuoran Yang, Dionysis Kalogerias, Amin Karbasi

NeurIPS 2024 On the Computational Landscape of Replicable Learning Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas, Felix Zhou

ICLR 2024 Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning Patrik Okanovic, Roger Waleffe, Vasilis Mageirakos, Konstantinos Nikolakakis, Amin Karbasi, Dionysios Kalogerias, Nezihe Merve Gürel, Theodoros Rekatsinas

ICML 2024 Replicable Learning of Large-Margin Halfspaces Alkis Kalavasis, Amin Karbasi, Kasper Green Larsen, Grigoris Velegkas, Felix Zhou

AISTATS 2024 Submodular Minimax Optimization: Finding Effective Sets Loay Raed Mualem, Ethan R Elenberg, Moran Feldman, Amin Karbasi

NeurIPS 2024 TSDS: Data Selection for Task-Specific Model Finetuning Zifan Liu, Amin Karbasi, Theodoros Rekatsinas

ALT 2024 The Impossibility of Parallelizing Boosting Amin Karbasi, Kasper Green Larsen

NeurIPS 2024 Tree of Attacks: Jailbreaking Black-Box LLMs Automatically Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, Blaine Nelson, Hyrum Anderson, Yaron Singer, Amin Karbasi

ICMLW 2024 Tree of Attacks: Jailbreaking Black-Box LLMs Automatically Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, Blaine Nelson, Hyrum S Anderson, Yaron Singer, Amin Karbasi

NeurIPS 2024 Universal Rates for Active Learning Steve Hanneke, Amin Karbasi, Shay Moran, Grigoris Velegkas

COLT 2024 Universal Rates for Regression: Separations Between Cut-Off and Absolute Loss Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas

ICLR 2023 Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD Konstantinos Nikolakakis, Farzin Haddadpour, Amin Karbasi, Dionysios Kalogerias

AISTATS 2023 Exact Gradient Computation for Spiking Neural Networks via Forward Propagation Jane H. Lee, Saeid Haghighatshoar, Amin Karbasi

JMLR 2023 How Do You Want Your Greedy: Simultaneous or Repeated? Moran Feldman, Christopher Harshaw, Amin Karbasi

ICML 2023 KDEformer: Accelerating Transformers via Kernel Density Estimation Amir Zandieh, Insu Han, Majid Daliri, Amin Karbasi

ICML 2023 Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning Amin Karbasi, Nikki Lijing Kuang, Yian Ma, Siddharth Mitra

NeurIPS 2023 Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization Liang Zhang, Junchi Yang, Amin Karbasi, Niao He

NeurIPS 2023 Optimal Learners for Realizable Regression: PAC Learning and Online Learning Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas

NeurIPS 2023 Replicability in Reinforcement Learning Amin Karbasi, Grigoris Velegkas, Lin Yang, Felix Zhou

ICLR 2023 Replicable Bandits Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni, Grigoris Velegkas

NeurIPS 2023 Replicable Clustering Hossein Esfandiari, Amin Karbasi, Vahab Mirrokni, Grigoris Velegkas, Felix Zhou

ICML 2023 Statistical Indistinguishability of Learning Algorithms Alkis Kalavasis, Amin Karbasi, Shay Moran, Grigoris Velegkas

AISTATS 2022 Federated Functional Gradient Boosting Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi

NeurIPS 2022 Black-Box Generalization: Stability of Zeroth-Order Learning Konstantinos Nikolakakis, Farzin Haddadpour, Dionysis Kalogerias, Amin Karbasi

NeurIPSW 2022 Exact Gradient Computation for Spiking Neural Networks Jane Lee, Saeid Haghighatshoar, Amin Karbasi

NeurIPS 2022 Fast Neural Kernel Embeddings for General Activations Insu Han, Amir Zandieh, Jaehoon Lee, Roman Novak, Lechao Xiao, Amin Karbasi

ICLR 2022 Learning Distributionally Robust Models at Scale via Composite Optimization Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Amin Karbasi

NeurIPS 2022 Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes Alkis Kalavasis, Grigoris Velegkas, Amin Karbasi

NeurIPS 2022 On Optimal Learning Under Targeted Data Poisoning Steve Hanneke, Amin Karbasi, Mohammad Mahmoody, Idan Mehalel, Shay Moran

NeurIPS 2022 Reinforcement Learning with Logarithmic Regret and Policy Switches Grigoris Velegkas, Zhuoran Yang, Amin Karbasi

ICML 2022 Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes Insu Han, Mike Gartrell, Elvis Dohmatob, Amin Karbasi

ICLR 2022 Scalable Sampling for Nonsymmetric Determinantal Point Processes Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, Amin Karbasi

COLT 2022 Self-Consistency of the Fokker Planck Equation Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani

NeurIPS 2022 Submodular Maximization in Clean Linear Time Wenxin Li, Moran Feldman, Ehsan Kazemi, Amin Karbasi

NeurIPS 2022 Universal Rates for Interactive Learning Steve Hanneke, Amin Karbasi, Shay Moran, Grigoris Velegkas

AISTATS 2021 Meta Learning in the Continuous Time Limit Ruitu Xu, Lin Chen, Amin Karbasi

COLT 2021 Adaptivity in Adaptive Submodularity Hossein Esfandiari, Amin Karbasi, Vahab Mirrokni

NeurIPS 2021 An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks Shashank Rajput, Kartik Sreenivasan, Dimitris Papailiopoulos, Amin Karbasi

UAI 2021 Learning and Certification Under Instance-Targeted Poisoning Ji Gao, Amin Karbasi, Mohammad Mahmoody

NeurIPS 2021 Multiple Descent: Design Your Own Generalization Curve Lin Chen, Yifei Min, Mikhail Belkin, Amin Karbasi

NeurIPS 2021 Parallelizing Thompson Sampling Amin Karbasi, Vahab Mirrokni, Mohammad Shadravan

AAAI 2021 Regret Bounds for Batched Bandits Hossein Esfandiari, Amin Karbasi, Abbas Mehrabian, Vahab S. Mirrokni

ICML 2021 Regularized Submodular Maximization at Scale Ehsan Kazemi, Shervin Minaee, Moran Feldman, Amin Karbasi

NeurIPS 2021 Submodular + Concave Siddharth Mitra, Moran Feldman, Amin Karbasi

UAI 2021 The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization Yifei Min, Lin Chen, Amin Karbasi

AISTATS 2020 Black Box Submodular Maximization: Discrete and Continuous Settings Lin Chen, Mingrui Zhang, Hamed Hassani, Amin Karbasi

NeurIPS 2020 Continuous Submodular Maximization: Beyond DR-Submodularity Moran Feldman, Amin Karbasi

NeurIPS 2020 Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transition Lin Chen, Qian Yu, Hannah Lawrence, Amin Karbasi

ICML 2020 More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi

AISTATS 2020 One Sample Stochastic Frank-Wolfe Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi

NeurIPS 2020 Online MAP Inference of Determinantal Point Processes Aditya Bhaskara, Amin Karbasi, Silvio Lattanzi, Morteza Zadimoghaddam

AISTATS 2020 Quantized Frank-Wolfe: Faster Optimization, Lower Communication, and Projection Free Mingrui Zhang, Lin Chen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi

JMLR 2020 Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization Aryan Mokhtari, Hamed Hassani, Amin Karbasi

ICML 2020 Streaming Submodular Maximization Under a K-Set System Constraint Ran Haba, Ehsan Kazemi, Moran Feldman, Amin Karbasi

NeurIPS 2020 Submodular Maximization Through Barrier Functions Ashwinkumar Badanidiyuru, Amin Karbasi, Ehsan Kazemi, Jan Vondrak

NeurIPS 2019 Adaptive Sequence Submodularity Marko Mitrovic, Ehsan Kazemi, Moran Feldman, Andreas Krause, Amin Karbasi

AAAI 2019 Eliminating Latent Discrimination: Train Then Mask Soheil Ghili, Ehsan Kazemi, Amin Karbasi

NeurIPS 2019 Online Continuous Submodular Maximization: From Full-Information to Bandit Feedback Mingrui Zhang, Lin Chen, Hamed Hassani, Amin Karbasi

AISTATS 2019 Projection-Free Bandit Convex Optimization Lin Chen, Mingrui Zhang, Amin Karbasi

NeurIPS 2019 Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match Amin Karbasi, Hamed Hassani, Aryan Mokhtari, Zebang Shen

ICML 2019 Submodular Maximization Beyond Non-Negativity: Guarantees, Fast Algorithms, and Applications Chris Harshaw, Moran Feldman, Justin Ward, Amin Karbasi

ICML 2019 Submodular Streaming in All Its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity Ehsan Kazemi, Marko Mitrovic, Morteza Zadimoghaddam, Silvio Lattanzi, Amin Karbasi

AISTATS 2018 Comparison Based Learning from Weak Oracles Ehsan Kazemi, Lin Chen, Sanjoy Dasgupta, Amin Karbasi

AISTATS 2018 Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap Aryan Mokhtari, Hamed Hassani, Amin Karbasi

ICML 2018 Data Summarization at Scale: A Two-Stage Submodular Approach Marko Mitrovic, Ehsan Kazemi, Morteza Zadimoghaddam, Amin Karbasi

ICML 2018 Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings Aryan Mokhtari, Hamed Hassani, Amin Karbasi

NeurIPS 2018 Do Less, Get More: Streaming Submodular Maximization with Subsampling Moran Feldman, Amin Karbasi, Ehsan Kazemi

AISTATS 2018 Online Continuous Submodular Maximization Lin Chen, Hamed Hassani, Amin Karbasi

ICML 2018 Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity Lin Chen, Christopher Harshaw, Hamed Hassani, Amin Karbasi

ICML 2018 Scalable Deletion-Robust Submodular Maximization: Data Summarization with Privacy and Fairness Constraints Ehsan Kazemi, Morteza Zadimoghaddam, Amin Karbasi

AISTATS 2018 Submodularity on Hypergraphs: From Sets to Sequences Marko Mitrovic, Moran Feldman, Andreas Krause, Amin Karbasi

ICML 2018 Weakly Submodular Maximization Beyond Cardinality Constraints: Does Randomization Help Greedy? Lin Chen, Moran Feldman, Amin Karbasi

ICML 2017 Deletion-Robust Submodular Maximization: Data Summarization with “the Right to Be Forgotten” Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause

ICML 2017 Differentially Private Submodular Maximization: Data Summarization in Disguise Marko Mitrovic, Mark Bun, Andreas Krause, Amin Karbasi

NeurIPS 2017 Gradient Methods for Submodular Maximization Hamed Hassani, Mahdi Soltanolkotabi, Amin Karbasi

COLT 2017 Greed Is Good: Near-Optimal Submodular Maximization via Greedy Optimization Moran Feldman, Christopher Harshaw, Amin Karbasi

NeurIPS 2017 Interactive Submodular Bandit Lin Chen, Andreas Krause, Amin Karbasi

AAAI 2017 Near-Optimal Active Learning of Halfspaces via Query Synthesis in the Noisy Setting Lin Chen, Seyed Hamed Hassani, Amin Karbasi

ICML 2017 Probabilistic Submodular Maximization in Sub-Linear Time Serban Stan, Morteza Zadimoghaddam, Andreas Krause, Amin Karbasi

NeurIPS 2017 Streaming Weak Submodularity: Interpreting Neural Networks on the Fly Ethan Elenberg, Alexandros G Dimakis, Moran Feldman, Amin Karbasi

UAI 2017 Submodular Variational Inference for Network Reconstruction Lin Chen, Forrest W. Crawford, Amin Karbasi

JMLR 2016 Distributed Submodular Maximization Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause

NeurIPS 2016 Estimating the Size of a Large Network and Its Communities from a Random Sample Lin Chen, Amin Karbasi, Forrest W. Crawford

ICML 2016 Fast Constrained Submodular Maximization: Personalized Data Summarization Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi

NeurIPS 2016 Fast Distributed Submodular Cover: Public-Private Data Summarization Baharan Mirzasoleiman, Morteza Zadimoghaddam, Amin Karbasi

AAAI 2016 Seeing the Unseen Network: Inferring Hidden Social Ties from Respondent-Driven Sampling Lin Chen, Forrest W. Crawford, Amin Karbasi

NeurIPS 2015 Distributed Submodular Cover: Succinctly Summarizing Massive Data Baharan Mirzasoleiman, Amin Karbasi, Ashwinkumar Badanidiyuru, Andreas Krause

COLT 2015 Fast Mixing for Discrete Point Processes Patrick Rebeschini, Amin Karbasi

AAAI 2015 Lazier than Lazy Greedy Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi, Jan Vondrák, Andreas Krause

IJCAI 2015 Non-Monotone Adaptive Submodular Maximization Alkis Gotovos, Amin Karbasi, Andreas Krause

COLT 2015 Sequential Information Maximization: When Is Greedy Near-Optimal? Yuxin Chen, S. Hamed Hassani, Amin Karbasi, Andreas Krause

AAAI 2015 Submodular Surrogates for Value of Information Yuxin Chen, Shervin Javdani, Amin Karbasi, J. Andrew Bagnell, Siddhartha S. Srinivasa, Andreas Krause

AISTATS 2015 Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning Mario Lucic, Mesrob I. Ohannessian, Amin Karbasi, Andreas Krause

AISTATS 2014 Near Optimal Bayesian Active Learning for Decision Making Shervin Javdani, Yuxin Chen, Amin Karbasi, Andreas Krause, Drew Bagnell, Siddhartha S. Srinivasa

ICML 2014 Near-Optimally Teaching the Crowd to Classify Adish Singla, Ilija Bogunovic, Gabor Bartok, Amin Karbasi, Andreas Krause

NeurIPS 2013 Distributed Submodular Maximization: Identifying Representative Elements in Massive Data Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause

ICML 2013 Iterative Learning and Denoising in Convolutional Neural Associative Memories Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi

NeurIPS 2013 Noise-Enhanced Associative Memories Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi, Lav R. Varshney

ICML 2012 Comparison-Based Learning with Rank Nets Amin Karbasi, Stratis Ioannidis, Laurent Massoulié