Mert Pilanci

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 143

Top Venues

Publications

Fangzhao Zhang, Mert Pilanci
Analyzing Neural Network-Based Generative Diffusion Models through Convex Optimization. CoRR (2024)
Yifei Wang, Mert Pilanci
Correction to: Sketching the Krylov subspace: faster computation of the entire ridge regularization path. J. Supercomput. 80 (1) (2024)
Fangzhao Zhang, Mert Pilanci
Spectral Adapter: Fine-Tuning in Spectral Space. CoRR (2024)
Aaron Mishkin, Mert Pilanci, Mark Schmidt
Faster Convergence of Stochastic Accelerated Gradient Descent under Interpolation. CoRR (2024)
Rajarshi Saha, Naomi Sagan, Varun Srivastava, Andrea J. Goldsmith, Mert Pilanci
Compressing Large Language Models using Low Rank and Low Precision Decomposition. CoRR (2024)
Sungyoon Kim, Mert Pilanci
Convex Relaxations of ReLU Neural Networks Approximate Global Optima in Polynomial Time. CoRR (2024)
Neophytos Charalambides, Hessam Mahdavifar, Mert Pilanci, Alfred O. Hero III
Iterative Sketching for Secure Coded Regression. IEEE J. Sel. Areas Inf. Theory 5 (2024)
Prateek Verma, Mert Pilanci
Towards Signal Processing In Large Language Models. CoRR (2024)
Ivan Villa-Renteria, Mason L. Wang, Zachary Shah, Zhe Li, Soohyun Kim, Neelesh Ramachandran, Mert Pilanci
Subtractive Training for Music Stem Insertion using Latent Diffusion Models. CoRR (2024)
Arda Sahiner, Tolga Ergen, Batu Ozturkler, John M. Pauly, Morteza Mardani, Mert Pilanci
Scaling Convex Neural Networks with Burer-Monteiro Factorization. ICLR (2024)
Alexandros E. Tzikas, Licio Romao, Mert Pilanci, Alessandro Abate, Mykel J. Kochenderfer
Distributed Markov Chain Monte Carlo Sampling based on the Alternating Direction Method of Multipliers. CoRR (2024)
Yifei Wang, Sungyoon Kim, Paul Chu, Indu Subramaniam, Mert Pilanci
Randomized Geometric Algebra Methods for Convex Neural Networks. CoRR (2024)
Emil Biju, Anirudh Sriram, Mert Pilanci
AdaPTwin: Low-Cost Adaptive Compression of Product Twins in Transformers. CoRR (2024)
Fangzhao Zhang, Mert Pilanci
Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models. CoRR (2024)
Soheil Hor, Ying Qian, Mert Pilanci, Amin Arbabian
Adaptive Inference: Theoretical Limits and Unexplored Opportunities. CoRR (2024)
Daniel Kuelbs, Sanjay Lall, Mert Pilanci
Adversarial Training of Two-Layer Polynomial and ReLU Activation Networks via Convex Optimization. CoRR (2024)
Emi Zeger, Yifei Wang, Aaron Mishkin, Tolga Ergen, Emmanuel J. Candès, Mert Pilanci
A Library of Mirrors: Deep Neural Nets in Low Dimensions are Convex Lasso Models with Reflection Features. CoRR (2024)
Aaron Mishkin, Mert Pilanci
Optimal Sets and Solution Paths of ReLU Networks. CoRR (2023)
Fangzhao Zhang, Mert Pilanci
Optimal Shrinkage for Distributed Second-Order Optimization. ICML (2023)
Rajat Vadiraj Dwaraknath, Tolga Ergen, Mert Pilanci
Fixing the NTK: From Neural Network Linearizations to Exact Convex Programs. CoRR (2023)
Yifei Wang, Mert Pilanci
Sketching the Krylov subspace: faster computation of the entire ridge regularization path. J. Supercomput. 79 (16) (2023)
Neophytos Charalambides, Mert Pilanci, Alfred O. Hero III
Gradient Coding through Iterative Block Leverage Score Sampling. CoRR (2023)
Rajarshi Saha, Varun Srivastava, Mert Pilanci
Matrix Compression via Randomized Low Rank and Low Precision Factorization. NeurIPS (2023)
Rajarshi Saha, Varun Srivastava, Mert Pilanci
Matrix Compression via Randomized Low Rank and Low Precision Factorization. CoRR (2023)
Neophytos Charalambides, Mert Pilanci, Alfred O. Hero III
Federated Coded Matrix Inversion. CoRR (2023)
Burak Bartan, Mert Pilanci
Distributed Sketching for Randomized Optimization: Exact Characterization, Concentration, and Lower Bounds. IEEE Trans. Inf. Theory 69 (6) (2023)
Yifei Wang, Tolga Ergen, Mert Pilanci
Parallel Deep Neural Networks Have Zero Duality Gap. ICLR (2023)
Burak Bartan, Mert Pilanci
Randomized Polar Codes for Anytime Distributed Machine Learning. IEEE J. Sel. Areas Inf. Theory 4 (2023)
Tolga Ergen, Halil Ibrahim Gulluk, Jonathan Lacotte, Mert Pilanci
Globally Optimal Training of Neural Networks with Threshold Activation Functions. ICLR (2023)
Annesha Ghosh, Gordon Wetzstein, Mert Pilanci, Sara Fridovich-Keil
Volumetric Reconstruction Resolves Off-Resonance Artifacts in Static and Dynamic PROPELLER MRI. CoRR (2023)
Rajat Vadiraj Dwaraknath, Tolga Ergen, Mert Pilanci
Fixing the NTK: From Neural Network Linearizations to Exact Convex Programs. NeurIPS (2023)
Tolga Ergen, Halil Ibrahim Gulluk, Jonathan Lacotte, Mert Pilanci
Globally Optimal Training of Neural Networks with Threshold Activation Functions. CoRR (2023)
Tolga Ergen, Mert Pilanci
Path Regularization: A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks. NeurIPS (2023)
Burak Bartan, Mert Pilanci
Convex Optimization of Deep Polynomial and ReLU Activation Neural Networks. ICASSP (2023)
Neophytos Charalambides, Mert Pilanci, Alfred O. Hero III
Securely Aggregated Coded Matrix Inversion. IEEE J. Sel. Areas Inf. Theory 4 (2023)
Rajarshi Saha, Mert Pilanci, Andrea J. Goldsmith
Low Precision Representations for High Dimensional Models. ICASSP (2023)
Burak Bartan, Mert Pilanci
Randomized Polar Codes for Anytime Distributed Machine Learning. CoRR (2023)
Yifei Wang, Mert Pilanci
Polynomial-Time Solutions for ReLU Network Training: A Complexity Classification via Max-Cut and Zonotopes. CoRR (2023)
Les Atlas, Nicholas Rasmussen, Felix Schwock, Mert Pilanci
Complex Clipping for Improved Generalization in Machine Learning. CoRR (2023)
Tolga Ergen, Mert Pilanci
The Convex Landscape of Neural Networks: Characterizing Global Optima and Stationary Points via Lasso Models. CoRR (2023)
Mert Pilanci
From Complexity to Clarity: Analytical Expressions of Deep Neural Network Weights via Clifford's Geometric Algebra and Convexity. CoRR (2023)
Aaron Mishkin, Mert Pilanci
Optimal Sets and Solution Paths of ReLU Networks. ICML (2023)
Neophytos Charalambides, Hessam Mahdavifar, Mert Pilanci, Alfred O. Hero III
Iterative Sketching for Secure Coded Regression. CoRR (2023)
Batu Ozturkler, Arda Sahiner, Tolga Ergen, Arjun D. Desai, Christopher M. Sandino, Shreyas Vasanawala, John M. Pauly, Morteza Mardani, Mert Pilanci
GLEAM: Greedy Learning for Large-Scale Accelerated MRI Reconstruction. CoRR (2022)
Rajarshi Saha, Mert Pilanci, Andrea J. Goldsmith
Minimax Optimal Quantization of Linear Models: Information-Theoretic Limits and Efficient Algorithms. CoRR (2022)
Beliz Gunel, Arda Sahiner, Arjun D. Desai, Akshay S. Chaudhari, Shreyas Vasanawala, Mert Pilanci, John M. Pauly
Scale-Equivariant Unrolled Neural Networks for Data-Efficient Accelerated MRI Reconstruction. CoRR (2022)
Mert Pilanci
Computational Polarization: An Information-Theoretic Method for Resilient Computing. IEEE Trans. Inf. Theory 68 (4) (2022)
Burak Bartan, Mert Pilanci
Distributed Sketching for Randomized Optimization: Exact Characterization, Concentration and Lower Bounds. CoRR (2022)
Neophytos Charalambides, Hessam Mahdavifar, Mert Pilanci, Alfred O. Hero III
Orthonormal Sketches for Secure Coded Regression. ISIT (2022)
Burak Bartan, Mert Pilanci
Neural Fisher Discriminant Analysis: Optimal Neural Network Embeddings in Polynomial Time. ICML (2022)
Richard Swartzbaugh, Amil Khanzada, Praveen Govindan, Mert Pilanci, Ayomide Owoyemi, Les Atlas, Hugo Estrada, Richard Nall, Michael Lotito, Rich Falcone, J. Jennifer Ranjani
Using a Novel COVID-19 Calculator to Measure Positive U.S. Socio-Economic Impact of a COVID-19 Pre-Screening Solution (AI/ML). CoRR (2022)
Tolga Ergen, Arda Sahiner, Batu Ozturkler, John M. Pauly, Morteza Mardani, Mert Pilanci
Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization. ICLR (2022)
Arda Sahiner, Tolga Ergen, Batu Ozturkler, John M. Pauly, Morteza Mardani, Mert Pilanci
Unraveling Attention via Convex Duality: Analysis and Interpretations of Vision Transformers. ICML (2022)
Aaron Mishkin, Arda Sahiner, Mert Pilanci
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions. ICML (2022)
Tavor Z. Baharav, Gary Cheng, Mert Pilanci, David Tse
Approximate Function Evaluation via Multi-Armed Bandits. CoRR (2022)
Shuyun Tang, Xinying Hu, Les Atlas, Amil Khanzada, Mert Pilanci
Hierarchical Multi-modal Transformer for Automatic Detection of COVID-19. SPML (2022)
Arda Sahiner, Tolga Ergen, Batu Ozturkler, John M. Pauly, Morteza Mardani, Mert Pilanci
Unraveling Attention via Convex Duality: Analysis and Interpretations of Vision Transformers. CoRR (2022)
Jonathan Lacotte, Mert Pilanci
Adaptive and Oblivious Randomized Subspace Methods for High-Dimensional Optimization: Sharp Analysis and Lower Bounds. IEEE Trans. Inf. Theory 68 (5) (2022)
Neophytos Charalambides, Hessam Mahdavifar, Mert Pilanci, Alfred O. Hero III
Orthonormal Sketches for Secure Coded Regression}. CoRR (2022)
Soheil Hor, Mert Pilanci, Amin Arbabian
A Data-Driven Waveform Adaptation Method for Mm-Wave Gait Classification at the Edge. IEEE Signal Process. Lett. 29 (2022)
Neophytos Charalambides, Mert Pilanci, Alfred O. Hero III
Secure Linear MDS Coded Matrix Inversion. Allerton (2022)
Aaron Mishkin, Arda Sahiner, Mert Pilanci
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions. CoRR (2022)
Yifei Wang, Jonathan Lacotte, Mert Pilanci
The Hidden Convex Optimization Landscape of Regularized Two-Layer ReLU Networks: an Exact Characterization of Optimal Solutions. ICLR (2022)
Tavor Z. Baharav, Gary Cheng, Mert Pilanci, David Tse
Approximate Function Evaluation via Multi-Armed Bandits. AISTATS (2022)
Rajarshi Saha, Mert Pilanci, Andrea J. Goldsmith
Efficient Randomized Subspace Embeddings for Distributed Optimization Under a Communication Budget. IEEE J. Sel. Areas Inf. Theory 3 (2) (2022)
Arda Sahiner, Tolga Ergen, Batu Ozturkler, Burak Bartan, John M. Pauly, Morteza Mardani, Mert Pilanci
Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions. ICLR (2022)
Esin Darici, Nicholas Rasmussen, J. Jennifer Ranjani, Jaclyn Xiao, Gunvant Chaudhari, Akanksha Rajput, Praveen Govindan, Minami Yamaura, Laura Gomezjurado, Amil Khanzada, Mert Pilanci
Using Deep Learning with Large Aggregated Datasets for COVID-19 Classification from Cough. CoRR (2022)
Beliz Gunel, Arda Sahiner, Arjun D. Desai, Akshay S. Chaudhari, Shreyas Vasanawala, Mert Pilanci, John M. Pauly
Scale-Equivariant Unrolled Neural Networks for Data-Efficient Accelerated MRI Reconstruction. MICCAI (6) (2022)
Yifei Wang, Mert Pilanci
The Convex Geometry of Backpropagation: Neural Network Gradient Flows Converge to Extreme Points of the Dual Convex Program. ICLR (2022)
Yifei Wang, Yixuan Hua, Emmanuel J. Candès, Mert Pilanci
ReLU Neural Networks Learn the Simplest Models: Neural Isometry and Exact Recovery. CoRR (2022)
Yifei Wang, Peng Chen, Mert Pilanci, Wuchen Li
Optimal Neural Network Approximation of Wasserstein Gradient Direction via Convex Optimization. CoRR (2022)
Neophytos Charalambides, Mert Pilanci, Alfred O. Hero III
Secure Linear MDS Coded Matrix Inversion. CoRR (2022)
Lawrence H. Kim, Rahul Goel, Jia Liang, Mert Pilanci, Pablo E. Paredes
Linear Predictive Coding for Acute Stress Prediction from Computer Mouse Movements. EMBC (2021)
Mert Pilanci
Computational Polarization: An Information-theoretic Method for Resilient Computing. CoRR (2021)
Arda Sahiner, Morteza Mardani, Batu Ozturkler, Mert Pilanci, John M. Pauly
Convex Regularization behind Neural Reconstruction. ICLR (2021)
Arda Sahiner, Tolga Ergen, John M. Pauly, Mert Pilanci
Vector-output ReLU Neural Network Problems are Copositive Programs: Convex Analysis of Two Layer Networks and Polynomial-time Algorithms. ICLR (2021)
Rajarshi Saha, Mert Pilanci, Andrea J. Goldsmith
Distributed Learning and Democratic Embeddings: Polynomial-Time Source Coding Schemes Can Achieve Minimax Lower Bounds for Distributed Gradient Descent under Communication Constraints. CoRR (2021)
Tolga Ergen, Mert Pilanci
Global Optimality Beyond Two Layers: Training Deep ReLU Networks via Convex Programs. ICML (2021)
Vikul Gupta, Burak Bartan, Tolga Ergen, Mert Pilanci
Convex Neural Autoregressive Models: Towards Tractable, Expressive, and Theoretically-Backed Models for Sequential Forecasting and Generation. ICASSP (2021)
Tolga Ergen, Mert Pilanci
Revealing the Structure of Deep Neural Networks via Convex Duality. ICML (2021)
Tolga Ergen, Mert Pilanci
Path Regularization: A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks. CoRR (2021)
Yifei Wang, Mert Pilanci
The Convex Geometry of Backpropagation: Neural Network Gradient Flows Converge to Extreme Points of the Dual Convex Program. CoRR (2021)
Burak Bartan, Mert Pilanci
Training Quantized Neural Networks to Global Optimality via Semidefinite Programming. ICML (2021)
Arda Sahiner, Tolga Ergen, Batu Ozturkler, Burak Bartan, John M. Pauly, Morteza Mardani, Mert Pilanci
Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions. CoRR (2021)
Tolga Ergen, Mert Pilanci
Global Optimality Beyond Two Layers: Training Deep ReLU Networks via Convex Programs. CoRR (2021)
Yifei Wang, Tolga Ergen, Mert Pilanci
Parallel Deep Neural Networks Have Zero Duality Gap. CoRR (2021)
Tolga Ergen, Mert Pilanci
Implicit Convex Regularizers of CNN Architectures: Convex Optimization of Two- and Three-Layer Networks in Polynomial Time. ICLR (2021)
Jonathan Lacotte, Mert Pilanci
Fast Convex Quadratic Optimization Solvers with Adaptive Sketching-based Preconditioners. CoRR (2021)
Michal Derezinski, Jonathan Lacotte, Mert Pilanci, Michael W. Mahoney
Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update. NeurIPS (2021)
Jonathan Lacotte, Yifei Wang, Mert Pilanci
Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality. CoRR (2021)
Neophytos Charalambides, Mert Pilanci, Alfred O. Hero III
Approximate Weighted C R Coded Matrix Multiplication. ICASSP (2021)
Jonathan Lacotte, Yifei Wang, Mert Pilanci
Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality. ICML (2021)
Burak Bartan, Mert Pilanci
Training Quantized Neural Networks to Global Optimality via Semidefinite Programming. CoRR (2021)
Michal Derezinski, Jonathan Lacotte, Mert Pilanci, Michael W. Mahoney
Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update. CoRR (2021)
Burak Bartan, Mert Pilanci
Neural Spectrahedra and Semidefinite Lifts: Global Convex Optimization of Polynomial Activation Neural Networks in Fully Polynomial-Time. CoRR (2021)
Tolga Ergen, Mert Pilanci
Convex Geometry and Duality of Over-parameterized Neural Networks. J. Mach. Learn. Res. 22 (2021)
Tolga Ergen, Arda Sahiner, Batu Ozturkler, John M. Pauly, Morteza Mardani, Mert Pilanci
Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization. CoRR (2021)
Mert Pilanci, Tolga Ergen
Neural Networks are Convex Regularizers: Exact Polynomial-time Convex Optimization Formulations for Two-layer Networks. ICML (2020)
Elaina Chai, Mert Pilanci, Boris Murmann
Separating the Effects of Batch Normalization on CNN Training Speed and Stability Using Classical Adaptive Filter Theory. CoRR (2020)
Jonathan Lacotte, Mert Pilanci
Optimal Randomized First-Order Methods for Least-Squares Problems. CoRR (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Mert Pilanci