A DOA estimation method for an arbitrary triangular microphone arrangement. - Amin Karbasi; Akihiko Sugiyama (EUSIPCO, 2006)

A new DOA estimation method using a circular microphone array. - Amin Karbasi; Akihiko Sugiyama (EUSIPCO, 2007)

Compressed sensing with probabilistic measurements: A group testing solution. - Mahdi Cheraghchi; Ali Hormati; Amin Karbasi; Martin Vetterli (Allerton, 2009)

Support recovery in compressed sensing: An estimation theoretic approach. - Amin Karbasi; Ali Hormati; Soheil Mohajer; Martin Vetterli (ISIT, 2009)

An Estimation Theoretic Approach for Sparsity Pattern Recovery in the Noisy Setting - Ali Hormati; Amin Karbasi; Soheil Mohajer; Martin Vetterli (CoRR, 2009)

From centralized to distributed sensor localization. - Amin Karbasi (S3@MobiCom, 2010)

Distributed sensor network localization from local connectivity: performance analysis for the HOP-TERRAIN algorithm. - Amin Karbasi; Sewoong Oh (SIGMETRICS, 2010)

Calibration for Ultrasound Breast Tomography Using Matrix Completion - Reza Parhizkar; Amin Karbasi; Sewoong Oh; Martin Vetterli (CoRR, 2010)

Content Search through Comparisons. - Amin Karbasi; Stratis Ioannidis; Laurent Massoulié (ICALP (2), 2011)

Calibration in circular ultrasound tomography devices. - Reza Parhizkar; Amin Karbasi; Martin Vetterli (ICASSP, 2011)

Compression with graphical constraints: An interactive browser. - Amin Karbasi; Morteza Zadimoghaddam (ISIT, 2011)

Adaptive Content Search Through Comparisons - Amin Karbasi; Stratis Ioannidis; Laurent Massoulié (CoRR, 2011)

Group Testing With Probabilistic Tests: Theory, Design and Application. - Mahdi Cheraghchi; Ali Hormati; Amin Karbasi; Martin Vetterli (IEEE Trans. Inf. Theory, 2011)

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

Multi-level error-resilient neural networks. - Amir Hesam Salavati; Amin Karbasi (ISIT, 2012)

Hot or not: Interactive content search using comparisons. - Amin Karbasi; Stratis Ioannidis; Laurent Massoulié (ITA, 2012)

Sequential group testing with graph constraints. - Amin Karbasi; Morteza Zadimoghaddam (ITW, 2012)

Multi-Level Error-Resilient Neural Networks with Learning - Amir Hesam Salavati; Amin Karbasi (CoRR, 2012)

Low-Rank Matrix Approximation Using Point-Wise Operators. - Arash Amini; Amin Karbasi; Farokh Marvasti (IEEE Trans. Inf. Theory, 2012)

Graph-Constrained Group Testing. - Mahdi Cheraghchi; Amin Karbasi; Soheil Mohajer; Venkatesh Saligrama (IEEE Trans. Inf. Theory, 2012)

Graph-Based Information Processing - Scaling Laws and Applications. - Amin Karbasi (2012)

Iterative Learning and Denoising in Convolutional Neural Associative Memories. - Amin Karbasi; Amir Hesam Salavati; Amin Shokrollahi (ICML (1), 2013)

Coupled neural associative memories. - Amin Karbasi; Amir Hesam Salavati; Amin Shokrollahi (ITW, 2013)

Noise-Enhanced Associative Memories. - Amin Karbasi; Amir Hesam Salavati; Amin Shokrollahi; Lav R. Varshney (NIPS, 2013)

Distributed Submodular Maximization: Identifying Representative Elements in Massive Data. - Baharan Mirzasoleiman; Amin Karbasi; Rik Sarkar; Andreas Krause 001 (NIPS, 2013)

Constrained Binary Identification Problem. - Amin Karbasi; Morteza Zadimoghaddam (STACS, 2013)

Robust Localization From Incomplete Local Information. - Amin Karbasi; Sewoong Oh (IEEE/ACM Trans. Netw., 2013)

Calibration Using Matrix Completion With Application to Ultrasound Tomography. - Reza Parhizkar; Amin Karbasi; Sewoong Oh; Martin Vetterli (IEEE Trans. Signal Process., 2013)

Near Optimal Bayesian Active Learning for Decision Making. - Shervin Javdani; Yuxin Chen 001; Amin Karbasi; Andreas Krause 001; Drew Bagnell; Siddhartha S. Srinivasa (AISTATS, 2014)

Near-Optimally Teaching the Crowd to Classify. - Adish Singla; Ilija Bogunovic; Gábor Bartók; Amin Karbasi; Andreas Krause 001 (ICML, 2014)

Streaming submodular maximization: massive data summarization on the fly. - Ashwinkumar Badanidiyuru; Baharan Mirzasoleiman; Amin Karbasi; Andreas Krause 001 (KDD, 2014)

Convolutional Neural Associative Memories: Massive Capacity with Noise Tolerance. - Amin Karbasi; Amir Hesam Salavati; Amin Shokrollahi (CoRR, 2014)

Noise Facilitation in Associative Memories of Exponential Capacity. - Amin Karbasi; Amir Hesam Salavati; Amin Shokrollahi; Lav R. Varshney (Neural Comput., 2014)

Submodular Surrogates for Value of Information. - Yuxin Chen 001; Shervin Javdani; Amin Karbasi; J. Andrew Bagnell; Siddhartha S. Srinivasa; Andreas Krause 001 (AAAI, 2015)

Lazier Than Lazy Greedy. - Baharan Mirzasoleiman; Ashwinkumar Badanidiyuru; Amin Karbasi; Jan Vondrák; Andreas Krause 001 (AAAI, 2015)

Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning. - Mario Lucic; Mesrob I. Ohannessian; Amin Karbasi; Andreas Krause 001 (AISTATS, 2015)

Sequential Information Maximization: When is Greedy Near-optimal? - Yuxin Chen 001; S. Hamed Hassani; Amin Karbasi; Andreas Krause 001 (COLT, 2015)

Fast Mixing for Discrete Point Processes. - Patrick Rebeschini; Amin Karbasi (COLT, 2015)

Normalization Phenomena in Asynchronous Networks. - Amin Karbasi; Johannes Lengler; Angelika Steger (ICALP (2), 2015)

Non-Monotone Adaptive Submodular Maximization. - Alkis Gotovos; Amin Karbasi; Andreas Krause 001 (IJCAI, 2015)

Asynchronous decoding of LDPC codes over BEC. - Saeid Haghighatshoar; Amin Karbasi; Amir Hesam Salavati (ISIT, 2015)

Distributed Submodular Cover: Succinctly Summarizing Massive Data. - Baharan Mirzasoleiman; Amin Karbasi; Ashwinkumar Badanidiyuru; Andreas Krause 001 (NIPS, 2015)

From Small-World Networks to Comparison-Based Search. - Amin Karbasi; Stratis Ioannidis; Laurent Massoulié (IEEE Trans. Inf. Theory, 2015)

Seeing the Unseen Network: Inferring Hidden Social Ties from Respondent-Driven Sampling. - Lin Chen 003; Forrest W. Crawford; Amin Karbasi (AAAI, 2016)

Learning network structures from firing patterns. - Amin Karbasi; Amir Hesam Salavati; Martin Vetterli (ICASSP, 2016)

Fast Constrained Submodular Maximization: Personalized Data Summarization. - Baharan Mirzasoleiman; Ashwinkumar Badanidiyuru; Amin Karbasi (ICML, 2016)

Estimating the Size of a Large Network and its Communities from a Random Sample. - Lin Chen 003; Amin Karbasi; Forrest W. Crawford (NIPS, 2016)

Fast Distributed Submodular Cover: Public-Private Data Summarization. - Baharan Mirzasoleiman; Morteza Zadimoghaddam; Amin Karbasi (NIPS, 2016)

Dimension Coupling: Optimal Active Learning of Halfspaces via Query Synthesis. - Lin Chen 003; S. Hamed Hassani; Amin Karbasi (CoRR, 2016)

Distributed Submodular Maximization. - Baharan Mirzasoleiman; Amin Karbasi; Rik Sarkar; Andreas Krause 001 (J. Mach. Learn. Res., 2016)

Near-Optimal Active Learning of Halfspaces via Query Synthesis in the Noisy Setting. - Lin Chen 003; Seyed Hamed Hassani; Amin Karbasi (AAAI, 2017)

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

Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten". - Baharan Mirzasoleiman; Amin Karbasi; Andreas Krause 001 (ICML, 2017)

Differentially Private Submodular Maximization: Data Summarization in Disguise. - Marko Mitrovic; Mark Bun; Andreas Krause 001; Amin Karbasi (ICML, 2017)

Probabilistic Submodular Maximization in Sub-Linear Time. - Serban Stan; Morteza Zadimoghaddam; Andreas Krause 001; Amin Karbasi (ICML, 2017)

A Submodular Approach to Create Individualized Parcellations of the Human Brain. - Mehraveh Salehi; Amin Karbasi; Dustin Scheinost; R. Todd Constable (MICCAI (1), 2017)

Interactive Submodular Bandit. - Lin Chen 003; Andreas Krause 001; Amin Karbasi (NIPS, 2017)

Streaming Weak Submodularity: Interpreting Neural Networks on the Fly. - Ethan R. Elenberg; Alexandros G. Dimakis; Moran Feldman; Amin Karbasi (NIPS, 2017)

Gradient Methods for Submodular Maximization. - S. Hamed Hassani; Mahdi Soltanolkotabi; Amin Karbasi (NIPS, 2017)

Submodular Variational Inference for Network Reconstruction. - Lin Chen 003; Forrest W. Crawford; Amin Karbasi (UAI, 2017)

Deletion-Robust Submodular Maximization at Scale. - Ehsan Kazemi 001; Morteza Zadimoghaddam; Amin Karbasi (CoRR, 2017)

Online Continuous Submodular Maximization. - Lin Chen 003; Hamed Hassani; Amin Karbasi (AISTATS, 2018)

Comparison Based Learning from Weak Oracles. - Ehsan Kazemi 001; Lin Chen 003; Sanjoy Dasgupta; Amin Karbasi (AISTATS, 2018)

Submodularity on Hypergraphs: From Sets to Sequences. - Marko Mitrovic; Moran Feldman; Andreas Krause 001; Amin Karbasi (AISTATS, 2018)

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

Scalable Deletion-Robust Submodular Maximization: Data Summarization with Privacy and Fairness Constraints. - Ehsan Kazemi 001; Morteza Zadimoghaddam; Amin Karbasi (ICML, 2018)

Weakly Submodular Maximization Beyond Cardinality Constraints: Does Randomization Help Greedy? - Lin Chen 003; Moran Feldman; Amin Karbasi (ICML, 2018)

Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity. - Lin Chen 003; Christopher Harshaw; Hamed Hassani; Amin Karbasi (ICML, 2018)

Data Summarization at Scale: A Two-Stage Submodular Approach. - Marko Mitrovic; Ehsan Kazemi 001; Morteza Zadimoghaddam; Amin Karbasi (ICML, 2018)

Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings. - Aryan Mokhtari; Hamed Hassani; Amin Karbasi (ICML, 2018)

Do Less, Get More: Streaming Submodular Maximization with Subsampling. - Moran Feldman; Amin Karbasi; Ehsan Kazemi 001 (NeurIPS, 2018)

Learning neural connectivity from firing activity: efficient algorithms with provable guarantees on topology. - Amin Karbasi; Amir Hesam Salavati; Martin Vetterli (J. Comput. Neurosci., 2018)

An exemplar-based approach to individualized parcellation reveals the need for sex specific functional networks. - Mehraveh Salehi; Amin Karbasi; Xilin Shen; Dustin Scheinost; R. Todd Constable (NeuroImage, 2018)

Eliminating Latent Discrimination: Train Then Mask. - Soheil Ghili; Ehsan Kazemi 001; Amin Karbasi (AAAI, 2019)

Projection-Free Bandit Convex Optimization. - Lin Chen 003; Mingrui Zhang; Amin Karbasi (AISTATS, 2019)

Submodular Streaming in All Its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity. - Ehsan Kazemi 001; Marko Mitrovic; Morteza Zadimoghaddam; Silvio Lattanzi; Amin Karbasi (ICML, 2019)

Submodular Maximization beyond Non-negativity: Guarantees, Fast Algorithms, and Applications. - Chris Harshaw; Moran Feldman; Justin Ward; Amin Karbasi (ICML, 2019)

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

Adaptive Sequence Submodularity. - Marko Mitrovic; Ehsan Kazemi 001; Moran Feldman; Andreas Krause 001; Amin Karbasi (NeurIPS, 2019)

Online Continuous Submodular Maximization: From Full-Information to Bandit Feedback. - Mingrui Zhang; Lin Chen 003; Hamed Hassani; Amin Karbasi (NeurIPS, 2019)

Unconstrained submodular maximization with constant adaptive complexity. - Lin Chen 003; Moran Feldman; Amin Karbasi (STOC, 2019)

Quantized Frank-Wolfe: Communication-Efficient Distributed Optimization. - Mingrui Zhang; Lin Chen 003; Aryan Mokhtari; Hamed Hassani; Amin Karbasi (CoRR, 2019)

Stochastic Conditional Gradient++. - Hamed Hassani; Amin Karbasi; Aryan Mokhtari; Zebang Shen (CoRR, 2019)

Batched Multi-Armed Bandits with Optimal Regret. - Hossein Esfandiari; Amin Karbasi; Abbas Mehrabian; Vahab S. Mirrokni (CoRR, 2019)

Black Box Submodular Maximization: Discrete and Continuous Settings. - Lin Chen 003; Mingrui Zhang; Hamed Hassani; Amin Karbasi (AISTATS, 2020)

Quantized Frank-Wolfe: Faster Optimization, Lower Communication, and Projection Free. - Mingrui Zhang; Lin Chen 003; Aryan Mokhtari; Hamed Hassani; Amin Karbasi (AISTATS, 2020)

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

More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard Models. - Lin Chen 003; Yifei Min; Mingrui Zhang; Amin Karbasi (ICML, 2020)

Streaming Submodular Maximization under a k-Set System Constraint. - Ran Haba; Ehsan Kazemi 001; Moran Feldman; Amin Karbasi (ICML, 2020)

Submodular Maximization Through Barrier Functions. - Ashwinkumar Badanidiyuru; Amin Karbasi; Ehsan Kazemi 001; Jan Vondrák (NeurIPS, 2020)

Online MAP Inference of Determinantal Point Processes. - Aditya Bhaskara; Amin Karbasi; Silvio Lattanzi; Morteza Zadimoghaddam (NeurIPS, 2020)

Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transition. - Lin Chen 003; Qian Yu 001; Hannah Lawrence; Amin Karbasi (NeurIPS, 2020)

Continuous Submodular Maximization: Beyond DR-Submodularity. - Moran Feldman; Amin Karbasi (NeurIPS, 2020)

Safe Learning under Uncertain Objectives and Constraints. - Mohammad Fereydounian; Zebang Shen; Aryan Mokhtari; Amin Karbasi; Hamed Hassani (CoRR, 2020)

Simultaneous Greedys: A Swiss Army Knife for Constrained Submodular Maximization. - Moran Feldman; Christopher Harshaw; Amin Karbasi (CoRR, 2020)

Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization. - Aryan Mokhtari; Hamed Hassani; Amin Karbasi (J. Mach. Learn. Res., 2020)

There is no single functional atlas even for a single individual: Functional parcel definitions change with task. - Mehraveh Salehi; Abigail S. Greene; Amin Karbasi; Xilin Shen; Dustin Scheinost; R. Todd Constable (NeuroImage, 2020)

Individualized functional networks reconfigure with cognitive state. - Mehraveh Salehi; Amin Karbasi; Daniel S. Barron; Dustin Scheinost; R. Todd Constable (NeuroImage, 2020)

Stochastic Conditional Gradient++: (Non)Convex Minimization and Continuous Submodular Maximization. - Hamed Hassani; Amin Karbasi; Aryan Mokhtari; Zebang Shen (SIAM J. Optim., 2020)

Submodularity in Action: From Machine Learning to Signal Processing Applications. - Ehsan Tohidi; Rouhollah Amiri; Mario Coutino; David Gesbert; Geert Leus; Amin Karbasi (IEEE Signal Process. Mag., 2020)

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

Meta Learning in the Continuous Time Limit. - Ruitu Xu; Lin Chen 003; Amin Karbasi (AISTATS, 2021)

Adaptivity in Adaptive Submodularity. - Hossein Esfandiari; Amin Karbasi; Vahab S. Mirrokni (COLT, 2021)

Regularized Submodular Maximization at Scale. - Ehsan Kazemi 001; Shervin Minaee; Moran Feldman; Amin Karbasi (ICML, 2021)

Data-Driven Mapping Between Functional Connectomes Using Optimal Transport. - Javid Dadashkarimi; Amin Karbasi; Dustin Scheinost (MICCAI (3), 2021)

Multiple Descent: Design Your Own Generalization Curve. - Lin Chen 003; Yifei Min; Mikhail Belkin; Amin Karbasi (NeurIPS, 2021)

Parallelizing Thompson Sampling. - Amin Karbasi; Vahab S. Mirrokni; Mohammad Shadravan (NeurIPS, 2021)

Submodular + Concave. - Siddharth Mitra; Moran Feldman; Amin Karbasi (NeurIPS, 2021)

An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks. - Shashank Rajput; Kartik Sreenivasan; Dimitris S. Papailiopoulos; Amin Karbasi (NeurIPS, 2021)

Learning and certification under instance-targeted poisoning. - Ji Gao; Amin Karbasi; Mohammad Mahmoody (UAI, 2021)

The curious case of adversarially robust models: More data can help, double descend, or hurt generalization. - Yifei Min; Lin Chen 003; Amin Karbasi (UAI, 2021)

Batched Neural Bandits. - Quanquan Gu; Amin Karbasi; Khashayar Khosravi; Vahab S. Mirrokni; Dongruo Zhou (CoRR, 2021)

Federated Functional Gradient Boosting. - Zebang Shen; Hamed Hassani; Satyen Kale; Amin Karbasi (AISTATS, 2022)

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

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

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

Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes. - Insu Han; Mike Gartrell; Elvis Dohmatob; Amin Karbasi (ICML, 2022)

Combining Multiple Atlases to Estimate Data-Driven Mappings Between Functional Connectomes Using Optimal Transport. - Javid Dadashkarimi; Amin Karbasi; Dustin Scheinost (MICCAI (1), 2022)

Transforming Connectomes to "Any" Parcellation via Graph Matching. - Qinghao Liang; Javid Dadashkarimi; Wei Dai; Amin Karbasi; Joseph Chang; Harrison H. Zhou; Dustin Scheinost (ISGIE/GRAIL@MICCAI, 2022)

Fast Neural Kernel Embeddings for General Activations. - Insu Han; Amir Zandieh; Jaehoon Lee 001; Roman Novak; Lechao Xiao; Amin Karbasi (NeurIPS, 2022)

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

Universal Rates for Interactive Learning. - Steve Hanneke; Amin Karbasi; Shay Moran; Grigoris Velegkas (NeurIPS, 2022)

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

Submodular Maximization in Clean Linear Time. - Wenxin Li; Moran Feldman; Ehsan Kazemi 001; Amin Karbasi (NeurIPS, 2022)

Black-Box Generalization: Stability of Zeroth-Order Learning. - Konstantinos E. Nikolakakis; Farzin Haddadpour; Dionysios S. Kalogerias; Amin Karbasi (NeurIPS, 2022)

Reinforcement Learning with Logarithmic Regret and Policy Switches. - Grigoris Velegkas; Zhuoran Yang; Amin Karbasi (NeurIPS, 2022)

Black-Box Generalization. - Konstantinos E. Nikolakakis; Farzin Haddadpour; Dionysios S. Kalogerias; Amin Karbasi (CoRR, 2022)

The Exact Class of Graph Functions Generated by Graph Neural Networks. - Mohammad Fereydounian; Hamed Hassani; Javid Dadashkarimi; Amin Karbasi (CoRR, 2022)

The Best of Both Worlds: Reinforcement Learning with Logarithmic Regret and Policy Switches. - Grigoris Velegkas; Zhuoran Yang; Amin Karbasi (CoRR, 2022)

Reproducible Bandits. - Hossein Esfandiari; Alkis Kalavasis; Amin Karbasi; Andreas Krause 001; Vahab Mirrokni; Grigoris Velegkas (CoRR, 2022)

Exact Gradient Computation for Spiking Neural Networks Through Forward Propagation. - Jane H. Lee; Saeid Haghighatshoar; Amin Karbasi (CoRR, 2022)

The Power of Subsampling in Submodular Maximization. - Christopher Harshaw; Ehsan Kazemi 001; Moran Feldman; Amin Karbasi (Math. Oper. Res., 2022)

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

Stacking multiple optimal transport policies to map functional connectomes. - Javid Dadashkarimi; Matthew Rosenblatt; Amin Karbasi; Dustin Scheinost (CISS, 2023)

Replicable Bandits. - Hossein Esfandiari; Alkis Kalavasis; Amin Karbasi; Andreas Krause 001; Vahab Mirrokni; Grigoris Velegkas (ICLR, 2023)

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

Statistical Indistinguishability of Learning Algorithms. - Alkis Kalavasis; Amin Karbasi; Shay Moran; Grigoris Velegkas (ICML, 2023)

Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning. - Amin Karbasi; Nikki Lijing Kuang; Yi-An Ma; Siddharth Mitra (ICML, 2023)

KDEformer: Accelerating Transformers via Kernel Density Estimation. - Amir Zandieh; Insu Han; Majid Daliri; Amin Karbasi (ICML, 2023)

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

Replicable Clustering. - Hossein Esfandiari; Amin Karbasi; Vahab Mirrokni; Grigoris Velegkas; Felix Zhou 002 (NeurIPS, 2023)

Replicability in Reinforcement Learning. - Amin Karbasi; Grigoris Velegkas; Lin Yang 011; Felix Zhou 002 (NeurIPS, 2023)

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

Select without Fear: Almost All Mini-Batch Schedules Generalize Optimally. - Konstantinos E. Nikolakakis; Amin Karbasi; Dionysis Kalogerias (CoRR, 2023)

Learning from Aggregated Data: Curated Bags versus Random Bags. - Lin Chen; Gang Fu; Amin Karbasi; Vahab Mirrokni (CoRR, 2023)

How Do You Want Your Greedy: Simultaneous or Repeated? - Moran Feldman; Christopher Harshaw; Amin Karbasi (J. Mach. Learn. Res., 2023)

Cross Atlas Remapping via Optimal Transport (CAROT): Creating connectomes for different atlases when raw data is not available. - 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; et al. (Medical Image Anal., 2023)

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

The Impossibility of Parallelizing Boosting. - Amin Karbasi; Kasper Green Larsen (ALT, 2024)

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

HyperAttention: Long-context Attention in Near-Linear Time. - Insu Han; Rajesh Jayaram; Amin Karbasi; Vahab Mirrokni; David P. Woodruff; Amir Zandieh (ICLR, 2024)

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

Replicable Learning of Large-Margin Halfspaces. - Alkis Kalavasis; Amin Karbasi; Kasper Green Larsen; Grigoris Velegkas; Felix Zhou 002 (ICML, 2024)

Cell2Sentence: Teaching Large Language Models the Language of Biology. - 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; et al. (ICML, 2024)

Universal Rates for Active Learning. - Steve Hanneke; Amin Karbasi; Shay Moran; Grigoris Velegkas (NeurIPS, 2024)

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

On the Computational Landscape of Replicable Learning. - Alkis Kalavasis; Amin Karbasi; Grigoris Velegkas; Felix Zhou 002 (NeurIPS, 2024)

TSDS: Data Selection for Task-Specific Model Finetuning. - Zifan Liu; Amin Karbasi; Theodoros Rekatsinas (NeurIPS, 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)

SubGen: Token Generation in Sublinear Time and Memory. - Amir Zandieh; Insu Han; Vahab Mirrokni; Amin Karbasi (CoRR, 2024)

Injecting Undetectable Backdoors in Deep Learning and Language Models. - Alkis Kalavasis; Amin Karbasi; Argyris Oikonomou; Katerina Sotiraki; Grigoris Velegkas; Manolis Zampetakis (CoRR, 2024)

Extracting Memorized Training Data via Decomposition. - Ellen Su; Anu Vellore; Amy Chang; Raffaele Mura; Blaine Nelson; Paul Kassianik; Amin Karbasi (CoRR, 2024)

Cognitive Overload Attack:Prompt Injection for Long Context. - Bibek Upadhayay; Vahid Behzadan; Amin Karbasi (CoRR, 2024)

Procurement Auctions via Approximately Optimal Submodular Optimization. - Yuan Deng; Amin Karbasi; Vahab Mirrokni; Renato Paes Leme; Grigoris Velegkas; Song Zuo (CoRR, 2024)

Criteria and Bias of Parameterized Linear Regression under Edge of Stability Regime. - Peiyuan Zhang; Amin Karbasi (CoRR, 2024)

Learning Task Representations from In-Context Learning. - Baturay Saglam; Xinyang Hu; Zhuoran Yang; Dionysis Kalogerias; Amin Karbasi (ACL (Findings), 2025)

Intelligence at the Edge of Chaos. - Shiyang Zhang; Aakash Patel; Syed Asad Rizvi; Nianchen Liu; Sizhuang He; Amin Karbasi; Emanuele Zappala; David van Dijk (ICLR, 2025)

A Flow-based Truncated Denoising Diffusion Model for super-resolution Magnetic Resonance Spectroscopic Imaging. - 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; et al. (Medical Image Anal., 2025)

Select without Fear: Almost All Minibatch Schedules Generalize Optimally. - Konstantinos E. Nikolakakis; Amin Karbasi; Dionysis Kalogerias (SIAM J. Math. Data Sci., 2025)

Adversarial Reasoning at Jailbreaking Time. - Mahdi Sabbaghi; Paul Kassianik; George J. Pappas; Yaron Singer; Amin Karbasi; Hamed Hassani (CoRR, 2025)

PolarQuant: Quantizing KV Caches with Polar Transformation. - Insu Han; Praneeth Kacham; Amin Karbasi; Vahab Mirrokni; Amir Zandieh (CoRR, 2025)

Learning Task Representations from In-Context Learning. - Baturay Saglam; Zhuoran Yang; Dionysis Kalogerias; Amin Karbasi (CoRR, 2025)

(Im)possibility of Automated Hallucination Detection in Large Language Models. - Amin Karbasi; Omar Montasser; John Sous; Grigoris Velegkas (CoRR, 2025)

Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report. - Paul Kassianik; Baturay Saglam; Alexander Chen; Blaine Nelson; Anu Vellore; Massimo Aufiero; Fraser Burch; Dhruv Kedia; Avi Zohary; Sajana Weerawardhena; Aman Priyanshu; Adam Swanda; et al. (CoRR, 2025)

On Union-Closedness of Language Generation. - Steve Hanneke; Amin Karbasi; Anay Mehrotra; Grigoris Velegkas (CoRR, 2025)

Large Language Models Encode Semantics in Low-Dimensional Linear Subspaces. - Baturay Saglam; Paul Kassianik; Blaine Nelson; Sajana Weerawardhena; Yaron Singer; Amin Karbasi (CoRR, 2025)