Constantine Caramanis

ORCID

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 126

Top Venues

Massachusetts Institute of Technology, Cambridge, MA, USA (PHD)

Education History

Massachusetts Institute of Technology, Cambridge, MA, USA

PHD

Publications

Litu Rout, Yujia Chen, Nataniel Ruiz, Abhishek Kumar, Constantine Caramanis, Sanjay Shakkottai, Wen-Sheng Chu
RB-Modulation: Training-Free Personalization of Diffusion Models using Stochastic Optimal Control. CoRR (2024)
Alexia Atsidakou, Constantine Caramanis, Evangelia Gergatsouli, Orestis Papadigenopoulos, Christos Tzamos
Contextual Pandora's Box. AAAI (2024)
Jeongyeol Kwon, Shie Mannor, Constantine Caramanis, Yonathan Efroni
RL in Latent MDPs is Tractable: Online Guarantees via Off-Policy Evaluation. CoRR (2024)
Alexia Atsidakou, Branislav Kveton, Sumeet Katariya, Constantine Caramanis, Sujay Sanghavi
Logarithmic Bayes Regret Bounds. CoRR (2023)
Litu Rout, Negin Raoof, Giannis Daras, Constantine Caramanis, Alex Dimakis, Sanjay Shakkottai
Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models. NeurIPS (2023)
Litu Rout, Advait Parulekar, Constantine Caramanis, Sanjay Shakkottai
A Theoretical Justification for Image Inpainting using Denoising Diffusion Probabilistic Models. CoRR (2023)
Alexia Atsidakou, Branislav Kveton, Sumeet Katariya, Constantine Caramanis, Sujay Sanghavi
Logarithmic Bayes Regret Bounds. NeurIPS (2023)
Matthew Faw, Litu Rout, Constantine Caramanis, Sanjay Shakkottai
Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD. CoRR (2023)
Litu Rout, Yujia Chen, Abhishek Kumar, Constantine Caramanis, Sanjay Shakkottai, Wen-Sheng Chu
Beyond First-Order Tweedie: Solving Inverse Problems using Latent Diffusion. CoRR (2023)
Jeongyeol Kwon, Yonathan Efroni, Shie Mannor, Constantine Caramanis
Prospective Side Information for Latent MDPs. CoRR (2023)
Matthew Faw, Litu Rout, Constantine Caramanis, Sanjay Shakkottai
Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD. COLT (2023)
Litu Rout, Negin Raoof, Giannis Daras, Constantine Caramanis, Alexandros G. Dimakis, Sanjay Shakkottai
Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models. CoRR (2023)
Constantine Caramanis, Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Methods. CoRR (2023)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
Reward-Mixing MDPs with Few Latent Contexts are Learnable. ICML (2023)
Constantine Caramanis, Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method. NeurIPS (2023)
Dhiraj Murthy, Constantine Caramanis, Koustav Rudra
Understanding Lexical Biases when Identifying Gang-related Social Media Communications. CoRR (2023)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
Tractable Optimality in Episodic Latent MABs. CoRR (2022)
Matthew Faw, Isidoros Tziotis, Constantine Caramanis, Aryan Mokhtari, Sanjay Shakkottai, Rachel Ward
The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance. COLT (2022)
Alexia Atsidakou, Constantine Caramanis, Evangelia Gergatsouli, Orestis Papadigenopoulos, Christos Tzamos
Contextual Pandora's Box. CoRR (2022)
Matthew Faw, Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai
Learning To Maximize Welfare with a Reusable Resource. Proc. ACM Meas. Anal. Comput. Syst. 6 (2) (2022)
Alexia Atsidakou, Orestis Papadigenopoulos, Constantine Caramanis, Sujay Sanghavi, Sanjay Shakkottai
Asymptotically-Optimal Gaussian Bandits with Side Observations. ICML (2022)
Matthew Faw, Isidoros Tziotis, Constantine Caramanis, Aryan Mokhtari, Sanjay Shakkottai, Rachel Ward
The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance. CoRR (2022)
Constantine Caramanis, Paul Dütting, Matthew Faw, Federico Fusco, Philip Lazos, Stefano Leonardi, Orestis Papadigenopoulos, Emmanouil Pountourakis, Rebecca Reiffenhäuser
Single-Sample Prophet Inequalities via Greedy-Ordered Selection. SODA (2022)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms. ICML (2022)
Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai
Non-Stationary Bandits under Recharging Payoffs: Improved Planning with Sublinear Regret. CoRR (2022)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms. CoRR (2022)
Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai
Non-Stationary Bandits under Recharging Payoffs: Improved Planning with Sublinear Regret. NeurIPS (2022)
Matthew Faw, Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai
Learning To Maximize Welfare with a Reusable Resource. SIGMETRICS (Abstracts) (2022)
Ashish Katiyar, Soumya Basu, Vatsal Shah, Constantine Caramanis
Recoverability Landscape of Tree Structured Markov Random Fields under Symmetric Noise. AISTATS (2022)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
Tractable Optimality in Episodic Latent MABs. NeurIPS (2022)
Sen Lin, Ming Shi, Anish Arora, Raef Bassily, Elisa Bertino, Constantine Caramanis, Kaushik R. Chowdhury, Eylem Ekici, Atilla Eryilmaz, Stratis Ioannidis, Nan Jiang, Gauri Joshi, Jim Kurose, Yingbin Liang, Zhiqiang Lin, Jia Liu, Mingyan Liu, Tommaso Melodia, Aryan Mokhtari, Rob Nowak, Sewoong Oh, Srini Parthasarathy, Chunyi Peng, Hulya Seferoglu, Ness Shroff, Sanjay Shakkottai, Kannan Srinivasan, Ameet Talwalkar, Aylin Yener, Lei Ying
Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks. CIC (2022)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
Reward-Mixing MDPs with a Few Latent Contexts are Learnable. CoRR (2022)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
Reinforcement Learning in Reward-Mixing MDPs. NeurIPS (2021)
Alexia Atsidakou, Orestis Papadigenopoulos, Soumya Basu, Constantine Caramanis, Sanjay Shakkottai
Combinatorial Blocking Bandits with Stochastic Delays. ICML (2021)
Ashish Katiyar, Soumya Basu, Vatsal Shah, Constantine Caramanis
Robust Estimation of Tree Structured Markov Random Fields. CoRR (2021)
Jeongyeol Kwon, Nhat Ho, Constantine Caramanis
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression. AISTATS (2021)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
RL for Latent MDPs: Regret Guarantees and a Lower Bound. NeurIPS (2021)
Orestis Papadigenopoulos, Constantine Caramanis
Recurrent Submodular Welfare and Matroid Blocking Semi-Bandits. NeurIPS (2021)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
Reinforcement Learning in Reward-Mixing MDPs. CoRR (2021)
Soumya Basu, Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai
Contextual Blocking Bandits. AISTATS (2021)
Alexia Atsidakou, Orestis Papadigenopoulos, Soumya Basu, Constantine Caramanis, Sanjay Shakkottai
Combinatorial Blocking Bandits with Stochastic Delays. CoRR (2021)
Constantine Caramanis, Paul Dütting, Matthew Faw, Federico Fusco, Philip Lazos, Stefano Leonardi, Orestis Papadigenopoulos, Emmanouil Pountourakis, Rebecca Reiffenhäuser
Single-Sample Prophet Inequalities via Greedy-Ordered Selection. CoRR (2021)
Orestis Papadigenopoulos, Constantine Caramanis
Recurrent Submodular Welfare and Matroid Blocking Bandits. CoRR (2021)
Constantine Caramanis, Matthew Faw, Orestis Papadigenopoulos, Emmanouil Pountourakis
Single-Sample Prophet Inequalities Revisited. CoRR (2021)
Jiacheng Zhuo, Jeongyeol Kwon, Nhat Ho, Constantine Caramanis
On the computational and statistical complexity of over-parameterized matrix sensing. CoRR (2021)
Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor
RL for Latent MDPs: Regret Guarantees and a Lower Bound. CoRR (2021)
Soumya Basu, Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai
Contextual Blocking Bandits. CoRR (2020)
Matthew Faw, Rajat Sen, Karthikeyan Shanmugam, Constantine Caramanis, Sanjay Shakkottai
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions. NeurIPS (2020)
Jeongyeol Kwon, Nhat Ho, Constantine Caramanis
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression. CoRR (2020)
Ajil Jalal, Liu Liu, Alexandros G. Dimakis, Constantine Caramanis
Robust compressed sensing using generative models. NeurIPS (2020)
Ajil Jalal, Liu Liu, Alexandros G. Dimakis, Constantine Caramanis
Robust compressed sensing of generative models. CoRR (2020)
Jessica Hoffmann, Matt Jordan, Constantine Caramanis
Quarantines as a Targeted Immunization Strategy. CoRR (2020)
Jiacheng Zhuo, Qi Lei, Alex Dimakis, Constantine Caramanis
Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls. AISTATS (2020)
Jeongyeol Kwon, Constantine Caramanis
EM Algorithm is Sample-Optimal for Learning Mixtures of Well-Separated Gaussians. CoRR (2020)
Jeongyeol Kwon, Constantine Caramanis
EM Converges for a Mixture of Many Linear Regressions. AISTATS (2020)
Jiacheng Zhuo, Liu Liu, Constantine Caramanis
Robust Structured Statistical Estimation via Conditional Gradient Type Methods. CoRR (2020)
Isidoros Tziotis, Constantine Caramanis, Aryan Mokhtari
Second Order Optimality in Decentralized Non-Convex Optimization via Perturbed Gradient Tracking. NeurIPS (2020)
Liu Liu, Yanyao Shen, Tianyang Li, Constantine Caramanis
High Dimensional Robust Sparse Regression. AISTATS (2020)
Jessica Hoffmann, Soumya Basu, Surbhi Goel, Constantine Caramanis
Learning Mixtures of Graphs from Epidemic Cascades. ICML (2020)
Ashish Katiyar, Vatsal Shah, Constantine Caramanis
Robust Estimation of Tree Structured Ising Models. CoRR (2020)
Murat Kocaoglu, Sanjay Shakkottai, Alexandros G. Dimakis, Constantine Caramanis, Sriram Vishwanath
Applications of Common Entropy for Causal Inference. NeurIPS (2020)
Jeongyeol Kwon, Constantine Caramanis
The EM Algorithm gives Sample-Optimality for Learning Mixtures of Well-Separated Gaussians. COLT (2020)
Qi Lei, Jiacheng Zhuo, Constantine Caramanis, Inderjit S. Dhillon, Alexandros G. Dimakis
Primal-Dual Block Frank-Wolfe. CoRR (2019)
Jessica Hoffmann, Soumya Basu, Surbhi Goel, Constantine Caramanis
Disentangling Mixtures of Epidemics on Graphs. CoRR (2019)
Jessica Hoffmann, Constantine Caramanis
Learning Graphs from Noisy Epidemic Cascades. Proc. ACM Meas. Anal. Comput. Syst. 3 (2) (2019)
Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning. CoRR (2019)
Jessica Hoffmann, Constantine Caramanis
Learning Graphs from Noisy Epidemic Cascades. CoRR (2019)
Jeongyeol Kwon, Wei Qian, Constantine Caramanis, Yudong Chen, Damek Davis
Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression. COLT (2019)
Jeongyeol Kwon, Constantine Caramanis
EM Converges for a Mixture of Many Linear Regressions. CoRR (2019)
Jessica H. Hoffmann, Constantine Caramanis
Learning Graphs from Noisy Epidemic Cascades. SIGMETRICS (Abstracts) (2019)
Qi Lei, Jiacheng Zhuo, Constantine Caramanis, Inderjit S. Dhillon, Alexandros G. Dimakis
Primal-Dual Block Generalized Frank-Wolfe. NeurIPS (2019)
Matthew Faw, Rajat Sen, Karthikeyan Shanmugam, Constantine Caramanis, Sanjay Shakkottai
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions. CoRR (2019)
Jiacheng Zhuo, Qi Lei, Alexandros G. Dimakis, Constantine Caramanis
Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls. CoRR (2019)
Ashish Katiyar, Jessica Hoffmann, Constantine Caramanis
Robust estimation of tree structured Gaussian Graphical Model. CoRR (2019)
Ashish Katiyar, Jessica Hoffmann, Constantine Caramanis
Robust Estimation of Tree Structured Gaussian Graphical Models. ICML (2019)
Liu Liu, Tianyang Li, Constantine Caramanis
High Dimensional Robust Estimation of Sparse Models via Trimmed Hard Thresholding. CoRR (2019)
Jessica Hoffmann, Constantine Caramanis
The Cost of Uncertainty in Curing Epidemics. SIGMETRICS (Abstracts) (2018)
Zeina Sinno, Constantine Caramanis, Alan C. Bovik
Towards a Closed Form Second-Order Natural Scene Statistics Model. IEEE Trans. Image Process. 27 (7) (2018)
Mikhail Kazdagli, Constantine Caramanis, Sanjay Shakkottai, Mohit Tiwari
The Shape of Alerts: Detecting Malware Using Distributed Detectors by Robustly Amplifying Transient Correlations. CoRR (2018)
Tianyang Li, Anastasios Kyrillidis, Liu Liu, Constantine Caramanis
Approximate Newton-based statistical inference using only stochastic gradients. CoRR (2018)
Tianyang Li, Liu Liu, Anastasios Kyrillidis, Constantine Caramanis
Statistical Inference Using SGD. AAAI (2018)
Jeongyeol Kwon, Constantine Caramanis
Global Convergence of EM Algorithm for Mixtures of Two Component Linear Regression. CoRR (2018)
Liu Liu, Yanyao Shen, Tianyang Li, Constantine Caramanis
High Dimensional Robust Sparse Regression. CoRR (2018)
Eli A. Meirom, Constantine Caramanis, Shie Mannor, Ariel Orda, Sanjay Shakkottai
Detecting Cascades from Weak Signatures. IEEE Trans. Netw. Sci. Eng. 5 (4) (2018)
Jessica Hoffmann, Constantine Caramanis
The Cost of Uncertainty in Curing Epidemics. Proc. ACM Meas. Anal. Comput. Syst. 2 (2) (2018)
Murat Kocaoglu, Sanjay Shakkottai, Alexandros G. Dimakis, Constantine Caramanis, Sriram Vishwanath
Entropic Latent Variable Discovery. CoRR (2018)
Zeina Sinno, Constantine Caramanis, Alan C. Bovik
Second Order Natural Scene Statistics Model of Blind Image Quality Assessment. ICASSP (2018)
Yudong Chen, Xinyang Yi, Constantine Caramanis
Convex and Nonconvex Formulations for Mixed Regression With Two Components: Minimax Optimal Rates. IEEE Trans. Inf. Theory 64 (3) (2018)
Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi
Finding Low-Rank Solutions via Nonconvex Matrix Factorization, Efficiently and Provably. SIAM J. Imaging Sci. 11 (4) (2018)
Tianyang Li, Liu Liu, Anastasios Kyrillidis, Constantine Caramanis
Statistical inference using SGD. CoRR (2017)
Guy Tennenholtz, Constantine Caramanis, Shie Mannor
The Stochastic Firefighter Problem. CoRR (2017)
Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach. AISTATS (2017)
Jessica Hoffmann, Constantine Caramanis
The Cost of Uncertainty in Curing Epidemics. CoRR (2017)
Anastasios Kyrillidis, Amir Kalev, Dohyung Park, Srinadh Bhojanapalli, Constantine Caramanis, Sujay Sanghavi
Provable quantum state tomography via non-convex methods. CoRR (2017)
Tianyang Li, Xinyang Yi, Constantine Caramanis, Pradeep Ravikumar
Minimax Gaussian Classification & Clustering. AISTATS (2017)
Mikhail Kazdagli, Constantine Caramanis, Sanjay Shakkottai, Mohit Tiwari
Exploiting Latent Attack Semantics for Intelligent Malware Detection. CoRR (2017)
Ye Wang, Constantine Caramanis, Michael Orshansky
PolyGP: Improving GP-based analog optimization through accurate high-order monomials and semidefinite relaxation. DATE (2016)
Ye Wang, Constantine Caramanis, Michael Orshansky
Exploiting randomness in sketching for efficient hardware implementation of machine learning applications. ICCAD (2016)
Yudong Chen, Huan Xu, Constantine Caramanis, Sujay Sanghavi
Matrix Completion With Column Manipulation: Near-Optimal Sample-Robustness-Rank Tradeoffs. IEEE Trans. Inf. Theory 62 (1) (2016)
Xinyang Yi, Constantine Caramanis, Sujay Sanghavi
Solving a Mixture of Many Random Linear Equations by Tensor Decomposition and Alternating Minimization. CoRR (2016)

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Publication Activity (10 Years)

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Constantine Caramanis