Constantine Caramanis

Constantine Caramanis's AcademicInfluence.com Rankings

Engineering

#3274

World Rank

#4320

Historical Rank

Electrical Engineering

#710

World Rank

#774

Historical Rank

engineering Degrees

Constantine Caramanis

Mathematics

#5498

World Rank

#7731

Historical Rank

Control Theory

#22

World Rank

#24

Historical Rank

Measure Theory

#765

World Rank

#1024

Historical Rank

mathematics Degrees

Download Badge

Engineering
Mathematics

Constantine Caramanis's Degrees

PhD Electrical Engineering Stanford University
Masters Electrical Engineering Stanford University
Bachelors Electrical Engineering Stanford University

Why Is Constantine Caramanis Influential?

(Suggest an Edit or Addition)

(See a Problem?)

Constantine Caramanis's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

What is ergodic theory (1963) (3687)
Theory and Applications of Robust Optimization (2010) (2303)
User Association for Load Balancing in Heterogeneous Cellular Networks (2012) (1138)
Robust PCA via Outlier Pursuit (2010) (733)
Robustness and Regularization of Support Vector Machines (2008) (425)
Robust Regression and Lasso (2008) (268)
Fast Algorithms for Robust PCA via Gradient Descent (2016) (234)
Finite Adaptability in Multistage Linear Optimization (2010) (183)
Sparse Algorithms Are Not Stable: A No-Free-Lunch Theorem (2008) (183)
Low-Rank Matrix Recovery From Errors and Erasures (2011) (174)
Memory Limited, Streaming PCA (2013) (157)
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach (2016) (151)
Robust Sparse Regression under Adversarial Corruption (2013) (120)
Outlier-Robust PCA: The High-Dimensional Case (2013) (118)
Distributed Resource Allocation in Device-to-Device Enhanced Cellular Networks (2014) (113)
Adaptation in Convolutionally Coded MIMO-OFDM Wireless Systems Through Supervised Learning and SNR Ordering (2010) (106)
Greedy Subspace Clustering (2014) (98)
Design of Linear Equalizers Optimized for the Structural Similarity Index (2008) (97)
Robust Matrix Completion and Corrupted Columns (2011) (91)
Resource Optimization in Device-to-Device Cellular Systems Using Time-Frequency Hopping (2013) (90)
Modeling the Time—Varying Subjective Quality of HTTP Video Streams With Rate Adaptations (2013) (89)
Equitable and Efficient Coordination in Traffic Flow Management (2012) (89)
On/off macrocells and load balancing in heterogeneous cellular networks (2013) (83)
Delay-Constrained Video Transmission: Quality-Driven Resource Allocation and Scheduling (2013) (79)
A Cross-Layer Design for Perceptual Optimization Of H.264/SVC with Unequal Error Protection (2012) (76)
User Association and Interference Management in Massive MIMO HetNets (2015) (67)
On Wireless Scheduling With Partial Channel-State Information (2012) (67)
Regularized EM Algorithms: A Unified Framework and Statistical Guarantees (2015) (66)
Rank minimization via online learning (2008) (66)
Robust Matrix Completion with Corrupted Columns (2011) (62)
Finding Low-rank Solutions to Matrix Problems, Efficiently and Provably (2016) (60)
A distributional interpretation of robust optimization (2010) (60)
A Convex Formulation for Mixed Regression with Two Components: Minimax Optimal Rates (2013) (60)
High Dimensional Robust Sparse Regression (2018) (56)
Principal Component Analysis with Contaminated Data: The High Dimensional Case (2010) (56)
Noisy and Missing Data Regression: Distribution-Oblivious Support Recovery (2013) (48)
Solving a Mixture of Many Random Linear Equations by Tensor Decomposition and Alternating Minimization (2016) (46)
Enabling efficient analog synthesis by coupling sparse regression and polynomial optimization (2014) (42)
Global Convergence of EM Algorithm for Mixtures of Two Component Linear Regression (2018) (41)
Optimization Under Probabilistic Envelope Constraints (2012) (40)
FrogWild! - Fast PageRank Approximations on Graph Engines (2015) (40)
RL for Latent MDPs: Regret Guarantees and a Lower Bound (2021) (38)
Binary Embedding: Fundamental Limits and Fast Algorithm (2015) (37)
Network forensics: random infection vs spreading epidemic (2012) (36)
Adaptability via sampling (2007) (33)
SSIM-optimal linear image restoration (2008) (33)
Provable compressed sensing quantum state tomography via non-convex methods (2018) (32)
Optimal Linear Estimation under Unknown Nonlinear Transform (2015) (32)
A dynamic system model of time-varying subjective quality of video streams over HTTP (2013) (31)
Provable Burer-Monteiro factorization for a class of norm-constrained matrix problems (2016) (29)
Efficient Energy Delivery Management for PHEVs (2010) (28)
Towards an optimal user association in heterogeneous cellular networks (2012) (28)
Bounds on linear PDEs via semidefinite optimization (2006) (28)
Alternating Minimization for Mixed Linear Regression (2013) (27)
Matrix Completion With Column Manipulation: Near-Optimal Sample-Robustness-Rank Tradeoffs (2011) (25)
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression (2020) (25)
A Supervised Learning Approach to Adaptation in Practical MIMO-OFDM Wireless Systems (2008) (24)
Statistical inference using SGD (2017) (24)
User rankings from comparisons: Learning permutations in high dimensions (2011) (24)
Robust compressed sensing using generative models (2020) (23)
Provable non-convex projected gradient descent for a class of constrained matrix optimization problems (2016) (22)
EM Converges for a Mixture of Many Linear Regressions (2019) (21)
Detecting epidemics using highly noisy data (2013) (21)
Reinforcement Learning for Link Adaptation in MIMO-OFDM Wireless Systems (2010) (21)
Finding Dense Subgraphs via Low-Rank Bilinear Optimization (2014) (21)
Multiclass support vector machines for adaptation in MIMO-OFDM wireless systems (2009) (20)
Adaptable optimization: theory and algorithms (2006) (20)
A tractable model for optimizing device-to-device communications in downlink cellular networks (2014) (20)
Robust High Dimensional Sparse Regression and Matching Pursuit (2013) (19)
On identifying the causative network of an epidemic (2012) (19)
Localized Epidemic Detection in Networks with Overwhelming Noise (2014) (19)
On the computational and statistical complexity of over-parameterized matrix sensing (2021) (18)
Predictable Equation-Based Analog Optimization Based on Explicit Capture of Modeling Error Statistics (2012) (17)
Statistical Optimization in High Dimensions (2012) (17)
Device-to-device modeling and analysis with a modified Matern hardcore BS location model (2013) (17)
The EM Algorithm gives Sample-Optimality for Learning Mixtures of Well-Separated Gaussians (2020) (16)
Orthogonal Matching Pursuit with Noisy and Missing Data: Low and High Dimensional Results (2012) (16)
Analyzing Queuing Systems with Coupled Processors through Semidefinite Programming (2008) (16)
Robust estimation of tree structured Gaussian Graphical Model (2019) (15)
Risk sensitive robust support vector machines (2009) (15)
Scheduling Algorithms for Providing Flexible , Rate-Based , Quality of Service Guarantees for Packet-Switching in Banyan Networks (2004) (15)
Joint Source-Channel Adaptation for Perceptually Optimized Scalable Video Transmission (2011) (14)
High Dimensional Robust Estimation of Sparse Models via Trimmed Hard Thresholding (2019) (14)
Towards a Closed Form Second-Order Natural Scene Statistics Model (2018) (14)
Rate Bounds on SSIM Index of Quantized Image DCT Coefficients (2008) (14)
Low-delay wireless scheduling with partial channel-state information (2012) (13)
Convex and Nonconvex Formulations for Mixed Regression With Two Components: Minimax Optimal Rates (2018) (12)
Single-Sample Prophet Inequalities via Greedy-Ordered Selection (2021) (12)
Contextual Blocking Bandits (2020) (12)
Loss Visibility Optimized Real-Time Video Transmission Over MIMO Systems (2013) (11)
Distinguishing Infections on Different Graph Topologies (2013) (11)
System-Level Optimization in Wireless Networks: Managing Interference and Uncertainty via Robust Optimization (2012) (11)
Minimax Gaussian Classification & Clustering (2017) (10)
Provable quantum state tomography via non-convex methods (2017) (10)
Robust Estimation of Tree Structured Ising Models (2020) (10)
The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance (2022) (10)
The Cost of Uncertainty in Curing Epidemics (2017) (10)
Primal-Dual Block Generalized Frank-Wolfe (2019) (9)
Video-aware MIMO precoding with packet prioritization and unequal modulation (2012) (9)
Local detection of infections in heterogeneous networks (2015) (9)
Reinforcement Learning in Reward-Mixing MDPs (2021) (8)
Learning Graphs from Noisy Epidemic Cascades (2019) (8)
Applications of Common Entropy for Causal Inference (2020) (8)
Efficient Algorithms for Budget-Constrained Markov Decision Processes (2014) (8)
An Inequality for Nearly Log-Concave Distributions With Applications to Learning (2004) (8)
Mitigation of intra-array SRAM variability using adaptive voltage architecture (2009) (7)
Robust compressed sensing of generative models (2020) (7)
Streaming, Memory-limited PCA (2013) (7)
Robustness, Risk, and Regularization in Support Vector Machines (2008) (7)
Learning in the Limit with Adversarial Disturbances (2008) (7)
A Theoretical Justification for Image Inpainting using Denoising Diffusion Probabilistic Models (2023) (7)
Video quality-maximizing resource allocation and scheduling with statistical delay guarantees (2013) (7)
Inter-cell relay cooperation in heterogeneous cellular uplink systems (2008) (6)
Second Order Natural Scene Statistics Model of Blind Image Quality Assessment (2018) (6)
Wireless scheduling with partial channel state information: large deviations and optimality (2014) (6)
High dimensional Principal Component Analysis with contaminated data (2009) (6)
Entropic Latent Variable Discovery (2018) (6)
Distributed link adaptation for multicast traffic in MIMO-OFDM systems (2011) (6)
Sparse Algorithms Are Not Stable (2012) (6)
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning (2019) (5)
Optimal feedback allocation algorithms for multi-user uplink (2009) (5)
Quarantines as a Targeted Immunization Strategy (2020) (5)
Sequential Vaccination for Containing Epidemics (2020) (5)
PolyGP: Improving GP-based analog optimization through accurate high-order monomials and semidefinite relaxation (2016) (4)
Learning Mixtures of Graphs from Epidemic Cascades (2019) (4)
An algorithm for exploiting modeling error statistics to enable robust analog optimization (2010) (4)
Queue-based sub-carrier grouping for feedback reduction in OFDMA systems (2012) (4)
Approximate Newton-based statistical inference using only stochastic gradients (2018) (4)
Limited feedback for cognitive radio networks using compressed sensing (2010) (4)
Detecting Cascades from Weak Signatures (2018) (4)
Single-Sample Prophet Inequalities Revisited (2021) (4)
On file sharing over a wireless social network (2011) (4)
EM Algorithm is Sample-Optimal for Learning Mixtures of Well-Separated Gaussians (2020) (4)
Modeling and Optimization Techniques for Yield-Aware SRAM Post-Silicon Tuning (2014) (3)
Solving linear partial differential equations via semidefinite optimization (2001) (3)
The Cost of Uncertainty in Curing Epidemics (2018) (3)
Procedural Content Generation of Angry Birds Levels Using Monte Carlo Tree Search APPROVED BY SUPERVISING COMMITTEE: (2016) (3)
Online learning for quality-driven unequal protection of scalable video (2012) (3)
Prioritized multimode precoding for joint minimization of source-channel video distortions (2012) (3)
Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls (2019) (3)
On Sharing Viral Video over an Ad Hoc Wireless Network (2011) (3)
Combinatorial Blocking Bandits with Stochastic Delays (2021) (3)
Exploiting Sparse Dynamics For Bandwidth Reduction In Cooperative Sensing Systems (2012) (2)
Recurrent Submodular Welfare and Matroid Blocking Semi-Bandits (2021) (2)
Finding low-rank solutions to smooth convex problems via the Burer-Monteiro approach (2016) (2)
Robust dimensionality reduction for high-dimension data (2008) (2)
System level optimization in wireless networks with uncertain customer arrival rates (2008) (2)
Recurrent Submodular Welfare and Matroid Blocking Bandits (2021) (2)
Novel power grid reduction method based on L1 regularization (2015) (2)
Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms (2022) (2)
Non-Convex Optimization via Real Algebraic Geometry (2001) (2)
Anytime Information Theory : A Summary of Anant Sahai ’ s Ph . D . Thesis (2001) (2)
The value of adaptability (2005) (2)
Regularized EM Algorithms: A Unified Framework and Provable Statistical Guarantees (2015) (2)
Geometry , Moments , and Semidefinite Optimization (2002) (2)
Feedback Allocation for OFDMA Systems With Slow Frequency-Domain Scheduling (2012) (2)
Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD (2023) (2)
The Stochastic Firefighter Problem (2017) (2)
On the Value of Coordination and Delayed Queue Information in Multicellular Scheduling (2013) (1)
Perceptual Optimization of Large-Scale Wireless Video Networks (2013) (1)
A Convex Formulation for Mixed Regression: Near Optimal Rates in the Face of Noise (2013) (1)
The Shape of Alerts: Detecting Malware Using Distributed Detectors by Robustly Amplifying Transient Correlations (2018) (1)
Learning To Maximize Welfare with a Reusable Resource (2022) (1)
Robust PCA for High-Dimensional Data (2008) (1)
Asymptotically-Optimal Gaussian Bandits with Side Observations (2022) (1)
A Bayesian approach to data-driven optimization under uncertainty (2007) (1)
Contextual Pandora's Box (2022) (1)
Robust Estimation of Tree Structured Markov Random Fields (2021) (1)
Non-Stationary Bandits under Recharging Payoffs: Improved Planning with Sublinear Regret (2022) (1)
Second Order Optimality in Decentralized Non-Convex Optimization via Perturbed Gradient Tracking (2020) (1)
Approximating Fluid Schedules in Crossbar Packet-Switches and Banyan Networks (2006) (1)
Disentangling Mixtures of Epidemics on Graphs (2019) (0)
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions (2019) (0)
Survey Propagation : Iterative Solutions to Constraint Satisfaction Problems (2003) (0)
Learning To Maximize Welfare with a Reusable Resource (2022) (0)
Executive Summary: Imputing Missing Data via Sparse Reconstruction Techniques (2017) (0)
Recoverability Landscape of Tree Structured Markov Random Fields under Symmetric Noise (2021) (0)
Exploiting randomness in sketching for efficient hardware implementation of machine learning applications (2016) (0)
Tractable Optimality in Episodic Latent MABs (2022) (0)
Learning Graphs from Noisy Epidemic Cascades (2019) (0)
Understanding Lexical Biases when Identifying Gang-related Social Media Communications (2023) (0)
Simple algorithms for sparse linear regression with uncertain covariates (2012) (0)
Large-scale linear programs in planning and prediction. (2017) (0)
Early and Robust Malware Detection in Enterprise Networks (2016) (0)
The Invariance of the Index of Elliptic Operators (1999) (0)
Imputing missing data via sparse reconstruction techniques. (2017) (0)
Supplement to “ Binary Embedding : Fundamental Limits and Fast Algorithm " (2015) (0)
Project : Streaming PCA with Many Missing Entries (2016) (0)
The Cost of Uncertainty in Curing Epidemics (2017) (0)
Reward-Mixing MDPs with a Few Latent Contexts are Learnable (2022) (0)
Dynamic Feedback Allocation Algorithms for Interference Management in MIMO Uplink (2010) (0)
Wireless scheduling with partial channel state information: large deviations and optimality (2015) (0)
Exploiting Latent Attack Semantics for Intelligent Malware Detection (2017) (0)
Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks (2022) (0)
Large-scale Optimization with Small- scale Data (2021) (0)
Design of power-optimal buffers tunable to process variability (2010) (0)
Provable compressed sensing quantum state tomography via non-convex methods (2018) (0)
Graphs with Cycles : A Summary of Martin Wainwright ’ s Ph . D . Thesis (2002) (0)
Robust Structured Statistical Estimation via Conditional Gradient Type Methods (2020) (0)
Learning Graphs from Noisy Epidemic Cascades (2019) (0)
Second-Order Optimality in Non-Convex Decentralized Optimization via Perturbed Gradient Tracking (2020) (0)
Targeted L1L2: Naturalness-constrained image recovery from random projections (2014) (0)
Uniform Glivenko–Cantelli Classes (2000) (0)
Noisy and Missing Data Regression Supplementary Material (2013) (0)
System Level Optimization in Wireless Networks : Managing Interference with Robust Optimization (2010) (0)
FrogWild! (2015) (0)
Robustness in High Dimensions: Greedy Algorithms (2012) (0)
Network Information Theory Summary: Multi-access and Broadcast Channels (0)
Robust Sparse Regression under Adversarial Corruption Supplementary Material (2013) (0)
Primal-Dual Block Frank-Wolfe (2019) (0)
Low-Complexity Feedback Allocation Algorithms For Cellular Uplink (2010) (0)

This paper list is powered by the following services:

What Schools Are Affiliated With Constantine Caramanis?

Constantine Caramanis is affiliated with the following schools:

University of Texas at Austin

Constantine Caramanis's Academic­Influence.com Rankings

Constantine Caramanis's Degrees

Why Is Constantine Caramanis Influential?

Constantine Caramanis's Published Works

Published Works

What Schools Are Affiliated With Constantine Caramanis?

Constantine Caramanis's AcademicInfluence.com Rankings