Constantine Caramanis

Infilling Score: A Pretraining Data Detection Algorithm for Large Language Models ICLR 2025 On Mitigating Affinity Bias through Bandits with Evolving Biased Feedback ICML 2025 RB-Modulation: Training-Free Stylization using Reference-Based Modulation ICLR 2025 Semantic Image Inversion and Editing using Rectified Stochastic Differential Equations ICLR 2025 Beyond First-Order Tweedie: Solving Inverse Problems using Latent Diffusion CVPR 2024 Contextual Pandora’s Box AAAI 2024 On the Computational and Statistical Complexity of Over-parameterized Matrix Sensing JMLR 2024 Optimization Can Learn Johnson Lindenstrauss Embeddings NeurIPS 2024 Prospective Side Information for Latent MDPs ICML 2024 RL in Latent MDPs is Tractable: Online Guarantees via Off-Policy Evaluation NeurIPS 2024 Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD COLT 2023 Finite-Time Logarithmic Bayes Regret Upper Bounds NeurIPS 2023 Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method NeurIPS 2023 Reward-Mixing MDPs with Few Latent Contexts are Learnable ICML 2023 Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models NeurIPS 2023 Asymptotically-Optimal Gaussian Bandits with Side Observations ICML 2022 Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms ICML 2022 Non-Stationary Bandits under Recharging Payoffs: Improved Planning with Sublinear Regret NeurIPS 2022 Recoverability Landscape of Tree Structured Markov Random Fields under Symmetric Noise AISTATS 2022 The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance COLT 2022 Tractable Optimality in Episodic Latent MABs NeurIPS 2022 Combinatorial Blocking Bandits with Stochastic Delays ICML 2021 Contextual Blocking Bandits AISTATS 2021 On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression AISTATS 2021 Recurrent Submodular Welfare and Matroid Blocking Semi-Bandits NeurIPS 2021 Reinforcement Learning in Reward-Mixing MDPs NeurIPS 2021 RL for Latent MDPs: Regret Guarantees and a Lower Bound NeurIPS 2021 Applications of Common Entropy for Causal Inference NeurIPS 2020 Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls AISTATS 2020 EM Converges for a Mixture of Many Linear Regressions AISTATS 2020 High Dimensional Robust Sparse Regression AISTATS 2020 Learning Mixtures of Graphs from Epidemic Cascades ICML 2020 Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions NeurIPS 2020 Robust compressed sensing using generative models NeurIPS 2020 Second Order Optimality in Decentralized Non-Convex Optimization via Perturbed Gradient Tracking NeurIPS 2020 The EM Algorithm gives Sample-Optimality for Learning Mixtures of Well-Separated Gaussians COLT 2020 Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression COLT 2019 Primal-Dual Block Generalized Frank-Wolfe NeurIPS 2019 Robust Estimation of Tree Structured Gaussian Graphical Models ICML 2019 Fast Algorithms for Robust PCA via Gradient Descent NeurIPS 2016 More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning NeurIPS 2016 Binary Embedding: Fundamental Limits and Fast Algorithm ICML 2015 Optimal Linear Estimation under Unknown Nonlinear Transform NeurIPS 2015 Regularized EM Algorithms: A Unified Framework and Statistical Guarantees NeurIPS 2015 A Convex Formulation for Mixed Regression with Two Components: Minimax Optimal Rates COLT 2014 Alternating Minimization for Mixed Linear Regression ICML 2014 Finding Dense Subgraphs via Low-Rank Bilinear Optimization ICML 2014 Greedy Subspace Clustering NeurIPS 2014 Memory Limited, Streaming PCA NeurIPS 2013 Noisy and Missing Data Regression: Distribution-Oblivious Support Recovery ICML 2013 Robust Sparse Regression under Adversarial Corruption ICML 2013 Statistical Optimization in High Dimensions AISTATS 2012 Robust PCA via Outlier Pursuit NeurIPS 2010 Robustness and Regularization of Support Vector Machines JMLR 2009 Robust Regression and Lasso NeurIPS 2008