Volkan Cevher

Orcid: 0000-0002-5004-201X

According to our database1, Volkan Cevher authored at least 317 papers between 2001 and 2024.

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Bibliography

2024
A unified stochastic approximation framework for learning in games.
Math. Program., January, 2024

Mixed Nash for Robust Federated Learning.
Trans. Mach. Learn. Res., 2024

On the Generalization of Stochastic Gradient Descent with Momentum.
J. Mach. Learn. Res., 2024

Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networks.
J. Mach. Learn. Res., 2024

μ P<sup>2</sup>: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling.
CoRR, 2024

Unlearning as multi-task optimization: A normalized gradient difference approach with an adaptive learning rate.
CoRR, 2024

SAMPa: Sharpness-aware Minimization Parallelized.
CoRR, 2024

Revisiting SMoE Language Models by Evaluating Inefficiencies with Task Specific Expert Pruning.
CoRR, 2024

Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants.
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CoRR, 2024

Going beyond compositional generalization, DDPMs can produce zero-shot interpolation.
CoRR, 2024

HeNCler: Node Clustering in Heterophilous Graphs through Learned Asymmetric Similarity.
CoRR, 2024

Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces.
CoRR, 2024

Revisiting character-level adversarial attacks.
CoRR, 2024

Leveraging the Context through Multi-Round Interactions for Jailbreaking Attacks.
CoRR, 2024

Polynomial Convergence of Bandit No-Regret Dynamics in Congestion Games.
CoRR, 2024

Inference Optimization of Foundation Models on AI Accelerators.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Improving SAM Requires Rethinking its Optimization Formulation.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Imitation Learning in Discounted Linear MDPs without exploration assumptions.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Universal Gradient Methods for Stochastic Convex Optimization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning to Remove Cuts in Integer Linear Programming.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Truly No-Regret Learning in Constrained MDPs.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

REST: Efficient and Accelerated EEG Seizure Analysis through Residual State Updates.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Revisiting Character-level Adversarial Attacks for Language Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Robust NAS under adversarial training: benchmark, theory, and beyond.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Adversarial Training Should Be Cast as a Non-Zero-Sum Game.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Efficient Continual Finite-Sum Minimization.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Multilinear Operator Networks.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Generalization of Scaled Deep ResNets in the Mean-Field Regime.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Efficient local linearity regularization to overcome catastrophic overfitting.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Extreme Miscalibration and the Illusion of Adversarial Robustness.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023
Federated Learning under Covariate Shifts with Generalization Guarantees.
Trans. Mach. Learn. Res., 2023

Revisiting adversarial training for the worst-performing class.
Trans. Mach. Learn. Res., 2023

Provable benefits of general coverage conditions in efficient online RL with function approximation.
CoRR, 2023

Min-Max Optimization Made Simple: Approximating the Proximal Point Method via Contraction Maps.
Proceedings of the 2023 Symposium on Simplicity in Algorithms, 2023

Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Convergence of Encoder-only Shallow Transformers.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Stable Nonconvex-Nonconcave Training via Linear Interpolation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Exponential Lower Bounds for Fictitious Play in Potential Games.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient Online Clustering with Moving Costs.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Alternation makes the adversary weaker in two-player games.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Maximum Independent Set: Self-Training through Dynamic Programming.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Benign Overfitting in Deep Neural Networks under Lazy Training.
Proceedings of the International Conference on Machine Learning, 2023

When do Minimax-fair Learning and Empirical Risk Minimization Coincide?
Proceedings of the International Conference on Machine Learning, 2023

Semi Bandit dynamics in Congestion Games: Convergence to Nash Equilibrium and No-Regret Guarantees.
Proceedings of the International Conference on Machine Learning, 2023

What can online reinforcement learning with function approximation benefit from general coverage conditions?
Proceedings of the International Conference on Machine Learning, 2023

DiGress: Discrete Denoising diffusion for graph generation.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Distributed Extra-gradient with Optimal Complexity and Communication Guarantees.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Solving stochastic weak Minty variational inequalities without increasing batch size.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Finding Actual Descent Directions for Adversarial Training.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Regularization of polynomial networks for image recognition.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Evaluating the Fairness of Discriminative Foundation Models in Computer Vision.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022
On the Convergence of Stochastic Primal-Dual Hybrid Gradient.
SIAM J. Optim., 2022

A 16-Channel Neural Recording System-on-Chip With CHT Feature Extraction Processor in 65-nm CMOS.
IEEE J. Solid State Circuits, 2022

A Newton Frank-Wolfe method for constrained self-concordant minimization.
J. Glob. Optim., 2022

Understanding Deep Neural Function Approximation in Reinforcement Learning via ε-Greedy Exploration.
CoRR, 2022

Adversarial Audio Synthesis with Complex-valued Polynomial Networks.
CoRR, 2022

Learning in games from a stochastic approximation viewpoint.
CoRR, 2022

On the Complexity of a Practical Primal-Dual Coordinate Method.
CoRR, 2022

Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization).
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Generalization Properties of NAS under Activation and Skip Connection Search.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Proximal Point Imitation Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Identifiability and generalizability from multiple experts in Inverse Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sound and Complete Verification of Polynomial Networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Understanding Deep Neural Function Approximation in Reinforcement Learning via $\epsilon$-Greedy Exploration.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On the Double Descent of Random Features Models Trained with SGD.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models.
Proceedings of the International Conference on Machine Learning, 2022

UnderGrad: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees.
Proceedings of the International Conference on Machine Learning, 2022

A Natural Actor-Critic Framework for Zero-Sum Markov Games.
Proceedings of the International Conference on Machine Learning, 2022

Controlling the Complexity and Lipschitz Constant improves Polynomial Nets.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems.
Proceedings of the Tenth International Conference on Learning Representations, 2022

High Probability Bounds for a Class of Nonconvex Algorithms with AdaGrad Stepsize.
Proceedings of the Tenth International Conference on Learning Representations, 2022

The Spectral Bias of Polynomial Neural Networks.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Scalable Semidefinite Programming.
SIAM J. Math. Data Sci., 2021

An Optimal-Storage Approach to Semidefinite Programming Using Approximate Complementarity.
SIAM J. Optim., 2021

STORM+: Fully Adaptive SGD with Momentum for Nonconvex Optimization.
CoRR, 2021

Self-Supervised Neural Architecture Search for Imbalanced Datasets.
CoRR, 2021

Forward-reflected-backward method with variance reduction.
Comput. Optim. Appl., 2021

A first-order primal-dual method with adaptivity to local smoothness.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Subquadratic Overparameterization for Shallow Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

STORM+: Fully Adaptive SGD with Recursive Momentum for Nonconvex Optimization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The Effect of the Intrinsic Dimension on the Generalization of Quadratic Classifiers.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Sifting through the noise: Universal first-order methods for stochastic variational inequalities.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Convergence of adaptive algorithms for constrained weakly convex optimization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets.
Proceedings of the 38th International Conference on Machine Learning, 2021

Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach.
Proceedings of the 38th International Conference on Machine Learning, 2021

A Plug-and-Play Deep Image Prior.
Proceedings of the IEEE International Conference on Acoustics, 2021

A 16-Channel Wireless Neural Recording System-on-Chip with CHT Feature Extraction Processor in 65nm CMOS.
Proceedings of the IEEE Custom Integrated Circuits Conference, 2021

2020
Optimization for Reinforcement Learning: From a single agent to cooperative agents.
IEEE Signal Process. Mag., 2020

Machine Learning From Distributed, Streaming Data [From the Guest Editors].
IEEE Signal Process. Mag., 2020

An adaptive primal-dual framework for nonsmooth convex minimization.
Math. Program. Comput., 2020

Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms.
J. Mach. Learn. Res., 2020

Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections.
J. Mach. Learn. Res., 2020

Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch.
CoRR, 2020

Interaction-limited Inverse Reinforcement Learning.
CoRR, 2020

Environment Shaping in Reinforcement Learning using State Abstraction.
CoRR, 2020

Convergence of adaptive algorithms for weakly convex constrained optimization.
CoRR, 2020

On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Robust Reinforcement Learning via Adversarial training with Langevin Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Conditional gradient methods for stochastically constrained convex minimization.
Proceedings of the 37th International Conference on Machine Learning, 2020

Double-Loop Unadjusted Langevin Algorithm.
Proceedings of the 37th International Conference on Machine Learning, 2020

Efficient Proximal Mapping of the 1-path-norm of Shallow Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020

A new regret analysis for Adam-type algorithms.
Proceedings of the 37th International Conference on Machine Learning, 2020

Random extrapolation for primal-dual coordinate descent.
Proceedings of the 37th International Conference on Machine Learning, 2020

Lipschitz constant estimation of Neural Networks via sparse polynomial optimization.
Proceedings of the 8th International Conference on Learning Representations, 2020

Scalable Learning-Based Sampling Optimization for Compressive Dynamic MRI.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
A Learning-Based Framework for Quantized Compressed Sensing.
IEEE Signal Process. Lett., 2019

Streaming Low-Rank Matrix Approximation with an Application to Scientific Simulation.
SIAM J. Sci. Comput., 2019

On the linear convergence of the stochastic gradient method with constant step-size.
Optim. Lett., 2019

Convergence of the Exponentiated Gradient Method with Armijo Line Search.
J. Optim. Theory Appl., 2019

Fast and Provable ADMM for Learning with Generative Priors.
CoRR, 2019

On Certifying Non-uniform Bound against Adversarial Attacks.
CoRR, 2019

Scalable Learning-Based Sampling Optimization for Compressive Dynamic MRI.
CoRR, 2019

Stochastic Conditional Gradient Method for Composite Convex Minimization.
CoRR, 2019

An Introductory Guide to Fano's Inequality with Applications in Statistical Estimation.
CoRR, 2019

An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Stochastic Frank-Wolfe for Composite Convex Minimization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Fast and Provable ADMM for Learning with Generative Priors.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Overlapping Multi-Bandit Best Arm Identification.
Proceedings of the IEEE International Symposium on Information Theory, 2019

Interactive Teaching Algorithms for Inverse Reinforcement Learning.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator.
Proceedings of the 36th International Conference on Machine Learning, 2019

A Conditional-Gradient-Based Augmented Lagrangian Framework.
Proceedings of the 36th International Conference on Machine Learning, 2019

Efficient learning of smooth probability functions from Bernoulli tests with guarantees.
Proceedings of the 36th International Conference on Machine Learning, 2019

On Certifying Non-Uniform Bounds against Adversarial Attacks.
Proceedings of the 36th International Conference on Machine Learning, 2019

Finding Mixed Nash Equilibria of Generative Adversarial Networks.
Proceedings of the 36th International Conference on Machine Learning, 2019

Almost surely constrained convex optimization.
Proceedings of the 36th International Conference on Machine Learning, 2019

Rethinking Sampling in Parallel MRI: A Data-Driven Approach.
Proceedings of the 27th European Signal Processing Conference, 2019

Iterative Classroom Teaching.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
A Non-Euclidean Gradient Descent Framework for Non-Convex Matrix Factorization.
IEEE Trans. Signal Process., 2018

Learning-Based Compressive MRI.
IEEE Trans. Medical Imaging, 2018

Adaptive Learning-Based Compressive Sampling for Low-power Wireless Implants.
IEEE Trans. Circuits Syst. I Regul. Pap., 2018

A Smooth Primal-Dual Optimization Framework for Nonsmooth Composite Convex Minimization.
SIAM J. Optim., 2018

A Single-Phase, Proximal Path-Following Framework.
Math. Oper. Res., 2018

Near-Optimal Noisy Group Testing via Separate Decoding of Items.
IEEE J. Sel. Top. Signal Process., 2018

An Eight-Lane 7-Gb/s/pin Source Synchronous Single-Ended RX With Equalization and Far-End Crosstalk Cancellation for Backplane Channels.
IEEE J. Solid State Circuits, 2018

Efficient learning of smooth probability functions from Bernoulli tests with guarantees.
CoRR, 2018

Kernel Conjugate Gradient Methods with Random Projections.
CoRR, 2018

Mirrored Langevin Dynamics.
CoRR, 2018

Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral-Regularization Algorithms.
CoRR, 2018

Optimal Rates for Spectral-regularized Algorithms with Least-Squares Regression over Hilbert Spaces.
CoRR, 2018

Online Adaptive Methods, Universality and Acceleration.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Mirrored Langevin Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Adversarially Robust Optimization with Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming.
Proceedings of the 35th International Conference on Machine Learning, 2018

Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces.
Proceedings of the 35th International Conference on Machine Learning, 2018

Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods.
Proceedings of the 35th International Conference on Machine Learning, 2018

Let's be Honest: An Optimal No-Regret Framework for Zero-Sum Games.
Proceedings of the 35th International Conference on Machine Learning, 2018

Real-Time DCT Learning-based Reconstruction of Neural Signals.
Proceedings of the 26th European Signal Processing Conference, 2018

An area and power efficient on-the-fly LBCS transformation for implantable neuronal signal acquisition systems.
Proceedings of the 15th ACM International Conference on Computing Frontiers, 2018

Dimension-free Information Concentration via Exp-Concavity.
Proceedings of the Algorithmic Learning Theory, 2018

Stochastic Three-Composite Convex Minimization with a Linear Operator.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Combinatorial Penalties: Which structures are preserved by convex relaxations?
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Robust Maximization of Non-Submodular Objectives.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Limits on Support Recovery With Probabilistic Models: An Information-Theoretic Framework.
IEEE Trans. Inf. Theory, 2017

Practical Sketching Algorithms for Low-Rank Matrix Approximation.
SIAM J. Matrix Anal. Appl., 2017

Efficient and Near-Optimal Noisy Group Testing: An Information-Theoretic Framework.
CoRR, 2017

An adaptive sublinear-time block sparse fourier transform.
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017

Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Phase Transitions in the Pooled Data Problem.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Robust Submodular Maximization: A Non-Uniform Partitioning Approach.
Proceedings of the 34th International Conference on Machine Learning, 2017

How little does non-exact recovery help in group testing?
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization.
Proceedings of the 30th Conference on Learning Theory, 2017

DCT Learning-Based Hardware Design for Neural Signal Acquisition Systems.
Proceedings of the Computing Frontiers Conference, 2017

A distributed algorithm for partitioned robust submodular maximization.
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

Sketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Lower Bounds on Active Learning for Graphical Model Selection.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Faster Coordinate Descent via Adaptive Importance Sampling.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Adaptive-Rate Reconstruction of Time-Varying Signals With Application in Compressive Foreground Extraction.
IEEE Trans. Signal Process., 2016

Binary Sparse Coding of Convolutive Mixtures for Sound Localization and Separation via Spatialization.
IEEE Trans. Signal Process., 2016

On the Difficulty of Selecting Ising Models With Approximate Recovery.
IEEE Trans. Signal Inf. Process. over Networks, 2016

Fixed Points of Generalized Approximate Message Passing With Arbitrary Matrices.
IEEE Trans. Inf. Theory, 2016

Group-Sparse Model Selection: Hardness and Relaxations.
IEEE Trans. Inf. Theory, 2016

Computational methods for underdetermined convolutive speech localization and separation via model-based sparse component analysis.
Speech Commun., 2016

Stochastic Spectral Descent for Discrete Graphical Models.
IEEE J. Sel. Top. Signal Process., 2016

Learning-Based Compressive Subsampling.
IEEE J. Sel. Top. Signal Process., 2016

Randomized single-view algorithms for low-rank matrix approximation.
CoRR, 2016

Phase Transitions in Group Testing.
Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, 2016

Stochastic Three-Composite Convex Minimization.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

An Efficient Streaming Algorithm for the Submodular Cover Problem.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Converse bounds for noisy group testing with arbitrary measurement matrices.
Proceedings of the IEEE International Symposium on Information Theory, 2016

Partial recovery bounds for the sparse stochastic block model.
Proceedings of the IEEE International Symposium on Information Theory, 2016

Frank-Wolfe works for non-Lipschitz continuous gradient objectives: Scalable poisson phase retrieval.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Learning data triage: Linear decoding works for compressive MRI.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Learning-Based Near-Optimal Area-Power Trade-offs in Hardware Design for Neural Signal Acquisition.
Proceedings of the 26th edition on Great Lakes Symposium on VLSI, 2016

Estimation error of the constrained lasso.
Proceedings of the 54th Annual Allerton Conference on Communication, 2016

Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Convex Block-sparse Linear Regression with Expanders - Provably.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Time-Varying Gaussian Process Bandit Optimization.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Signal Recovery and System Calibration from Multiple Compressive Poisson Measurements.
SIAM J. Imaging Sci., 2015

Introduction to the issue on signal processing for big data.
IEEE J. Sel. Top. Signal Process., 2015

Designing Statistical Estimators That Balance Sample Size, Risk, and Computational Cost.
IEEE J. Sel. Top. Signal Process., 2015

Composite self-concordant minimization.
J. Mach. Learn. Res., 2015

Limits on Support Recovery with Probabilistic Models: An Information-Spectrum Approach.
CoRR, 2015

Adaptive-Rate Sparse Signal Reconstruction With Application in Compressive Background Subtraction.
CoRR, 2015

Structured Sparsity: Discrete and Convex approaches.
CoRR, 2015

Linear Inverse Problems with Norm and Sparsity Constraints.
CoRR, 2015

What's the Frequency, Kenneth?: Sublinear Fourier Sampling Off the Grid.
Algorithmica, 2015

A 5.9mW/Gb/s 7Gb/s/pin 8-lane single-ended RX with crosstalk cancellation scheme using a XCTLE and 56-tap XDFE in 32nm SOI CMOS.
Proceedings of the Symposium on VLSI Circuits, 2015

A Universal Primal-Dual Convex Optimization Framework.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Preconditioned Spectral Descent for Deep Learning.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Composite Convex Minimization Involving Self-concordant-Like Cost Functions.
Proceedings of the Modelling, Computation and Optimization in Information Systems and Management Sciences - Proceedings of the 3rd International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences, 2015

A concentration-of-measure inequality for multiple-measurement models.
Proceedings of the IEEE International Symposium on Information Theory, 2015

Sparse group covers and greedy tree approximations.
Proceedings of the IEEE International Symposium on Information Theory, 2015

Dynamic sparse state estimation using ℓ1-ℓ1 minimization: Adaptive-rate measurement bounds, algorithms and applications.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Consistency of ℓ1-regularized maximum-likelihood for compressive Poisson regression.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Active learning of self-concordant like multi-index functions.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

A primal-dual framework for mixtures of regularizers.
Proceedings of the 23rd European Signal Processing Conference, 2015

Scalable convex methods for phase retrieval.
Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015

Structured sampling and recovery of iEEG signals.
Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015

WASP: Scalable Bayes via barycenters of subset posteriors.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Sparsistency of 1-Regularized M-Estimators.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

A totally unimodular view of structured sparsity.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Stochastic Spectral Descent for Restricted Boltzmann Machines.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Bilinear Generalized Approximate Message Passing - Part II: Applications.
IEEE Trans. Signal Process., 2014

Bilinear Generalized Approximate Message Passing - Part I: Derivation.
IEEE Trans. Signal Process., 2014

Structured Sparsity Models for Reverberant Speech Separation.
IEEE ACM Trans. Audio Speech Lang. Process., 2014

Convexity in Source Separation : Models, geometry, and algorithms.
IEEE Signal Process. Mag., 2014

Convex Optimization for Big Data: Scalable, randomized, and parallel algorithms for big data analytics.
IEEE Signal Process. Mag., 2014

An Inexact Proximal Path-Following Algorithm for Constrained Convex Minimization.
SIAM J. Optim., 2014

Matrix Recipes for Hard Thresholding Methods.
J. Math. Imaging Vis., 2014

Convex Optimization for Big Data.
CoRR, 2014

A variational approach to stable principal component pursuit.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Model-based Sketching and Recovery with Expanders.
Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014

Constrained convex minimization via model-based excessive gap.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Time-Data Tradeoffs by Aggressive Smoothing.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Map estimation for Bayesian mixture models with submodular priors.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

Barrier smoothing for nonsmooth convex minimization.
Proceedings of the IEEE International Conference on Acoustics, 2014

Metric learning with rank and sparsity constraints.
Proceedings of the IEEE International Conference on Acoustics, 2014

Model-based sparse component analysis for reverberant speech localization.
Proceedings of the IEEE International Conference on Acoustics, 2014

Scalable Sparse Covariance Estimation via Self-Concordance.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Group-Sparse Model Selection: Hardness and Relaxations
CoRR, 2013

Randomized Low-Memory Singular Value Projection
CoRR, 2013

Bilinear Generalized Approximate Message Passing.
CoRR, 2013

Energy-aware adaptive bi-Lipschitz embeddings.
CoRR, 2013

High-Dimensional Gaussian Process Bandits.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions.
Proceedings of the 30th International Conference on Machine Learning, 2013

Sparse projections onto the simplex.
Proceedings of the 30th International Conference on Machine Learning, 2013

Fast proximal algorithms for Self-concordant function minimization with application to sparse graph selection.
Proceedings of the IEEE International Conference on Acoustics, 2013

Sparse simplex projections for portfolio optimization.
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

Tractability of interpretability via selection of group-sparse models.
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

To convexify or not? Regression with clustering penalties on graphs.
Proceedings of the 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2013

Manifold sparse beamforming.
Proceedings of the 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2013

2012
Compressible Distributions for High-Dimensional Statistics.
IEEE Trans. Inf. Theory, 2012

Bearing Estimation via Spatial Sparsity using Compressive Sensing.
IEEE Trans. Aerosp. Electron. Syst., 2012

Structured Sparsity Models for Multiparty Speech Recovery from Reverberant Recordings
CoRR, 2012

Sparse projections onto the simplex
CoRR, 2012

MATRIX ALPS: Accelerated low rank and sparse matrix reconstruction.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

Equivalence of synthesis and atomic formulations of sparse recovery.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

Active Learning of Multi-Index Function Models.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Combinatorial selection and least absolute shrinkage via the Clash algorithm.
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

Structured sparse coding for microphone array location calibration.
Proceedings of the ISCA Workshop on Statistical And Perceptual Audition, 2012

Learning ridge functions with randomized sampling in high dimensions.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

Hard thresholding with norm constraints.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

Filtered Variation method for denoising and sparse signal processing.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

Computational methods for structured sparse component analysis of convolutive speech mixtures.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2011
Learning Low-Dimensional Signal Models.
IEEE Signal Process. Mag., 2011

Greedy Dictionary Selection for Sparse Representation.
IEEE J. Sel. Top. Signal Process., 2011

A game theoretic approach to expander-based compressive sensing.
Proceedings of the 2011 IEEE International Symposium on Information Theory Proceedings, 2011

Multi-Party Speech Recovery Exploiting Structured Sparsity Models.
Proceedings of the 12th Annual Conference of the International Speech Communication Association, 2011

Compressive sensing meets game theory.
Proceedings of the IEEE International Conference on Acoustics, 2011

Online performance guarantees for sparse recovery.
Proceedings of the IEEE International Conference on Acoustics, 2011

An ALPS view of sparse recovery.
Proceedings of the IEEE International Conference on Acoustics, 2011

Model-based compressive sensing for multi-party distant speech recognition.
Proceedings of the IEEE International Conference on Acoustics, 2011

Recipes on hard thresholding methods.
Proceedings of the 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2011

Compressive sensing under matrix uncertainties: An Approximate Message Passing approach.
Proceedings of the Conference Record of the Forty Fifth Asilomar Conference on Signals, 2011

2010
Model-based compressive sensing.
IEEE Trans. Inf. Theory, 2010

Sparse Signal Recovery and Acquisition with Graphical Models.
IEEE Signal Process. Mag., 2010

Low-Dimensional Models for Dimensionality Reduction and Signal Recovery: A Geometric Perspective.
Proc. IEEE, 2010

Submodular Dictionary Selection for Sparse Representation.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Distributed bearing estimation via matrix completion.
Proceedings of the IEEE International Conference on Acoustics, 2010

2009
Vehicle Speed Estimation Using Acoustic Wave Patterns.
IEEE Trans. Signal Process., 2009

Acoustic sensor network design for position estimation.
ACM Trans. Sens. Networks, 2009

Learning with Compressible Priors.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Near-optimal Bayesian localization via incoherence and sparsity.
Proceedings of the 8th International Conference on Information Processing in Sensor Networks, 2009

Recovery of compressible signals in unions of subspaces.
Proceedings of the 43rd Annual Conference on Information Sciences and Systems, 2009

Model-based compressive sensing for signal ensembles.
Proceedings of the 47th Annual Allerton Conference on Communication, 2009

2008
Sparse Signal Recovery Using Markov Random Fields.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Pareto Frontiers of Sensor Networks for Localization.
Proceedings of the 7th International Conference on Information Processing in Sensor Networks, 2008

Compressed sensing for multi-view tracking and 3-D voxel reconstruction.
Proceedings of the International Conference on Image Processing, 2008

A compressive beamforming method.
Proceedings of the IEEE International Conference on Acoustics, 2008

Factorized variational approximations for acoustic multi source localization.
Proceedings of the IEEE International Conference on Acoustics, 2008

Compressive wireless arrays for bearing estimation.
Proceedings of the IEEE International Conference on Acoustics, 2008

Distributed target localization via spatial sparsity.
Proceedings of the 2008 16th European Signal Processing Conference, 2008

Compressive Sensing for Background Subtraction.
Proceedings of the Computer Vision, 2008

2007
Decentralized State Initialization with Delay Compensation for Multi-modal Sensor Networks.
J. VLSI Signal Process., 2007

Acoustic Multitarget Tracking Using Direction-of-Arrival Batches.
IEEE Trans. Signal Process., 2007

Target Tracking Using a Joint Acoustic Video System.
IEEE Trans. Multim., 2007

Optimal Maneuvering of Seismic Sensors for Localization of Subsurface Targets.
IEEE Trans. Geosci. Remote. Sens., 2007

Low computation and low latency algorithms for distributed sensor network initialization.
Signal Image Video Process., 2007

Joint Acoustic-Video Fingerprinting of Vehicles, Part II.
Proceedings of the IEEE International Conference on Acoustics, 2007

Joint Acoustic-Video Fingerprinting of Vehicles, Part I.
Proceedings of the IEEE International Conference on Acoustics, 2007

2006
A Range-Only Multiple Target Particle Filter Tracker.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

A Monte-Carlo Method for Initializing Distributed Tracking Algorithms.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Optimal Experiments With Seismic Sensors.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

On low-power analog implementation of particle filters for target tracking.
Proceedings of the 14th European Signal Processing Conference, 2006

A joint radar-acoustic particle filter tracker with acoustic propagation delay compensation.
Proceedings of the 14th European Signal Processing Conference, 2006

2005
A Bayesian Framework for Target Tracking using Acoustic and Image Measurements.
PhD thesis, 2005

General direction-of-arrival tracking with acoustic nodes.
IEEE Trans. Signal Process., 2005

Proposal strategies for joint state-space tracking with particle filters.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

2004
Fast initialization of particle filters using a modified metropolis-Hastings algorithm: mode-hungry approach.
Proceedings of the 2004 IEEE International Conference on Acoustics, 2004

2001
Sensor array calibration via tracking with the extended Kalman filter.
Proceedings of the IEEE International Conference on Acoustics, 2001


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