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2020 – today
- 2024
[j46]Jiacheng Zhuo, Jeongyeol Kwon, Nhat Ho, Constantine Caramanis:
On the Computational and Statistical Complexity of Over-parameterized Matrix Sensing. J. Mach. Learn. Res. 25: 169:1-169:47 (2024)- [j45]Jeongyeol Kwon
, Wei Qian, Yudong Chen, Constantine Caramanis, Damek Davis, Nhat Ho:
Global Optimality of the EM Algorithm for Mixtures of Two-Component Linear Regressions. IEEE Trans. Inf. Theory 70(9): 6519-6546 (2024) - [c106]Alexia Atsidakou, Constantine Caramanis, Evangelia Gergatsouli, Orestis Papadigenopoulos, Christos Tzamos:
Contextual Pandora's Box. AAAI 2024: 10944-10952 - [c105]Litu Rout, Yujia Chen, Abhishek Kumar, Constantine Caramanis, Sanjay Shakkottai, Wen-Sheng Chu:
Beyond First-Order Tweedie: Solving Inverse Problems using Latent Diffusion. CVPR 2024: 9472-9481 - [c104]Jeongyeol Kwon, Yonathan Efroni, Shie Mannor, Constantine Caramanis:
Prospective Side Information for Latent MDPs. ICML 2024 - [i85]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 abs/2405.17401 (2024) - [i84]Jeongyeol Kwon, Shie Mannor, Constantine Caramanis, Yonathan Efroni:
RL in Latent MDPs is Tractable: Online Guarantees via Off-Policy Evaluation. CoRR abs/2406.01389 (2024) - 2023
- [c103]Matthew Faw, Litu Rout, Constantine Caramanis, Sanjay Shakkottai:
Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD. COLT 2023: 89-160 - [c102]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
Reward-Mixing MDPs with Few Latent Contexts are Learnable. ICML 2023: 18057-18082 - [c101]Alexia Atsidakou, Branislav Kveton, Sumeet Katariya, Constantine Caramanis, Sujay Sanghavi:
Logarithmic Bayes Regret Bounds. NeurIPS 2023 - [c100]Constantine Caramanis, Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos:
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method. NeurIPS 2023 - [c99]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 - [i83]Litu Rout, Advait Parulekar, Constantine Caramanis, Sanjay Shakkottai:
A Theoretical Justification for Image Inpainting using Denoising Diffusion Probabilistic Models. CoRR abs/2302.01217 (2023) - [i82]Matthew Faw, Litu Rout, Constantine Caramanis, Sanjay Shakkottai:
Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD. CoRR abs/2302.06570 (2023) - [i81]Dhiraj Murthy, Constantine Caramanis, Koustav Rudra:
Understanding Lexical Biases when Identifying Gang-related Social Media Communications. CoRR abs/2304.11485 (2023) - [i80]Alexia Atsidakou, Branislav Kveton, Sumeet Katariya, Constantine Caramanis, Sujay Sanghavi:
Logarithmic Bayes Regret Bounds. CoRR abs/2306.09136 (2023) - [i79]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 abs/2307.00619 (2023) - [i78]Constantine Caramanis, Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos:
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Methods. CoRR abs/2310.05309 (2023) - [i77]Jeongyeol Kwon, Yonathan Efroni, Shie Mannor, Constantine Caramanis:
Prospective Side Information for Latent MDPs. CoRR abs/2310.07596 (2023) - [i76]Litu Rout, Yujia Chen, Abhishek Kumar, Constantine Caramanis, Sanjay Shakkottai, Wen-Sheng Chu:
Beyond First-Order Tweedie: Solving Inverse Problems using Latent Diffusion. CoRR abs/2312.00852 (2023) - 2022
- [j44]Matthew Faw, Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai:
Learning To Maximize Welfare with a Reusable Resource. Proc. ACM Meas. Anal. Comput. Syst. 6(2): 27:1-27:30 (2022) - [c98]Ashish Katiyar, Soumya Basu, Vatsal Shah, Constantine Caramanis:
Recoverability Landscape of Tree Structured Markov Random Fields under Symmetric Noise. AISTATS 2022: 9356-9399 - [c97]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 B. 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: 16-25 - [c96]Matthew Faw, Isidoros Tziotis, Constantine Caramanis, Aryan Mokhtari, Sanjay Shakkottai, Rachel A. Ward:
The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance. COLT 2022: 313-355 - [c95]Alexia Atsidakou, Orestis Papadigenopoulos, Constantine Caramanis, Sujay Sanghavi, Sanjay Shakkottai:
Asymptotically-Optimal Gaussian Bandits with Side Observations. ICML 2022: 1057-1077 - [c94]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms. ICML 2022: 11772-11789 - [c93]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
Tractable Optimality in Episodic Latent MABs. NeurIPS 2022 - [c92]Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai:
Non-Stationary Bandits under Recharging Payoffs: Improved Planning with Sublinear Regret. NeurIPS 2022 - [c91]Matthew Faw, Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai:
Learning To Maximize Welfare with a Reusable Resource. SIGMETRICS (Abstracts) 2022: 111-112 - [c90]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: 1298-1325 - [i75]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms. CoRR abs/2201.12700 (2022) - [i74]Matthew Faw, Isidoros Tziotis, Constantine Caramanis, Aryan Mokhtari, Sanjay Shakkottai, Rachel A. Ward:
The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance. CoRR abs/2202.05791 (2022) - [i73]Alexia Atsidakou, Constantine Caramanis, Evangelia Gergatsouli, Orestis Papadigenopoulos, Christos Tzamos:
Contextual Pandora's Box. CoRR abs/2205.13114 (2022) - [i72]Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai:
Non-Stationary Bandits under Recharging Payoffs: Improved Planning with Sublinear Regret. CoRR abs/2205.14790 (2022) - [i71]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
Reward-Mixing MDPs with a Few Latent Contexts are Learnable. CoRR abs/2210.02594 (2022) - [i70]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
Tractable Optimality in Episodic Latent MABs. CoRR abs/2210.03528 (2022) - 2021
- [c89]Soumya Basu, Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai:
Contextual Blocking Bandits. AISTATS 2021: 271-279 - [c88]Jeongyeol Kwon, Nhat Ho, Constantine Caramanis:
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression. AISTATS 2021: 1405-1413 - [c87]Alexia Atsidakou, Orestis Papadigenopoulos, Soumya Basu, Constantine Caramanis, Sanjay Shakkottai:
Combinatorial Blocking Bandits with Stochastic Delays. ICML 2021: 404-413 - [c86]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
Reinforcement Learning in Reward-Mixing MDPs. NeurIPS 2021: 2253-2264 - [c85]Orestis Papadigenopoulos, Constantine Caramanis:
Recurrent Submodular Welfare and Matroid Blocking Semi-Bandits. NeurIPS 2021: 23334-23346 - [c84]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
RL for Latent MDPs: Regret Guarantees and a Lower Bound. NeurIPS 2021: 24523-24534 - [i69]Orestis Papadigenopoulos, Constantine Caramanis:
Recurrent Submodular Welfare and Matroid Blocking Bandits. CoRR abs/2102.00321 (2021) - [i68]Jiacheng Zhuo, Jeongyeol Kwon, Nhat Ho, Constantine Caramanis:
On the computational and statistical complexity of over-parameterized matrix sensing. CoRR abs/2102.02756 (2021) - [i67]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
RL for Latent MDPs: Regret Guarantees and a Lower Bound. CoRR abs/2102.04939 (2021) - [i66]Ashish Katiyar, Soumya Basu, Vatsal Shah, Constantine Caramanis:
Robust Estimation of Tree Structured Markov Random Fields. CoRR abs/2102.08554 (2021) - [i65]Constantine Caramanis, Matthew Faw, Orestis Papadigenopoulos, Emmanouil Pountourakis:
Single-Sample Prophet Inequalities Revisited. CoRR abs/2103.13089 (2021) - [i64]Alexia Atsidakou, Orestis Papadigenopoulos, Soumya Basu, Constantine Caramanis, Sanjay Shakkottai:
Combinatorial Blocking Bandits with Stochastic Delays. CoRR abs/2105.10625 (2021) - [i63]Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor:
Reinforcement Learning in Reward-Mixing MDPs. CoRR abs/2110.03743 (2021) - [i62]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 abs/2111.03174 (2021) - 2020
- [c83]Liu Liu, Yanyao Shen, Tianyang Li, Constantine Caramanis:
High Dimensional Robust Sparse Regression. AISTATS 2020: 411-421 - [c82]Jiacheng Zhuo, Qi Lei, Alex Dimakis, Constantine Caramanis:
Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls. AISTATS 2020: 1464-1474 - [c81]Jeongyeol Kwon, Constantine Caramanis:
EM Converges for a Mixture of Many Linear Regressions. AISTATS 2020: 1727-1736 - [c80]Jeongyeol Kwon, Constantine Caramanis:
The EM Algorithm gives Sample-Optimality for Learning Mixtures of Well-Separated Gaussians. COLT 2020: 2425-2487 - [c79]Jessica Hoffmann, Soumya Basu, Surbhi Goel, Constantine Caramanis:
Learning Mixtures of Graphs from Epidemic Cascades. ICML 2020: 4342-4352 - [c78]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 - [c77]Ajil Jalal, Liu Liu, Alexandros G. Dimakis, Constantine Caramanis:
Robust compressed sensing using generative models. NeurIPS 2020 - [c76]Murat Kocaoglu, Sanjay Shakkottai, Alexandros G. Dimakis, Constantine Caramanis, Sriram Vishwanath:
Applications of Common Entropy for Causal Inference. NeurIPS 2020 - [c75]Isidoros Tziotis, Constantine Caramanis, Aryan Mokhtari:
Second Order Optimality in Decentralized Non-Convex Optimization via Perturbed Gradient Tracking. NeurIPS 2020 - [i61]Jeongyeol Kwon, Constantine Caramanis:
EM Algorithm is Sample-Optimal for Learning Mixtures of Well-Separated Gaussians. CoRR abs/2002.00329 (2020) - [i60]Soumya Basu, Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai:
Contextual Blocking Bandits. CoRR abs/2003.03426 (2020) - [i59]Jeongyeol Kwon, Nhat Ho, Constantine Caramanis:
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression. CoRR abs/2006.02601 (2020) - [i58]Ashish Katiyar, Vatsal Shah, Constantine Caramanis:
Robust Estimation of Tree Structured Ising Models. CoRR abs/2006.05601 (2020) - [i57]Ajil Jalal, Liu Liu, Alexandros G. Dimakis, Constantine Caramanis:
Robust compressed sensing of generative models. CoRR abs/2006.09461 (2020) - [i56]Jiacheng Zhuo, Liu Liu, Constantine Caramanis:
Robust Structured Statistical Estimation via Conditional Gradient Type Methods. CoRR abs/2007.03572 (2020) - [i55]Jessica Hoffmann, Matt Jordan, Constantine Caramanis:
Quarantines as a Targeted Immunization Strategy. CoRR abs/2008.08262 (2020)
2010 – 2019
- 2019
- [j43]Jessica Hoffmann, Constantine Caramanis:
Learning Graphs from Noisy Epidemic Cascades. Proc. ACM Meas. Anal. Comput. Syst. 3(2): 40:1-40:34 (2019) - [c74]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: 2055-2110 - [c73]Ashish Katiyar, Jessica Hoffmann, Constantine Caramanis:
Robust Estimation of Tree Structured Gaussian Graphical Models. ICML 2019: 3292-3300 - [c72]Qi Lei, Jiacheng Zhuo, Constantine Caramanis, Inderjit S. Dhillon, Alexandros G. Dimakis:
Primal-Dual Block Generalized Frank-Wolfe. NeurIPS 2019: 13866-13875 - [c71]Jessica H. Hoffmann, Constantine Caramanis:
Learning Graphs from Noisy Epidemic Cascades. SIGMETRICS (Abstracts) 2019: 3-4 - [i54]Liu Liu, Tianyang Li, Constantine Caramanis:
High Dimensional Robust Estimation of Sparse Models via Trimmed Hard Thresholding. CoRR abs/1901.08237 (2019) - [i53]Ashish Katiyar, Jessica Hoffmann, Constantine Caramanis:
Robust estimation of tree structured Gaussian Graphical Model. CoRR abs/1901.08770 (2019) - [i52]Jessica Hoffmann, Constantine Caramanis:
Learning Graphs from Noisy Epidemic Cascades. CoRR abs/1903.02650 (2019) - [i51]Jeongyeol Kwon, Constantine Caramanis:
EM Converges for a Mixture of Many Linear Regressions. CoRR abs/1905.12106 (2019) - [i50]Qi Lei, Jiacheng Zhuo, Constantine Caramanis, Inderjit S. Dhillon, Alexandros G. Dimakis:
Primal-Dual Block Frank-Wolfe. CoRR abs/1906.02436 (2019) - [i49]Jessica Hoffmann, Soumya Basu, Surbhi Goel, Constantine Caramanis:
Disentangling Mixtures of Epidemics on Graphs. CoRR abs/1906.06057 (2019) - [i48]Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu:
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning. CoRR abs/1907.06257 (2019) - [i47]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 abs/1907.10154 (2019) - [i46]Jiacheng Zhuo, Qi Lei, Alexandros G. Dimakis, Constantine Caramanis:
Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls. CoRR abs/1910.07703 (2019) - 2018
- [j42]Jessica Hoffmann, Constantine Caramanis:
The Cost of Uncertainty in Curing Epidemics. Proc. ACM Meas. Anal. Comput. Syst. 2(2): 31:1-31:33 (2018) - [j41]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): 2165-2204 (2018) - [j40]Zeina Sinno, Constantine Caramanis, Alan C. Bovik:
Towards a Closed Form Second-Order Natural Scene Statistics Model. IEEE Trans. Image Process. 27(7): 3194-3209 (2018) - [j39]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): 1738-1766 (2018) - [j38]Eli A. Meirom, Constantine Caramanis, Shie Mannor, Ariel Orda, Sanjay Shakkottai:
Detecting Cascades from Weak Signatures. IEEE Trans. Netw. Sci. Eng. 5(4): 313-325 (2018) - [c70]Tianyang Li, Liu Liu, Anastasios Kyrillidis, Constantine Caramanis:
Statistical Inference Using SGD. AAAI 2018: 3571-3578 - [c69]Zeina Sinno, Constantine Caramanis, Alan C. Bovik:
Second Order Natural Scene Statistics Model of Blind Image Quality Assessment. ICASSP 2018: 1238-1242 - [c68]Jessica Hoffmann, Constantine Caramanis:
The Cost of Uncertainty in Curing Epidemics. SIGMETRICS (Abstracts) 2018: 11-13 - [i45]Mikhail Kazdagli, Constantine Caramanis, Sanjay Shakkottai, Mohit Tiwari:
The Shape of Alerts: Detecting Malware Using Distributed Detectors by Robustly Amplifying Transient Correlations. CoRR abs/1803.00883 (2018) - [i44]Tianyang Li, Anastasios Kyrillidis, Liu Liu, Constantine Caramanis:
Approximate Newton-based statistical inference using only stochastic gradients. CoRR abs/1805.08920 (2018) - [i43]Liu Liu, Yanyao Shen, Tianyang Li, Constantine Caramanis:
High Dimensional Robust Sparse Regression. CoRR abs/1805.11643 (2018) - [i42]Murat Kocaoglu, Sanjay Shakkottai, Alexandros G. Dimakis, Constantine Caramanis, Sriram Vishwanath:
Entropic Latent Variable Discovery. CoRR abs/1807.10399 (2018) - [i41]Jeongyeol Kwon, Constantine Caramanis:
Global Convergence of EM Algorithm for Mixtures of Two Component Linear Regression. CoRR abs/1810.05752 (2018) - 2017
- [c67]Tianyang Li, Xinyang Yi, Constantine Caramanis, Pradeep Ravikumar:
Minimax Gaussian Classification & Clustering. AISTATS 2017: 1-9 - [c66]Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi:
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach. AISTATS 2017: 65-74 - [i40]Tianyang Li, Liu Liu, Anastasios Kyrillidis, Constantine Caramanis:
Statistical inference using SGD. CoRR abs/1705.07477 (2017) - [i39]Mikhail Kazdagli, Constantine Caramanis, Sanjay Shakkottai, Mohit Tiwari:
Exploiting Latent Attack Semantics for Intelligent Malware Detection. CoRR abs/1708.01864 (2017) - [i38]Jessica Hoffmann, Constantine Caramanis:
The Cost of Uncertainty in Curing Epidemics. CoRR abs/1711.00167 (2017) - [i37]Anastasios Kyrillidis, Amir Kalev, Dohyung Park, Srinadh Bhojanapalli, Constantine Caramanis, Sujay Sanghavi:
Provable quantum state tomography via non-convex methods. CoRR abs/1711.02524 (2017) - [i36]Guy Tennenholtz, Constantine Caramanis, Shie Mannor:
The Stochastic Firefighter Problem. CoRR abs/1711.08237 (2017) - 2016
- [j37]Huan Xu, Constantine Caramanis, Shie Mannor:
Statistical Optimization in High Dimensions. Oper. Res. 64(4): 958-979 (2016) - [j36]Qiaoyang Ye, Ozgun Yilmaz Bursalioglu, Haralabos C. Papadopoulos, Constantine Caramanis, Jeffrey G. Andrews:
User Association and Interference Management in Massive MIMO HetNets. IEEE Trans. Commun. 64(5): 2049-2065 (2016) - [j35]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): 503-526 (2016) - [c65]Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi:
Finding low-rank solutions to smooth convex problems via the Burer-Monteiro approach. Allerton 2016: 439-446 - [c64]Ye Wang, Constantine Caramanis, Michael Orshansky:
PolyGP: Improving GP-based analog optimization through accurate high-order monomials and semidefinite relaxation. DATE 2016: 1423-1428 - [c63]Ye Wang, Constantine Caramanis, Michael Orshansky:
Exploiting randomness in sketching for efficient hardware implementation of machine learning applications. ICCAD 2016: 114 - [c62]Xinyang Yi, Dohyung Park, Yudong Chen, Constantine Caramanis:
Fast Algorithms for Robust PCA via Gradient Descent. NIPS 2016: 4152-4160 - [c61]Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu:
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning. NIPS 2016: 4475-4483 - [i35]Xinyang Yi, Dohyung Park, Yudong Chen, Constantine Caramanis:
Fast Algorithms for Robust PCA via Gradient Descent. CoRR abs/1605.07784 (2016) - [i34]Dohyung Park, Anastasios Kyrillidis, Srinadh Bhojanapalli, Constantine Caramanis, Sujay Sanghavi:
Provable non-convex projected gradient descent for a class of constrained matrix optimization problems. CoRR abs/1606.01316 (2016) - [i33]Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi:
Finding Low-rank Solutions to Matrix Problems, Efficiently and Provably. CoRR abs/1606.03168 (2016) - [i32]Xinyang Yi, Constantine Caramanis, Sujay Sanghavi:
Solving a Mixture of Many Random Linear Equations by Tensor Decomposition and Alternating Minimization. CoRR abs/1608.05749 (2016) - [i31]Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi:
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach. CoRR abs/1609.03240 (2016) - 2015
- [j34]Amin Abdel Khalek, Constantine Caramanis, Robert W. Heath Jr.:
Delay-Constrained Video Transmission: Quality-Driven Resource Allocation and Scheduling. IEEE J. Sel. Top. Signal Process. 9(1): 60-75 (2015) - [j33]Ioannis Mitliagkas, Michael Borokhovich, Alexandros G. Dimakis, Constantine Caramanis:
FrogWild! - Fast PageRank Approximations on Graph Engines. Proc. VLDB Endow. 8(8): 874-885 (2015) - [j32]Aditya Gopalan, Constantine Caramanis, Sanjay Shakkottai:
Wireless scheduling with partial channel state information: large deviations and optimality. Queueing Syst. Theory Appl. 80(4): 293-340 (2015) - [j31]Qiaoyang Ye, Mazin Al-Shalash, Constantine Caramanis, Jeffrey G. Andrews:
Distributed Resource Allocation in Device-to-Device Enhanced Cellular Networks. IEEE Trans. Commun. 63(2): 441-454 (2015) - [j30]Chris Milling, Constantine Caramanis, Shie Mannor, Sanjay Shakkottai:
Distinguishing Infections on Different Graph Topologies. IEEE Trans. Inf. Theory 61(6): 3100-3120 (2015) - [j29]Amin Abdel Khalek, Constantine Caramanis, Robert W. Heath Jr.:
Loss Visibility Optimized Real-Time Video Transmission Over MIMO Systems. IEEE Trans. Multim. 17(10): 1802-1817 (2015) - [c60]Ye Wang, Meng Li, Xinyang Yi, Zhao Song, Michael Orshansky, Constantine Caramanis:
Novel power grid reduction method based on L1 regularization. DAC 2015: 93:1-93:6 - [c59]Xinyang Yi, Constantine Caramanis, Eric Price:
Binary Embedding: Fundamental Limits and Fast Algorithm. ICML 2015: 2162-2170 - [c58]Chris Milling, Constantine Caramanis, Shie Mannor, Sanjay Shakkottai:
Local detection of infections in heterogeneous networks. INFOCOM 2015: 1517-1525 - [c57]Xinyang Yi, Zhaoran Wang, Constantine Caramanis, Han Liu:
Optimal Linear Estimation under Unknown Nonlinear Transform. NIPS 2015: 1549-1557 - [c56]Xinyang Yi, Constantine Caramanis:
Regularized EM Algorithms: A Unified Framework and Statistical Guarantees. NIPS 2015: 1567-1575 - [c55]