Caramanis, Constantine

64 publications

NeurIPS 2025 Anchored Diffusion Language Model Litu Rout, Constantine Caramanis, Sanjay Shakkottai

ICLR 2025 Infilling Score: A Pretraining Data Detection Algorithm for Large Language Models Negin Raoof, Litu Rout, Giannis Daras, Sujay Sanghavi, Constantine Caramanis, Sanjay Shakkottai, Alex Dimakis

ICML 2025 On Mitigating Affinity Bias Through Bandits with Evolving Biased Feedback Matthew Faw, Constantine Caramanis, Jessica Hoffmann

ICLR 2025 RB-Modulation: Training-Free Stylization Using Reference-Based Modulation Litu Rout, Yujia Chen, Nataniel Ruiz, Abhishek Kumar, Constantine Caramanis, Sanjay Shakkottai, Wen-Sheng Chu

ICLR 2025 Semantic Image Inversion and Editing Using Rectified Stochastic Differential Equations Litu Rout, Yujia Chen, Nataniel Ruiz, Constantine Caramanis, Sanjay Shakkottai, Wen-Sheng Chu

CVPR 2024 Beyond First-Order Tweedie: Solving Inverse Problems Using Latent Diffusion Litu Rout, Yujia Chen, Abhishek Kumar, Constantine Caramanis, Sanjay Shakkottai, Wen-Sheng Chu

AAAI 2024 Contextual Pandora's Box Alexia Atsidakou, Constantine Caramanis, Evangelia Gergatsouli, Orestis Papadigenopoulos, Christos Tzamos

JMLR 2024 On the Computational and Statistical Complexity of Over-Parameterized Matrix Sensing Jiacheng Zhuo, Jeongyeol Kwon, Nhat Ho, Constantine Caramanis

NeurIPS 2024 Optimization Can Learn Johnson Lindenstrauss Embeddings Nikos Tsikouras, Constantine Caramanis, Christos Tzamos

ICML 2024 Prospective Side Information for Latent MDPs Jeongyeol Kwon, Yonathan Efroni, Shie Mannor, Constantine Caramanis

NeurIPS 2024 RL in Latent MDPs Is Tractable: Online Guarantees via Off-Policy Evaluation Jeongyeol Kwon, Shie Mannor, Constantine Caramanis, Yonathan Efroni

COLT 2023 Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD Matthew Faw, Litu Rout, Constantine Caramanis, Sanjay Shakkottai

NeurIPS 2023 Finite-Time Logarithmic Bayes Regret Upper Bounds Alexia Atsidakou, Branislav Kveton, Sumeet Katariya, Constantine Caramanis, Sujay Sanghavi

NeurIPS 2023 Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method Constantine Caramanis, Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos

ICML 2023 Reward-Mixing MDPs with Few Latent Contexts Are Learnable Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

NeurIPS 2023 Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models Litu Rout, Negin Raoof, Giannis Daras, Constantine Caramanis, Alex Dimakis, Sanjay Shakkottai

AISTATS 2022 Recoverability Landscape of Tree Structured Markov Random Fields Under Symmetric Noise Ashish Katiyar, Soumya Basu, Vatsal Shah, Constantine Caramanis

ICML 2022 Asymptotically-Optimal Gaussian Bandits with Side Observations Alexia Atsidakou, Orestis Papadigenopoulos, Constantine Caramanis, Sujay Sanghavi, Sanjay Shakkottai

ICML 2022 Coordinated Attacks Against Contextual Bandits: Fundamental Limits and Defense Mechanisms Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

NeurIPS 2022 Non-Stationary Bandits Under Recharging Payoffs: Improved Planning with Sublinear Regret Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai

COLT 2022 The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance Matthew Faw, Isidoros Tziotis, Constantine Caramanis, Aryan Mokhtari, Sanjay Shakkottai, Rachel Ward

NeurIPS 2022 Tractable Optimality in Episodic Latent MABs Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

AISTATS 2021 Contextual Blocking Bandits Soumya Basu, Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai

AISTATS 2021 On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression Jeongyeol Kwon, Nhat Ho, Constantine Caramanis

ICML 2021 Combinatorial Blocking Bandits with Stochastic Delays Alexia Atsidakou, Orestis Papadigenopoulos, Soumya Basu, Constantine Caramanis, Sanjay Shakkottai

NeurIPS 2021 RL for Latent MDPs: Regret Guarantees and a Lower Bound Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

NeurIPS 2021 Recurrent Submodular Welfare and Matroid Blocking Semi-Bandits Orestis Papadigenopoulos, Constantine Caramanis

NeurIPS 2021 Reinforcement Learning in Reward-Mixing MDPs Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

NeurIPS 2020 Applications of Common Entropy for Causal Inference Murat Kocaoglu, Sanjay Shakkottai, Alexandros G Dimakis, Constantine Caramanis, Sriram Vishwanath

AISTATS 2020 Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-Norm Balls Jiacheng Zhuo, Qi Lei, Alex Dimakis, Constantine Caramanis

AISTATS 2020 EM Converges for a Mixture of Many Linear Regressions Jeongyeol Kwon, Constantine Caramanis

AISTATS 2020 High Dimensional Robust Sparse Regression Liu Liu, Yanyao Shen, Tianyang Li, Constantine Caramanis

ICML 2020 Learning Mixtures of Graphs from Epidemic Cascades Jessica Hoffmann, Soumya Basu, Surbhi Goel, Constantine Caramanis

NeurIPS 2020 Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions Matthew Faw, Rajat Sen, Karthikeyan Shanmugam, Constantine Caramanis, Sanjay Shakkottai

NeurIPS 2020 Robust Compressed Sensing Using Generative Models Ajil Jalal, Liu Liu, Alexandros G Dimakis, Constantine Caramanis

NeurIPS 2020 Second Order Optimality in Decentralized Non-Convex Optimization via Perturbed Gradient Tracking Isidoros Tziotis, Constantine Caramanis, Aryan Mokhtari

COLT 2020 The EM Algorithm Gives Sample-Optimality for Learning Mixtures of Well-Separated Gaussians Jeongyeol Kwon, Constantine Caramanis

COLT 2019 Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression Jeongyeol Kwon, Wei Qian, Constantine Caramanis, Yudong Chen, Damek Davis

NeurIPS 2019 Primal-Dual Block Generalized Frank-Wolfe Qi Lei, Jiacheng Zhuo, Constantine Caramanis, Inderjit S Dhillon, Alexandros G Dimakis

ICML 2019 Robust Estimation of Tree Structured Gaussian Graphical Models Ashish Katiyar, Jessica Hoffmann, Constantine Caramanis

AAAI 2018 Statistical Inference Using SGD Tianyang Li, Liu Liu, Anastasios Kyrillidis, Constantine Caramanis

AISTATS 2017 Minimax Gaussian Classification & Clustering Tianyang Li, Xinyang Yi, Constantine Caramanis, Pradeep Ravikumar

AISTATS 2017 Non-Square Matrix Sensing Without Spurious Local Minima via the Burer-Monteiro Approach Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi

NeurIPS 2016 Fast Algorithms for Robust PCA via Gradient Descent Xinyang Yi, Dohyung Park, Yudong Chen, Constantine Caramanis

NeurIPS 2016 More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu

ICML 2015 Binary Embedding: Fundamental Limits and Fast Algorithm Xinyang Yi, Constantine Caramanis, Eric Price

NeurIPS 2015 Optimal Linear Estimation Under Unknown Nonlinear Transform Xinyang Yi, Zhaoran Wang, Constantine Caramanis, Han Liu

NeurIPS 2015 Regularized EM Algorithms: A Unified Framework and Statistical Guarantees Xinyang Yi, Constantine Caramanis

COLT 2014 A Convex Formulation for Mixed Regression with Two Components: Minimax Optimal Rates Yudong Chen, Xinyang Yi, Constantine Caramanis

ICML 2014 Alternating Minimization for Mixed Linear Regression Xinyang Yi, Constantine Caramanis, Sujay Sanghavi

ICML 2014 Finding Dense Subgraphs via Low-Rank Bilinear Optimization Dimitris Papailiopoulos, Ioannis Mitliagkas, Alexandros Dimakis, Constantine Caramanis

NeurIPS 2014 Greedy Subspace Clustering Dohyung Park, Constantine Caramanis, Sujay Sanghavi

NeurIPS 2013 Memory Limited, Streaming PCA Ioannis Mitliagkas, Constantine Caramanis, Prateek Jain

ICML 2013 Noisy and Missing Data Regression: Distribution-Oblivious Support Recovery Yudong Chen, Constantine Caramanis

ICML 2013 Robust Sparse Regression Under Adversarial Corruption Yudong Chen, Constantine Caramanis, Shie Mannor

AISTATS 2012 Statistical Optimization in High Dimensions Huan Xu, Constantine Caramanis, Shie Mannor

ICML 2011 Robust Matrix Completion and Corrupted Columns Yudong Chen, Huan Xu, Constantine Caramanis, Sujay Sanghavi

COLT 2010 Principal Component Analysis with Contaminated Data: The High Dimensional Case Huan Xu, Constantine Caramanis, Shie Mannor

NeurIPS 2010 Robust PCA via Outlier Pursuit Huan Xu, Constantine Caramanis, Sujay Sanghavi

JMLR 2009 Robustness and Regularization of Support Vector Machines Huan Xu, Constantine Caramanis, Shie Mannor

COLT 2008 Learning in the Limit with Adversarial Disturbances Constantine Caramanis, Shie Mannor

ICML 2008 Rank Minimization via Online Learning Raghu Meka, Prateek Jain, Constantine Caramanis, Inderjit S. Dhillon

NeurIPS 2008 Robust Regression and Lasso Huan Xu, Constantine Caramanis, Shie Mannor

COLT 2004 An Inequality for Nearly Log-Concave Distributions with Applications to Learning Constantine Caramanis, Shie Mannor